Profit Factor And Expectancy For Your Trading Strategy
Profit Factor And Expectancy For Your Trading Strategy
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2 years of PTI with the economy
As PTI comes onto two years, I felt like making this post on account of seeing multiple people supporting PML-N for having an allegedly better economy for Pakistan, particularly with allegations present that PTI has done nothing for the economy. So here's a short list of some major achievements done by PTI in contrast to PML-N.
Stopping Pakistan from defaulting: The move to devalue the rupee was one done despite knowing the backlash that would be faced. Under Nawaz Sharif the rupee was artificially overvalued through loans and forex reserves, this meant Pakistan had no sustainable way for repaying those massive loans. Imran Khan on the other hand had to approach the IMF due to these overlaying maturing debts, lack of growth in exports under PMLN, decline in Foreign Direct Investment and an ever higher import bill. This was done at the cost of letting the rupee massively devalue against the dollar, however paved the path for economic stability as noted by the IMF.
Renewed focus on taxation: Easily the most controversial facet of the economic policy by PTI, but one that has shown merit and results. Overall, there has been a 40% increase in returns filers and a 17% revenue increase. This coupled with a massive austerity scheme, meant that the government has started an incline towards increasing it's revenues. While this hasn't been met with open arms, it presents a solution to the everpresent crisis that the Pakistan government has faced, in it's inability to increase it's revenues. Not only that, but the general taxation system was streamlined, making it easier for individuals to file taxes. Introductions of new apps and consolidating activities for the FBR were among the efforts as well. Moreover, businesses that were entitled to tax refunds are finally being granted them, under PMLN they were held onto so as to inflate collection numbers, however under PTI that has changed and it's not inflated. It is worth noting, that because of the covid-19 pandemic, the effect of the austerity schemes and feasibility have seriously dampened, and it's created a bigger problem for increasing revenue collection.
It is worth noting, that some may criticise the overall decrease in the account deficit to be a result of the decrease in imports, and the increase in worker remittances, however this was indeed a result of the overall economic impact from the covid-19 pandemic. And that general trends support the notion of exports increasing and the account deficit decreasing in the second quarter of 2019.
Tourism: The reforms and measures taken to facilitate tourism in Pakistan were evidently among the most successful — Pakistan went from being sidelined to being amongst the worlds top destinations to visit. There were multiple reasons for this, the removal of the mandatory NOC, the initiative for online visas for upto 175 countries alongside visa-on-arrival for 50 countries were among the facilitating measures taken for tourism.
Foreign Direct Investment: What can be appreciated is the general reception of Pakistan's economic outlook, where FDI climbed by upto 137% within this fiscal year, gathering upto nearly $2.1 billion. Yet, once again — the pandemic will undoubtedly cause most countries to rethink their economic policies for now, and the overall FDI might see a downward trend with regards to global decrease in FDI. Despite, the increases in FDI are welcomed, especially considering total foreign investment rose 380 percent to $2.375 billion in July-March FY2020. Yet the sustainability of this remains to be seen.
Dealing with covid: Despite all odds, Pakistan has somehow managed to deal well with the pandemic. Coming out relatively alright, in perspective of countries such as India, Mexico, Italy, Brazil etc. The factor that plays out, is that despite being incredibly vulnerable, the country managed to pull through and has markedly reduced the impact of the virus. With regards to the economy, taking a bold risk of abating a complete lockdown, whilst met with criticism was once again a factor that showed competency. Keeping in mind that 51 million Pakistanis lived below the poverty line, and the adverse effect it would have on the economy. Pakistan managed to come through the economic contraction with only a -0.38% growth. Although the full effects are still not abated or understood, what's commendable is the fact that Pakistan under PTI has kept itself from an even worse situation. Whilst managing to keep covid under relative control. Especially given increases in exports despite the pandemic in countries such as Qatar, Saudi Arabia, and Italy.
This is by no means a highly comprehensive list, just my opinion on some of the bigger achievements; saving the economy from defaulting, adopting tax reforms, tourism reforms, export reforms among them whilst managing covid and economic stability with relative success. There are of course a multitude of other factors, successfully avoiding a blacklist from the FATF, macroeconomic reforms, attempts to strengthen the working class; ehsaas programs, Naya Pakistan housing schemes alongside other relief efforts. These are measures in accordance with curtailing the effect of increasing taxation and attempts to abate the economic slowdown that came as a result of forcing an increase in government revenue. Alongside the focus on multiple new hydroelectric dams, industrial cities, reduction of the PM office staff from 552 to 298, 10 billion tree project and an overall renewed interest in renewable energy and green Pakistan. The list is comprehensive. Pakistan remains on a rocky path, it is not out of the woods yet. Covid-19 has seriously hampered the overall projections, and caused a worldwide economic contraction. Not only that, but there are criticisms that can be attributed to the government as well, as they are not without fault. However, the overall achievements of the government with regards to the economy do present hope for the long-term fiscal policy and development of Pakistan.
Some trading wisdom, tools and information I picked up along the way that helped me be a better trader. Maybe it can help you too.
Its a bit lengthy and I tried to condense it as much as I can. So take everything at a high level as each subject is has a lot more depth but fundamentally if you distill it down its just taking simple things and applying your experience using them to add nuance and better deploy them. There are exceptions to everything that you will learn with experience or have already learned. If you know something extra or something to add to it to implement it better or more accurately. Then great! However, my intention of this post is just a high level overview. Trading can be far too nuanced to go into in this post and would take forever to type up every exception (not to mention the traders individual personality). If you take the general information as a starting point, hopefully you will learn the edge cases long the way and learn how to use the more effectively if you end up using them. I apologize in advice for any errors or typos. Introduction After reflecting on my fun (cough) trading journey that was more akin to rolling around on broken glass and wondering if brown glass will help me predict market direction better than green glass. Buying a $100 indicator at 2 am when I was acting a fool, looking at it and going at and going "This is a piece of lagging crap, I miss out on a large part of the fundamental move and never using it for even one trade". All while struggling with massive over trading and bad habits because I would get bored watching a single well placed trade on fold for the day. Also, I wanted to get rich quick. On top all of that I had a terminal Stage 4 case of FOMO on every time the price would move up and then down then back up. Just think about all those extra pips I could have trading both directions as it moves across the chart! I can just sell right when it goes down, then buy right before it goes up again. Its so easy right? Well, turns out it was not as easy as I thought and I lost a fair chunk of change and hit my head against the wall a lot until it clicked. Which is how I came up with a mixed bag of things that I now call "Trade the Trade" which helped support how I wanted to trade so I can still trade intra day price action like a rabid money without throwing away all my bananas. Why Make This Post? - Core Topic of Discussion I wish to share a concept I came up with that helped me become a reliable trader. Support the weakness of how I like to trade. Also, explaining what I do helps reinforce my understanding of the information I share as I have to put words to it and not just use internalized processes. I came up with a method that helped me get my head straight when trading intra day. I call it "Trade the Trade" as I am making mini trades inside of a trade setup I make from analysis on a higher timeframe that would take multiple days to unfold or longer. I will share information, principles, techniques I used and learned from others I talked to on the internet (mixed bag of folks from armatures to professionals, and random internet people) that helped me form a trading style that worked for me. Even people who are not good at trading can say something that might make it click in your head so I would absorbed all the information I could get.I will share the details of how I approach the methodology and the tools in my trading belt that I picked up by filtering through many tools, indicators strategies and witchcraft. Hopefully you read something that ends up helping you be a better trader. I learned a lot from people who make community posts so I wanted to give back now that I got my ducks in a row. General Trading Advice If your struggling finding your own trading style, fixing weakness's in it, getting started, being reliably profitable or have no framework to build yourself higher with, hopefully you can use the below advice to help provide some direction or clarity to moving forward to be a better trader.
KEEP IT SIMPLE. Do not throw a million things on your chart from the get go or over analyzing what the market is doing while trying to learn the basics. Tons of stuff on your chart can actually slow your learning by distracting your focus on all your bells and whistles and not the price action.
PRICE ACTION. Learn how to read price action. Not just the common formations, but larger groups of bars that form the market structure. Those formations carry more weight the higher the time frame they form on. If struggle to understand what is going on or what your looking at, move to a higher time frame.
INDICATORS. If you do use them you should try to understand how every indicator you use calculates its values. Many indicators are lagging indicators, understanding how it calculates the values can help you learn how to identify the market structure before the indicator would trigger a signal . This will help you understand why the signal is a lagged signal. If you understand that you can easily learn to look at the price action right before the signal and learn to watch for that price action on top of it almost trigging a signal so you can get in at a better position and assume less downside risk. I recommend using no more than 1-2 indicators for simplicity, but your free to use as many as you think you think you need or works for your strategy/trading style.
PSYCOLOGY. First, FOMO is real, don't feed the beast. When you trade you should always have an entry and exit. If you miss your entry do not chase it, wait for a new entry. At its core trading is gambling and your looking for an edge against the house (the other market participants). With that in mind, treat as such. Do not risk more than you can afford to lose. If you are afraid to lose it will negatively effect your trade decisions. Finally, be honest with your self and bad trading happens. No one is going to play trade cop and keep you in line, that's your job.
TRADE DECISION MARKING: Before you enter any trade you should have an entry and exit area. As you learn price action you will get better entries and better exits. Use a larger zone and stop loss at the start while learning. Then you can tighten it up as you gain experience. If you do not have a area you wish to exit, or you are entering because "the markets looking like its gonna go up". Do not enter the trade. Have a reason for everything you do, if you cannot logically explain why then you probably should not be doing it.
ROBOTS/ALGOS: Loved by some, hated by many who lost it all to one, and surrounded by scams on the internet. If you make your own, find a legit one that works and paid for it or lost it all on a crappy one, more power to ya. I do not use robots because I do not like having a robot in control of my money. There is too many edge cases for me to be ok with it.However, the best piece of advice about algos was that the guy had a algo/robot for each market condition (trending/ranging) and would make personalized versions of each for currency pairs as each one has its own personality and can make the same type of movement along side another currency pair but the price action can look way different or the move can be lagged or leading. So whenever he does his own analysis and he sees a trend, he turns the trend trading robot on. If the trend stops, and it starts to range he turns the range trading robot on. He uses robots to trade the market types that he is bad at trading. For example, I suck at trend trading because I just suck at sitting on my hands and letting my trade do its thing.
Trade the Trade - The Methodology
Base Principles These are the base principles I use behind "Trade the Trade". Its called that because you are technically trading inside your larger high time frame trade as it hopefully goes as you have analyzed with the trade setup. It allows you to scratch that intraday trading itch, while not being blind to the bigger market at play. It can help make sense of why the price respects, rejects or flat out ignores support/resistance/pivots.
Trade Setup: Find a trade setup using high level time frames (daily, 4hr, or 1hr time frames). The trade setup will be used as a base for starting to figure out a bias for the markets direction for that day.
Indicator Data: Check any indicators you use (I use Stochastic RSI and Relative Vigor Index) for any useful information on higher timeframes.
Support Resistance: See if any support/resistance/pivot points are in currently being tested/resisted by the price. Also check for any that are within reach so they might become in play through out the day throughout the day (which can influence your bias at least until the price reaches it if it was already moving that direction from previous days/weeks price action).
Currency Strength/Weakness: I use the TradeVision currency strength/weakness dashboard to see if the strength/weakness supports the narrative of my trade and as an early indicator when to keep a closer eye for signs of the price reversing.Without the tool, the same concept can be someone accomplished with fundamentals and checking for higher level trends and checking cross currency pairs for trends as well to indicate strength/weakness, ranging (and where it is in that range) or try to get some general bias from a higher level chart that may help you out. However, it wont help you intra day unless your monitoring the currency's index or a bunch of charts related to the currency.
Watch For Trading Opportunities: Personally I make a mental short list and alerts on TradingView of currency pairs that are close to key levels and so I get a notification if it reaches there so I can check it out. I am not against trading both directions, I just try to trade my bias before the market tries to commit to a direction. Then if I get out of that trade I will scalp against the trend of the day and hold trades longer that are with it.Then when you see a opportunity assume the directional bias you made up earlier (unless the market solidly confirms with price action the direction while waiting for an entry) by trying to look for additional confirmation via indicators, price action on support/resistances etc on the low level time frame or higher level ones like hourly/4hr as the day goes on when the price reaches key areas or makes new market structures to get a good spot to enter a trade in the direction of your bias.Then enter your trade and use the market structures to determine how much of a stop you need. Once your in the trade just monitor it and watch the price action/indicators/tools you use to see if its at risk of going against you. If you really believe the market wont reach your TP and looks like its going to turn against you, then close the trade. Don't just hold on to it for principle and let it draw down on principle or the hope it does not hit your stop loss.
Trade Duration Hold your trades as long or little as you want that fits your personality and trading style/trade analysis. Personally I do not hold trades past the end of the day (I do in some cases when a strong trend folds) and I do not hold trades over the weekends. My TP targets are always places I think it can reach within the day. Typically I try to be flat before I sleep and trade intra day price movements only. Just depends on the higher level outlook, I have to get in at really good prices for me to want to hold a trade and it has to be going strong. Then I will set a slightly aggressive stop on it before I leave. I do know several people that swing trade and hold trades for a long period of time. That is just not a trading style that works for me.
Enhance Your Success Rate Below is information I picked up over the years that helped me enhance my success rate with not only guessing intra day market bias (even if it has not broken into the trend for the day yet (aka pre London open when the end of Asia likes to act funny sometimes), but also with trading price action intra day. People always say "When you enter a trade have an entry and exits. I am of the belief that most people do not have problem with the entry, its the exit. They either hold too long, or don't hold long enough. With the below tools, drawings, or instruments, hopefully you can increase your individual probability of a successful trade. **P.S.*\* Your mileage will vary depending on your ability to correctly draw, implement and interpret the below items. They take time and practice to implement with a high degree of proficiency. If you have any questions about how to do that with anything listed, comment below and I will reply as I can. I don't want to answer the same question a million times in a pm. Tools and Methods Used This is just a high level overview of what I use. Each one of the actions I could go way more in-depth on but I would be here for a week typing something up of I did that. So take the information as a base level understanding of how I use the method or tool. There is always nuance and edge cases that you learn from experience.
I keep a general high level Macro outlook for currencies. I dont get too deep into Fundamentals and just keep an eye out for news. If I am already in a trade I will hold it if its far enough away from my entry. However, I wont enter right before/during news as it can invalidate your setup.
I started with the basics of learning the standard price action formations/patterns and candles. You can find tons of free info on that online, google is your friend. Then I stared at charts and said "why did the price do that or do this etc" then after a while I started to understand what's happening without having to think about it and I can see the market structure without having to look as closely as I did in the past.
After many many hours of staring at 5 min charts for 15 hours a day 5 days a week I learned how to look at 5 min charts and be like "Oh that's a hammer on the 15 min etc. If you keep track of time you can do the same for hourly candles as well and you will start to see market structure naturally. However I typically trade in a two chart panel window so I have a 15 min and 5 min chart up when trading intra day so I dont have to think too hard about it.
Draw support resistance lines on Daily/4hr timeframes. I prefer to use body of the candle instead of the wick for support/resistance.
You can find support/resistance liquidity levels through out the day as well and trade those if the price retraces back through levels its already been through that same day.
It would be a bit length to explain exactly the best place to draw them. If your unsure there is plenty of free resources on the internet. Just try to use your head and look for price levels where the price was "Supported" or it "Resisted" that price level then slap a line on it. Draw as few or as many lines as you feel helps you and your style. I tend to lean on the side of fewer. I typically do about 6 lines main support/resistances (3 of each).
Draw two Fibonacci Extensions. One on the daily timeframe, and then one on the 4hr time frame. Then you can trade the Fibonacci levels and use them for TP targets or entry zones if price action respects the level. Also you can use it along with support/resistance and pivots if they happen to line up or are very close.
I cannot really figure out how to put it into words how to draw a Fib if you dont know how. I will have to make a picture to demonstrate it. If your interested post below and I will draw one up and post a link. Probably the easiest way to understand. Just keep in mind the Fib you draw on the 4hr time frame will be inside the daily timeframe one.
The TradeVision2020 dashboard that I use just helps me keep a tab on the current market post plus any swing strength/momentum a currency might have on higher time frames. Helps me look for shifts in the market or confirmation that the bias it already has in momentum is continuing. I have found that often currencies when they get really/weak or strong might continue for several days or even longer like a full week or more. We recently had what felt like 1 week or so of flat out Yen weakness which was making some things wonky. All it does is allow me to look at the dashboard instead of a million other charts.
I use two that work well for my intra day style. The Stochastic RSI is just like a RSI but its faster. The second is the Relative Vigor Index which I use to detect swings in momentum and divergences in bullish/bearish momentum. I have used many others in the past, but as I have grown and got better as a trader I have found making my analysis simpler has improved my trading.I dont like the whole idea of have 43 different indicators on 32 different time frames light up a dashboard to be green for me to enter a trade. With how I do it now, I have a clear understanding of what I expect to happen and why. That way when it does happen I understand the move and dont get freaked out if the market moves funny after I am in the trade.
Conclusion I use the above tools/indicators/resources/philosophy's to trade intra day price action that sometimes ends up as noise in the grand scheme of the markets movement.use that method until the price action for the day proves the bias assumption wrong. Also you can couple that with things like Stoch RSI + Relative Vigor Index to find divergences which can increase the probability of your targeted guesses. Trade Example from Yesterday This is an example of a trade I took today and why I took it. I used the following core areas to make my trade decision.
Fundamental Bias: I already had a bullish fundamental outlook on EUUSD with expecting the markets to price in future similes due a higher an higher chance of Biden winning on paper as the election closed in and a "Blue wave" coming which would lead to a weaker dollar. Also, the Euro Zone is getting hammered with COVID pretty hard plus Brexit drama so I had a strong Euro bias.NOTE: As frame of reference, all the other pairs I trade I traded as if they were ranging and trade a range. Markets are messed up right now.
Currency Strength/Weakness: I use a tool that gives me a currency strength/weakness dashboard called TradeVision2020. Helps me track individual currency strength/weakness intra day. Took me about a month to get used to it, but helps me keep track of intra day strength/weakness that can add a bias to trade direction as the day unfolds. Like "Will this run have a 2nd or 3rd push higher" or "I should look to TP at the first sign of weakness in the push" type bias data. You still got to use your brain and figure out the best decision. It wont make choices for you, its only a guide.NOTE: I am not trying to adverse the tool (if providing the code is against sub rules let me know), its just a tool I use every day that helps me with directional bias calls. I am sharing the coupon code that was given to me when I found out about the tool in the TradingView forex chatroom and the guy gave me the code to use when I signed up. I dont want someone to read the name and want to try it out then overpay for no reason. The coupon will give you 40% off. Coupon Code: 3F7A0T5T
Higher Timeframe Analysis: Detected some early signs of Bearish Divergence on the 1hr chart using a on a higher time frame using a Stochastic RSI. Then I saw more confirmation on 5 min charts using Relative Vigor Index to help time my entry mid session.
Pivot Points: I treat pivot points like support/resistance and trade them as such using price action to give me some idea how its being treated by the market. Pretty straight forward.
It may seem like a lot of stuff to process on the fly while trying to figure out live price action but, for the fundamental bias for a pair should already baked in your mindset for any currency pair you trade. For the currency strength/weakness I stare at the dashboard 12-15 hours a day so I am always trying to keep a pulse on what's going or shifts so that's not really a factor when I want to enter as I would not look to enter if I felt the market was shifting against me. Then the higher timeframe analysis had already happened when I woke up, so it was a game of "Stare at the 5 min chart until the price does something interesting" Trade Example: Today , I went long EUUSD long bias when I first looked at the chart after waking up around 9-10pm Eastern. Fortunately, the first large drop had already happened so I had a easy baseline price movement to work with. I then used tool for currency strength/weakness monitoring, Pivot Points, and bearish divergence detected using Stochastic RSI and Relative Vigor Index. I first noticed Bearish Divergence on the 1hr time frame using the Stochastic RSI and got confirmation intra day on the 5 min time frame with the Relative Vigor Index. I ended up buying the second mini dip around midnight Eastern because it was already dancing along the pivot point that the price had been dancing along since the big drop below the pivot point and dipped below it and then shortly closed back above it. I put a stop loss below the first large dip. With a TP goal of the middle point pivot line Then I waited for confirmation or invalidation of my trade. I ended up getting confirmation with Bearish Divergence from the second large dip so I tightened up my stop to below that smaller drip and waited for the London open. Not only was it not a lower low, I could see the divergence with the Relative Vigor Index. It then ran into London and kept going with tons of momentum. Blew past my TP target so I let it run to see where the momentum stopped. Ended up TP'ing at the Pivot Point support/resistance above the middle pivot line. Random Note: The Asian session has its own unique price action characteristics that happen regularly enough that you can easily trade them when they happen with high degrees of success. It takes time to learn them all and confidently trade them as its happening. If you trade Asia you should learn to recognize them as they can fake you out if you do not understand what's going on. TL;DR At the end of the day there is no magic solution that just works. You have to find out what works for you and then what people say works for them. Test it out and see if it works for you or if you can adapt it to work for you. If it does not work or your just not interested then ignore it. At the end of the day, you have to use your brain to make correct trading decisions. Blindly following indicators may work sometimes in certain market conditions, but trading with information you don't understand can burn you just as easily as help you. Its like playing with fire. So, get out there and grind it out. It will either click or it wont. Not everyone has the mindset or is capable of changing to be a successful trader. Trading is gambling, you do all this work to get a edge on the house. Trading without the edge or an edge you understand how to use will only leave your broker happy in the end.
Factset: How You can Invest in Hedge Funds’ Biggest Investment Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now: Their latest 8k filing reported the following: Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions. Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic. Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019. Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results. The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020. FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders. As you can see, there’s not much of a negative sign in sight here. It makes sense considering how FactSet’s FCF has never slowed down: https://preview.redd.it/frmtdk8e9hk51.png?width=276&format=png&auto=webp&s=1c0ff12539e0b2f9dbfda13d0565c5ce2b6f8f1a https://preview.redd.it/6axdb6lh9hk51.png?width=593&format=png&auto=webp&s=9af1673272a5a2d8df28f60f4707e948a00e5ff1 FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with. Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis: https://www.investopedia.com/terms/f/factset.asp https://preview.redd.it/yo71y6qj9hk51.png?width=355&format=png&auto=webp&s=a9414bdaa03c06114ca052304a26fae2773c3e45 FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015: https://preview.redd.it/oxaa1wel9hk51.png?width=443&format=png&auto=webp&s=13d60d2518980360c403364f7150392ab83d07d7 So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33% https://preview.redd.it/e4trju3p9hk51.png?width=387&format=png&auto=webp&s=6f6bee15f836c47e73121054ec60459f147d353e EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded. https://preview.redd.it/yl7f58tr9hk51.png?width=489&format=png&auto=webp&s=68906b9ecbcf6d886393c4ff40f81bdecab9e9fd P/E has declined in the past 2 years, making it a great time to buy. https://preview.redd.it/4mqw3t4t9hk51.png?width=445&format=png&auto=webp&s=e8d719f4913883b044c4150f11b8732e14797b6d Increasing ROE despite lowering of leverage post 2016 https://preview.redd.it/lt34avzu9hk51.png?width=441&format=png&auto=webp&s=f3742ed87cd1c2ccb7a3d3ee71ae8c7007313b2b Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself. https://preview.redd.it/fliirmpx9hk51.png?width=370&format=png&auto=webp&s=1216eddeadb4f84c8f4f48692a2f962ba2f1e848 SGA expense/Gross profit has been declining despite expansion of offices I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful. Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in. Calls have shitty greeks, but if you're ballsy October 450s LOL, I'm holding shares I’d say it’s a great long term investment, and it should at least be on your watchlist.
Everything You Always Wanted To Know About Swaps* (*But Were Afraid To Ask)
Hello, dummies It's your old pal, Fuzzy. As I'm sure you've all noticed, a lot of the stuff that gets posted here is - to put it delicately - fucking ridiculous. More backwards-ass shit gets posted to wallstreetbets than you'd see on a Westboro Baptist community message board. I mean, I had a look at the daily thread yesterday and..... yeesh. I know, I know. We all make like the divine Laura Dern circa 1992 on the daily and stick our hands deep into this steaming heap of shit to find the nuggets of valuable and/or hilarious information within (thanks for reading, BTW). I agree. I love it just the way it is too. That's what makes WSB great. What I'm getting at is that a lot of the stuff that gets posted here - notwithstanding it being funny or interesting - is just... wrong. Like, fucking your cousin wrong. And to be clear, I mean the fucking your *first* cousin kinda wrong, before my Southerners in the back get all het up (simmer down, Billy Ray - I know Mabel's twice removed on your grand-sister's side). Truly, I try to let it slide. Idomybit to try and put you on the right path. Most of the time, I sleep easy no matter how badly I've seen someone explain what a bank liquidity crisis is. But out of all of those tens of thousands of misguided, autistic attempts at understanding the world of high finance, one thing gets so consistently - so *emphatically* - fucked up and misunderstood by you retards that last night I felt obligated at the end of a long work day to pull together this edition of Finance with Fuzzy just for you. It's so serious I'm not even going to make a u/pokimane gag. Have you guessed what it is yet? Here's a clue. It's in the title of the post. That's right, friends. Today in the neighborhood we're going to talk all about hedging in financial markets - spots, swaps, collars, forwards, CDS, synthetic CDOs, all that fun shit. Don't worry; I'm going to explain what all the scary words mean and how they impact your OTM RH positions along the way. We're going to break it down like this. (1) "What's a hedge, Fuzzy?" (2) Common Hedging Strategies and (3) All About ISDAs and Credit Default Swaps. Before we begin. For the nerds and JV traders in the back (and anyone else who needs to hear this up front) - I am simplifying these descriptions for the purposes of this post. I am also obviously not going to try and cover every exotic form of hedge under the sun or give a detailed summation of what caused the financial crisis. If you are interested in something specific ask a question, but don't try and impress me with your Investopedia skills or technical points I didn't cover; I will just be forced to flex my years of IRL experience on you in the comments and you'll look like a big dummy. TL;DR? Fuck you. There is no TL;DR. You've come this far already. What's a few more paragraphs? Put down the Cheetos and try to concentrate for the next 5-7 minutes. You'll learn something, and I promise I'll be gentle. Ready? Let's get started. 1.The Tao of Risk: Hedging as a Way of Life The simplest way to characterize what a hedge 'is' is to imagine every action having a binary outcome. One is bad, one is good. Red lines, green lines; uppie, downie. With me so far? Good. A 'hedge' is simply the employment of a strategy to mitigate the effect of your action having the wrong binary outcome. You wanted X, but you got Z! Frowny face. A hedge strategy introduces a third outcome. If you hedged against the possibility of Z happening, then you can wind up with Y instead. Not as good as X, but not as bad as Z. The technical definition I like to give my idiot juniors is as follows: Utilization of a defensive strategy to mitigate risk, at a fraction of the cost to capital of the risk itself. Congratulations. You just finished Hedging 101. "But Fuzzy, that's easy! I just sold a naked call against my 95% OTM put! I'm adequately hedged!". Spoiler alert: you're not (although good work on executing a collar, which I describe below). What I'm talking about here is what would be referred to as a 'perfect hedge'; a binary outcome where downside is totally mitigated by a risk management strategy. That's not how it works IRL. Pay attention; this is the tricky part. You can't take a single position and conclude that you're adequately hedged because risks are fluid, not static. So you need to constantly adjust your position in order to maximize the value of the hedge and insure your position. You also need to consider exposure to more than one category of risk. There are micro (specific exposure) risks, and macro (trend exposure) risks, and both need to factor into the hedge calculus. That's why, in the real world, the value of hedging depends entirely on the design of the hedging strategy itself. Here, when we say "value" of the hedge, we're not talking about cash money - we're talking about the intrinsic value of the hedge relative to the the risk profile of your underlying exposure. To achieve this, people hedge dynamically. In wallstreetbets terms, this means that as the value of your position changes, you need to change your hedges too. The idea is to efficiently and continuously distribute and rebalance risk across different states and periods, taking value from states in which the marginal cost of the hedge is low and putting it back into states where marginal cost of the hedge is high, until the shadow value of your underlying exposure is equalized across your positions. The punchline, I guess, is that one static position is a hedge in the same way that the finger paintings you make for your wife's boyfriend are art - it's technically correct, but you're only playing yourself by believing it. Anyway. Obviously doing this as a small potatoes trader is hard but it's worth taking into account. Enough basic shit. So how does this work in markets? 2. A Hedging Taxonomy The best place to start here is a practical question. What does a business need to hedge against? Think about the specific risk that an individual business faces. These are legion, so I'm just going to list a few of the key ones that apply to most corporates. (1) You have commodity risk for the shit you buy or the shit you use. (2) You have currency risk for the money you borrow. (3) You have rate risk on the debt you carry. (4) You have offtake risk for the shit you sell. Complicated, right? To help address the many and varied ways that shit can go wrong in a sophisticated market, smart operators like yours truly have devised a whole bundle of different instruments which can help you manage the risk. I might write about some of the more complicated ones in a later post if people are interested (CDO/CLOs, strip/stack hedges and bond swaps with option toggles come to mind) but let's stick to the basics for now. (i) Swaps A swap is one of the most common forms of hedge instrument, and they're used by pretty much everyone that can afford them. The language is complicated but the concept isn't, so pay attention and you'll be fine. This is the most important part of this section so it'll be the longest one. Swaps are derivative contracts with two counterparties (before you ask, you can't trade 'em on an exchange - they're OTC instruments only). They're used to exchange one cash flow for another cash flow of equal expected value; doing this allows you to take speculative positions on certain financial prices or to alter the cash flows of existing assets or liabilities within a business. "Wait, Fuzz; slow down! What do you mean sets of cash flows?". Fear not, little autist. Ol' Fuzz has you covered. The cash flows I'm talking about are referred to in swap-land as 'legs'. One leg is fixed - a set payment that's the same every time it gets paid - and the other is variable - it fluctuates (typically indexed off the price of the underlying risk that you are speculating on / protecting against). You set it up at the start so that they're notionally equal and the two legs net off; so at open, the swap is a zero NPV instrument. Here's where the fun starts. If the price that you based the variable leg of the swap on changes, the value of the swap will shift; the party on the wrong side of the move ponies up via the variable payment. It's a zero sum game. I'll give you an example using the most vanilla swap around; an interest rate trade. Here's how it works. You borrow money from a bank, and they charge you a rate of interest. You lock the rate up front, because you're smart like that. But then - quelle surprise! - the rate gets better after you borrow. Now you're bagholding to the tune of, I don't know, 5 bps. Doesn't sound like much but on a billion dollar loan that's a lot of money (a classic example of the kind of 'small, deep hole' that's terrible for profits). Now, if you had a swap contract on the rate before you entered the trade, you're set; if the rate goes down, you get a payment under the swap. If it goes up, whatever payment you're making to the bank is netted off by the fact that you're borrowing at a sub-market rate. Win-win! Or, at least, Lose Less / Lose Less. That's the name of the game in hedging. There are many different kinds of swaps, some of which are pretty exotic; but they're all different variations on the same theme. If your business has exposure to something which fluctuates in price, you trade swaps to hedge against the fluctuation. The valuation of swaps is also super interesting but I guarantee you that 99% of you won't understand it so I'm not going to try and explain it here although I encourage you to google it if you're interested. Because they're OTC, none of them are filed publicly. Someeeeeetimes you see an ISDA (dsicussed below) but the confirms themselves (the individual swaps) are not filed. You can usually read about the hedging strategy in a 10-K, though. For what it's worth, most modern credit agreements ban speculative hedging. Top tip: This is occasionally something worth checking in credit agreements when you invest in businesses that are debt issuers - being able to do this increases the risk profile significantly and is particularly important in times of economic volatility (ctrl+f "non-speculative" in the credit agreement to be sure). (ii) Forwards A forward is a contract made today for the future delivery of an asset at a pre-agreed price. That's it. "But Fuzzy! That sounds just like a futures contract!". I know. Confusing, right? Just like a futures trade, forwards are generally used in commodity or forex land to protect against price fluctuations. The differences between forwards and futures are small but significant. I'm not going to go into super boring detail because I don't think many of you are commodities traders but it is still an important thing to understand even if you're just an RH jockey, so stick with me. Just like swaps, forwards are OTC contracts - they're not publicly traded. This is distinct from futures, which are traded on exchanges (see The Ballad Of Big Dick Vick for some more color on this). In a forward, no money changes hands until the maturity date of the contract when delivery and receipt are carried out; price and quantity are locked in from day 1. As you now know having read about BDV, futures are marked to market daily, and normally people close them out with synthetic settlement using an inverse position. They're also liquid, and that makes them easier to unwind or close out in case shit goes sideways. People use forwards when they absolutely have to get rid of the thing they made (or take delivery of the thing they need). If you're a miner, or a farmer, you use this shit to make sure that at the end of the production cycle, you can get rid of the shit you made (and you won't get fucked by someone taking cash settlement over delivery). If you're a buyer, you use them to guarantee that you'll get whatever the shit is that you'll need at a price agreed in advance. Because they're OTC, you can also exactly tailor them to the requirements of your particular circumstances. These contracts are incredibly byzantine (and there are even crazier synthetic forwards you can see in money markets for the true degenerate fund managers). In my experience, only Texan oilfield magnates, commodities traders, and the weirdo forex crowd fuck with them. I (i) do not own a 10 gallon hat or a novelty size belt buckle (ii) do not wake up in the middle of the night freaking out about the price of pork fat and (iii) love greenbacks too much to care about other countries' monopoly money, so I don't fuck with them. (iii) Collars No, not the kind your wife is encouraging you to wear try out to 'spice things up' in the bedroom during quarantine. Collars are actually the hedging strategy most applicable to WSB. Collars deal with options! Hooray! To execute a basic collar (also called a wrapper by tea-drinking Brits and people from the Antipodes), you buy an out of the money put while simultaneously writing a covered call on the same equity. The put protects your position against price drops and writing the call produces income that offsets the put premium. Doing this limits your tendies (you can only profit up to the strike price of the call) but also writes down your risk. If you screen large volume trades with a VOL/OI of more than 3 or 4x (and they're not bullshit biotech stocks), you can sometimes see these being constructed in real time as hedge funds protect themselves on their shorts. (3) All About ISDAs, CDS and Synthetic CDOs You may have heard about the mythical ISDA. Much like an indenture (discussed in my post on $F), it's a magic legal machine that lets you build swaps via trade confirms with a willing counterparty. They are very complicated legal documents and you need to be a true expert to fuck with them. Fortunately, I am, so I do. They're made of two parts; a Master (which is a form agreement that's always the same) and a Schedule (which amends the Master to include your specific terms). They are also the engine behind just about every major credit crunch of the last 10+ years. First - a brief explainer. An ISDA is a not in and of itself a hedge - it's an umbrella contract that governs the terms of your swaps, which you use to construct your hedge position. You can trade commodities, forex, rates, whatever, all under the same ISDA. Let me explain. Remember when we talked about swaps? Right. So. You can trade swaps on just about anything. In the late 90s and early 2000s, people had the smart idea of using other people's debt and or credit ratings as the variable leg of swap documentation. These are called credit default swaps. I was actually starting out at a bank during this time and, I gotta tell you, the only thing I can compare people's enthusiasm for this shit to was that moment in your early teens when you discover jerking off. Except, unlike your bathroom bound shame sessions to Mom's Sears catalogue, every single person you know felt that way too; and they're all doing it at once. It was a fiscal circlejerk of epic proportions, and the financial crisis was the inevitable bukkake finish. WSB autism is absolutely no comparison for the enthusiasm people had during this time for lighting each other's money on fire. Here's how it works. You pick a company. Any company. Maybe even your own! And then you write a swap. In the swap, you define "Credit Event" with respect to that company's debt as the variable leg . And you write in... whatever you want. A ratings downgrade, default under the docs, failure to meet a leverage ratio or FCCR for a certain testing period... whatever. Now, this started out as a hedge position, just like we discussed above. The purest of intentions, of course. But then people realized - if bad shit happens, you make money. And banks... don't like calling in loans or forcing bankruptcies. Can you smell what the moral hazard is cooking? Enter synthetic CDOs. CDOs are basically pools of asset backed securities that invest in debt (loans or bonds). They've been around for a minute but they got famous in the 2000s because a shitload of them containing subprime mortgage debt went belly up in 2008. This got a lot of publicity because a lot of sad looking rednecks got foreclosed on and were interviewed on CNBC. "OH!", the people cried. "Look at those big bad bankers buying up subprime loans! They caused this!". Wrong answer, America. The debt wasn't the problem. What a lot of people don't realize is that the real meat of the problem was not in regular way CDOs investing in bundles of shit mortgage debts in synthetic CDOs investing in CDS predicated on that debt. They're synthetic because they don't have a stake in the actual underlying debt; just the instruments riding on the coattails. The reason these are so popular (and remain so) is that smart structured attorneys and bankers like your faithful correspondent realized that an even more profitable and efficient way of building high yield products with limited downside was investing in instruments that profit from failure of debt and in instruments that rely on that debt and then hedging that exposure with other CDS instruments in paired trades, and on and on up the chain. The problem with doing this was that everyone wound up exposed to everybody else's books as a result, and when one went tits up, everybody did. Hence, recession, Basel III, etc. Thanks, Obama. Heavy investment in CDS can also have a warping effect on the price of debt (something else that happened during the pre-financial crisis years and is starting to happen again now). This happens in three different ways. (1) Investors who previously were long on the debt hedge their position by selling CDS protection on the underlying, putting downward pressure on the debt price. (2) Investors who previously shorted the debt switch to buying CDS protection because the relatively illiquid debt (partic. when its a bond) trades at a discount below par compared to the CDS. The resulting reduction in short selling puts upward pressure on the bond price. (3) The delta in price and actual value of the debt tempts some investors to become NBTs (neg basis traders) who long the debt and purchase CDS protection. If traders can't take leverage, nothing happens to the price of the debt. If basis traders can take leverage (which is nearly always the case because they're holding a hedged position), they can push up or depress the debt price, goosing swap premiums etc. Anyway. Enough technical details. I could keep going. This is a fascinating topic that is very poorly understood and explained, mainly because the people that caused it all still work on the street and use the same tactics today (it's also terribly taught at business schools because none of the teachers were actually around to see how this played out live). But it relates to the topic of today's lesson, so I thought I'd include it here. Work depending, I'll be back next week with a covenant breakdown. Most upvoted ticker gets the post. *EDIT 1\* In a total blowout, $PLAY won. So it's D&B time next week. Post will drop Monday at market open.
I have a habit of backtesting every strategy I find as long as it makes sense. I find it fun, and even if the strategy ends up being underperforming, it gives me a good excuse to gain valuable chart experience that would normally take years to gather. After I backtest something, I compare it to my current methodology, and usually conclude that mine is better either because it has a better performance or the new method requires too much time to manage (Spoiler: until now, I like this better) During the last two days, I have worked on backtesting ParallaxFx strategy, as it seemed promising and it seemed to fit my personality (a lazy fuck who will happily halve his yearly return if it means he can spend 10% less time in front of the screens). My backtesting is preliminary, and I didn't delve very deep in the data gathering. I usually track all sort of stuff, but for this first pass, I sticked to the main indicators of performance over a restricted sample size of markets. Before I share my results with you, I always feel the need to make a preface that I know most people will ignore.
I am words on your screen. You cannot trust me. I could have edited this or literally just typed random numbers on a spreadsheet. Do your own research if you want to trust my conclusion.
Even if you trust me, you need to do backtesting for yourself. The goal of backtesting isn't simply to figure out whether a strategy has an edge: it's a way to get used to how the market flows (valuable experience you will bring on to any other strategy) and how the strategy behaves. You need to see it with your own eyes to allow your subconscious mind to be at ease when it comes time to trade it live: the only way to truly trust your strategy during a period of drawdown, is to have seen it work over hundreds of trades in the past.
Strategy I am not going to go into the strategy in this thread. If you haven't read the series of threads by the guy who shared it, go here. As suggested by my mentioned personality type, I went with the passive management options of ParallaxFx's strategy. After a valid setup forms, I place two orders of half my risk. I add or remove 1 pip from each level to account for spread.
The first at the 23.6 retracement.
The second at the 38.2 retracement.
Both orders have a stop loss at the 78.6 retracement.
Both orders have the same target at the -100.0 extension.
If price moves to the -38.2 extension, I delete any unfilled orders.
I do not scale out, I do not move to breakeven, I place my orders and walk away.
Sample I tested this strategy over the seven major currency pairs: AUDUSD, USDCAD, NZDUSD, GBPUSD, USDJPY, EURUSD, USDCHF. The time period started on January 1th 2018 and ended on July 1th 2020, so a 2.5 years backtest. I tested over the D1 timeframe, and I plan on testing other timeframes. My "protocol" for backtesting is that, if I like what I see during this phase, I will move to the second phase where I'll backtest over 5 years and 28 currency pairs. Units of measure I used R multiples to track my performance. If you don't know what they are, I'm too sleepy to explain right now. This article explains what they are. The gist is that the results you'll see do not take into consideration compounding and they normalize volatility (something pips don't do, and why pips are in my opinion a terrible unit of measure for performance) as well as percentage risk (you can attach variable risk profiles on your R values to optimize position sizing in order to maximize returns and minimize drawdowns, but I won't get into that). Results I am not going to link the spreadsheet directly, because it is in my GDrive folder and that would allow you to see my personal information. I will attach screenshots of both the results and the list of trades. In the latter, I have included the day of entry for each trade, so if you're up to the task, you can cross-reference all the trades I have placed to make sure I am not making things up. Overall results: R Curve and Segmented performance. List of trades: 1, 2, 3, 4, 5, 6, 7. Something to note: I treated every half position as an individual trade for the sake of simplicity. It should not mess with the results, but it simply means you will see huge streaks of wins and losses. This does not matter because I'm half risk in each of them, so a winstreak of 6 trades is just a winstreak of 3 trades. For reference:
Profit Factor: 2.34
Return: 100.47 R
Strike rate: 48.28%
Average win: 2.51 R
Average loss: -1.00 R
Thoughts Nice. I'll keep testing. As of now it is vastly better than my current strategy.
I always dreamt of becoming a multi millionaire in 5 to 10 years but this guy has brought an interesting point to the table:
Day Trading Market Ceiling There also a Day Trading Market Ceiling. A successful day trader (not an investor, though) will eventually get capped out, as the market simply can’t accommodate an infinitely increasing position size for a particular strategy. To make more the trader either needs to alter the strategy, or also trade something else…and this may or may not work. Change one thing and you can’t assume all else will stay the same. To attain the returns discussed in the “How Much Day Traders Make,” multiple trades are made each day. Trades are likely only lasting a couple minutes. While multiple-millions of dollars worth of stocks, futures or currencies may change hands over the course of couple hours, day traders have precise entry points. Therefore, position size is limited to the amount of liquidity (volume) available at the exact moment a trader needs to get into and out of trades. Investors, hedge funds and mutual funds can accumulate or dispose of positions over weeks, taking advantage of days or even weeks worth liquidity. Day traders don’t have that luxury. It doesn’t matter if a stock trades millions of shares a day; if there is only 100 shares available when they need to take the trade (based on the strategy) that’s all they get. That’s an extreme example, but at any given moment there isn’t infinite liquidity available–there is what there is, and that means there is a limit to how big of a position you can accumulate and dispose of when your strategy calls for it. Based on personal experience, in day trading forex I wouldn’t be comfortable taking more than 5 standard lots on a day trade. Some may take more, most traders would take way less. Taking a larger amount would mean significantly increased risk of slippage or partial fills (you end up with the whole position on losing trades, but only partial positions on some winning trades). Possible gains attained by taking a larger position are offset by these negative factors. At 10:1 or 15:1 leverage a forex day trader–using a day trading forex strategy similar to mine— may cap out at around a $50,000 to $75,000 account (including leverage, that means trading close to $1million). Beyond that, they may find little additional gains, unless they alter their strategy, take longer term trades or stagger their entries and exits at various prices. Changing a strategy to accommodate a larger position isn’t a bad thing, but it takes additional research/practice time…and is it worth it? Only each individual can answer that for them self. In the ES futures market I cap out at about 10 contracts, and that only requires a $40,000 to $75,000 account (maybe even less depending on how much you risk per trade). There is no reason to trade more in my opinion. Could you day trade more contracts? Sure, you could probably get away with 100 contracts some days/some trades…but why? It would take a long time to work up to carrying those sorts of positions, and even trading a few contracts can produce a good living. The same goes for the stock market. Even in a very liquid stock or ETF like the SPDR S&P 500 (SPY) you will hit a limit on how much you can effectively trade on a short time frame. It may be a big limit, but you do hit it. To see the minimum amount of capital you need to day trade, see How Much Do I Need to Become a Day Trader. The bottom line is that you hit a limit on the amount of capital you can utilize effectively, and beyond that your percentage returns will likely decrease. For example, it’s much easier to make 10% a month on a $20,000 account than it is to make 10% a month on $20,000,000. That means day trader tend to withdraw all proceeds over and above their “efficient capital limit.” So a $50,000 day trading forex accounts stays a $50,000 account and monthly profits are withdrawn and spent (like any other job) or allocated to something else. In other words the account doesn’t keep compounding indefinitely, the trader nor the market can withstand doing that…there are ceilings…psychological, natural (life) and structural (market).
Crosspost: My first trading bot, now 4 months in development, started trading live last week and already gained 10%!
Backtest screenshot: https://solrac.prodibi.com/a/1jwk24gd54qyqxv/i/jdydmjj8wrrm725 Here's my original post: https://www.reddit.com/algotrading/comments/hd7e6c/my_first_algo_trading_bot_in_python_is_getting/?utm_source=share&utm_medium=ios_app&utm_name=iossmf Since then we've grown to a team of five people. We started trading live last week with a $100 test account on Binance Futures and gained 10% in our first week! Some amazing updates in the works: we are building this bot to connect to multiple exchanges via websocket in order to execute commands as fast as possible, and control them all through one web interface. This is a high velocity leveraged trading bot that uses 50x leverage and risks 5% of the wallet per trade. Soon we will implement dynamic leverage and position sizes based on key risk factors, like trading during range highs and lows. Beyond that, we also want to add different crypto markets, and maybe even forex eventually. Our very next target is Digitex Futures, the first totally commission free zero fee crypto exchange! We think this will be a game changer as fees make a huge impact on profitability. The current backtest, which is returning 900x over a 1 year 7 month period (with 100% of profits compounded) is viewable at cryptoravager dot com. I still need help to add Sharpe, equity, & drawdown indicators to the chart. Anyone have experience with the tradingview library? Please give me any feedback or advice! I'm one of those developers turned algo traders. I have 20 years experience in web application development, and only 1 year in trading and markets. Back in January I paid a pro trader good money to learn the strategy my bot is now using, which I used successfully by hand in March / April. That personal history plus the stellar backtest is what spurred us on to reach this point today.
No, the British did not steal $45 trillion from India
This is an updated copy of the version on BadHistory. I plan to update it in accordance with the feedback I got. I'd like to thank two people who will remain anonymous for helping me greatly with this post (you know who you are) Three years ago a festschrift for Binay Bhushan Chaudhuri was published by Shubhra Chakrabarti, a history teacher at the University of Delhi and Utsa Patnaik, a Marxist economist who taught at JNU until 2010. One of the essays in the festschirt by Utsa Patnaik was an attempt to quantify the "drain" undergone by India during British Rule. Her conclusion? Britain robbed India of $45 trillion (or £9.2 trillion) during their 200 or so years of rule. This figure was immensely popular, and got republished in several major news outlets (here, here, here, here (they get the number wrong) and more recently here), got a mention from the Minister of External Affairs & returns 29,100 results on Google. There's also plenty of references to it here on Reddit. Patnaik is not the first to calculate such a figure. Angus Maddison thought it was £100 million, Simon Digby said £1 billion, Javier Estaban said £40 million see Roy (2019). The huge range of figures should set off some alarm bells. So how did Patnaik calculate this (shockingly large) figure? Well, even though I don't have access to the festschrift, she conveniently has written an article detailing her methodology here. Let's have a look.
How exactly did the British manage to diddle us and drain our wealth’ ? was the question that Basudev Chatterjee (later editor of a volume in the Towards Freedom project) had posed to me 50 years ago when we were fellow-students abroad.
This is begging the question.
After decades of research I find that using India’s commodity export surplus as the measure and applying an interest rate of 5%, the total drain from 1765 to 1938, compounded up to 2016, comes to £9.2 trillion; since $4.86 exchanged for £1 those days, this sum equals about $45 trillion.
This is completely meaningless. To understand why it's meaningless consider India's annual coconut exports. These are almost certainly a surplus but the surplus in trade is countered by the other country buying the product (indeed, by definition, trade surpluses contribute to the GDP of a nation which hardly plays into intuitive conceptualisations of drain). Furthermore, Dewey (2019) critiques the 5% interest rate.
She [Patnaik] consistently adopts statistical assumptions (such as compound interest at a rate of 5% per annum over centuries) that exaggerate the magnitude of the drain
The exact mechanism of drain, or transfers from India to Britain was quite simple.
Drain theory possessed the political merit of being easily grasped by a nation of peasants. [...] No other idea could arouse people than the thought that they were being taxed so that others in far off lands might live in comfort. [...] It was, therefore, inevitable that the drain theory became the main staple of nationalist political agitation during the Gandhian era.
The key factor was Britain’s control over our taxation revenues combined with control over India’s financial gold and forex earnings from its booming commodity export surplus with the world. Simply put, Britain used locally raised rupee tax revenues to pay for its net import of goods, a highly abnormal use of budgetary funds not seen in any sovereign country.
The issue with figures like these is they all make certain methodological assumptions that are impossible to prove. From Roy in Frankema et al. (2019):
the "drain theory" of Indian poverty cannot be tested with evidence, for several reasons. First, it rests on the counterfactual that any money saved on account of factor payments abroad would translate into domestic investment, which can never be proved. Second, it rests on "the primitive notion that all payments to foreigners are "drain"", that is, on the assumption that these payments did not contribute to domestic national income to the equivalent extent (Kumar 1985, 384; see also Chaudhuri 1968). Again, this cannot be tested. [...] Fourth, while British officers serving India did receive salaries that were many times that of the average income in India, a paper using cross-country data shows that colonies with better paid officers were governed better (Jones 2013).
Indeed, drain theory rests on some very weak foundations. This, in of itself, should be enough to dismiss any of the other figures that get thrown out. Nonetheless, I felt it would be a useful exercise to continue exploring Patnaik's take on drain theory.
The East India Company from 1765 onwards allocated every year up to one-third of Indian budgetary revenues net of collection costs, to buy a large volume of goods for direct import into Britain, far in excess of that country’s own needs.
So what's going on here? Well Roy (2019) explains it better:
Colonial India ran an export surplus, which, together with foreign investment, was used to pay for services purchased from Britain. These payments included interest on public debt, salaries, and pensions paid to government offcers who had come from Britain, salaries of managers and engineers, guaranteed profts paid to railway companies, and repatriated business profts. How do we know that any of these payments involved paying too much? The answer is we do not.
So what was really happening is the government was paying its workers for services (as well as guaranteeing profits - to promote investment - something the GoI does today Dalal (2019), and promoting business in India), and those workers were remitting some of that money to Britain. This is hardly a drain (unless, of course, Indian diaspora around the world today are "draining" it). In some cases, the remittances would take the form of goods (as described) see Chaudhuri (1983):
It is obvious that these debit items were financed through the export surplus on merchandise account, and later, when railway construction started on a large scale in India, through capital import. Until 1833 the East India Company followed a cumbersome method in remitting the annual home charges. This was to purchase export commodities in India out of revenue, which were then shipped to London and the proceeds from their sale handed over to the home treasury.
While Roy's earlier point argues better paid officers governed better, it is honestly impossible to say what part of the repatriated export surplus was a drain, and what was not. However calling all of it a drain is definitely misguided. It's worth noting that Patnaik seems to make no attempt to quantify the benefits of the Raj either, Dewey (2019)'s 2nd criticism:
she [Patnaik] consistently ignores research that would tend to cut the economic impact of the drain down to size, such as the work on the sources of investment during the industrial revolution (which shows that industrialisation was financed by the ploughed-back profits of industrialists) or the costs of empire school (which stresses the high price of imperial defence)
Since tropical goods were highly prized in other cold temperate countries which could never produce them, in effect these free goods represented international purchasing power for Britain which kept a part for its own use and re-exported the balance to other countries in Europe and North America against import of food grains, iron and other goods in which it was deficient.
Re-exports necessarily adds value to goods when the goods are processed and when the goods are transported. The country with the largest navy at the time would presumably be in very good stead to do the latter.
The British historians Phyllis Deane and WA Cole presented an incorrect estimate of Britain’s 18th-19th century trade volume, by leaving out re-exports completely. I found that by 1800 Britain’s total trade was 62% higher than their estimate, on applying the correct definition of trade including re-exports, that is used by the United Nations and by all other international organisations.
While interesting, and certainly expected for such an old book, re-exporting necessarily adds value to goods.
When the Crown took over from the Company, from 1861 a clever system was developed under which all of India’s financial gold and forex earnings from its fast-rising commodity export surplus with the world, was intercepted and appropriated by Britain. As before up to a third of India’s rising budgetary revenues was not spent domestically but was set aside as ‘expenditure abroad’.
So, what does this mean? Britain appropriated all of India's earnings, and then spent a third of it aboard? Not exactly. She is describing home charges see Roy (2019) again:
Some of the expenditures on defense and administration were made in sterling and went out of the country. This payment by the government was known as the Home Charges. For example, interest payment on loans raised to finance construction of railways and irrigation works, pensions paid to retired officers, and purchase of stores, were payments in sterling. [...] almost all money that the government paid abroad corresponded to the purchase of a service from abroad. [...] The balance of payments system that emerged after 1800 was based on standard business principles.India bought something and paid for it.State revenues were used to pay for wages of people hired abroad, pay for interest on loans raised abroad, and repatriation of profits on foreign investments coming into India. These were legitimate market transactions.
Indeed, if paying for what you buy is drain, then several billions of us are drained every day.
The Secretary of State for India in Council, based in London, invited foreign importers to deposit with him the payment (in gold, sterling and their own currencies) for their net imports from India, and these gold and forex payments disappeared into the yawning maw of the SoS’s account in the Bank of England.
It should be noted that India having two heads was beneficial, and encouraged investment per Roy (2019):
The fact that the India Office in London managed a part of the monetary system made India creditworthy, stabilized its currency, and encouraged foreign savers to put money into railways and private enterprise in India. Current research on the history of public debt shows that stable and large colonies found it easier to borrow abroad than independent economies because the investors trusted the guarantee of the colonist powers.
Against India’s net foreign earnings he issued bills, termed Council bills (CBs), to an equivalent rupee value. The rate (between gold-linked sterling and silver rupee) at which the bills were issued, was carefully adjusted to the last farthing, so that foreigners would never find it more profitable to ship financial gold as payment directly to Indians, compared to using the CB route. Foreign importers then sent the CBs by post or by telegraph to the export houses in India, that via the exchange banks were paid out of the budgeted provision of sums under ‘expenditure abroad’, and the exporters in turn paid the producers (peasants and artisans) from whom they sourced the goods.
Sunderland (2013) argues CBs had two main roles (and neither were part of a grand plot to keep gold out of India):
Council bills had two roles. They firstly promoted trade by handing the IO some control of the rate of exchange and allowing the exchange banks to remit funds to India and to hedge currency transaction risks. They also enabled the Indian government to transfer cash to England for the payment of its UK commitments.
The United Nations (1962) historical data for 1900 to 1960, show that for three decades up to 1928 (and very likely earlier too) India posted the second highest merchandise export surplus in the world, with USA in the first position. Not only were Indians deprived of every bit of the enormous international purchasing power they had earned over 175 years, even its rupee equivalent was not issued to them since not even the colonial government was credited with any part of India’s net gold and forex earnings against which it could issue rupees. The sleight-of-hand employed, namely ‘paying’ producers out of their own taxes, made India’s export surplus unrequited and constituted a tax-financed drain to the metropolis, as had been correctly pointed out by those highly insightful classical writers, Dadabhai Naoroji and RCDutt.
It doesn't appear that others appreciate their insight Roy (2019):
K. N. Chaudhuri rightly calls such practice ‘confused’ economics ‘coloured by political feelings’.
Surplus budgets to effect such heavy tax-financed transfers had a severe employment–reducing and income-deflating effect: mass consumption was squeezed in order to release export goods. Per capita annual foodgrains absorption in British India declined from 210 kg. during the period 1904-09, to 157 kg. during 1937-41, and to only 137 kg by 1946.
If even a part of its enormous foreign earnings had been credited to it and not entirely siphoned off, India could have imported modern technology to build up an industrial structure as Japan was doing.
This is, unfortunately, impossible to prove. Had the British not arrived in India, there is no clear indication that India would've united (this is arguably more plausible than the given counterfactual1). Had the British not arrived in India, there is no clear indication India would not have been nuked in WW2, much like Japan. Had the British not arrived in India, there is no clear indication India would not have been invaded by lizard people, much like Japan. The list continues eternally. Nevertheless, I will charitably examine the given counterfactual anyway. Did pre-colonial India have industrial potential? The answer is a resounding no. From Gupta (1980):
This article starts from the premise that while economic categories - the extent of commodity production, wage labour, monetarisation of the economy, etc - should be the basis for any analysis of the production relations of pre-British India, it is the nature of class struggles arising out of particular class alignments that finally gives the decisive twist to social change. Arguing on this premise, and analysing the available evidence, this article concludes that there was little potential for industrial revolution before the British arrived in India because, whatever might have been the character of economic categories of that period,the class relations had not sufficiently matured to develop productive forces and the required class struggle for a 'revolution' to take place.
Yet all of this did not amount to an economic situation comparable to that of western Europe on the eve of the industrial revolution. Her technology - in agriculture as well as manufacturers - had by and large been stagnant for centuries. [...] The weakness of the Indian economy in the mid-eighteenth century, as compared to pre-industrial Europe was not simply a matter of technology and commercial and industrial organization. No scientific or geographical revolution formed part of the eighteenth-century Indian's historical experience. [...] Spontaneous movement towards industrialisation is unlikely in such a situation.
So now we've established India did not have industrial potential, was India similar to Japan just before the Meiji era? The answer, yet again, unsurprisingly, is no. Japan's economic situation was not comparable to India's, which allowed for Japan to finance its revolution. From Yasuba (1986):
All in all, the Japanese standard of living may not have been much below the English standard of living before industrialization, and both of them may have been considerably higher than the Indian standard of living. We can no longer say that Japan started from a pathetically low economic level and achieved a rapid or even "miraculous" economic growth. Japan's per capita income was almost as high as in Western Europe before industrialization, and it was possible for Japan to produce surplus in the Meiji Period to finance private and public capital formation.
The circumstances that led to Meiji Japan were extremely unique. See Tomlinson (1985):
Most modern comparisons between India and Japan, written by either Indianists or Japanese specialists, stress instead that industrial growth in Meiji Japan was the product of unique features that were not reproducible elsewhere. [...] it is undoubtably true that Japan's progress to industrialization has been unique and unrepeatable
So there you have it. Unsubstantiated statistical assumptions, calling any number you can a drain & assuming a counterfactual for no good reason gets you this $45 trillion number. Hopefully that's enough to bury it in the ground. 1. Several authors have affirmed that Indian identity is a colonial artefact. For example seeRajan 1969:
Perhaps the single greatest and most enduring impact of British rule over India is that it created an Indian nation, in the modern political sense. After centuries of rule by different dynasties overparts of the Indian sub-continent, and after about 100 years of British rule, Indians ceased to be merely Bengalis, Maharashtrians,or Tamils, linguistically and culturally.
But then, it would be anachronistic to condemn eighteenth-century Indians, who served the British, as collaborators, when the notion of 'democratic' nationalism or of an Indian 'nation' did not then exist.[...]Indians who fought for them, differed from the Europeans in having a primary attachment to a non-belligerent religion, family and local chief, which was stronger than any identity they might have with a more remote prince or 'nation'.
Chakrabarti, Shubra & Patnaik, Utsa (2018). Agrarian and other histories: Essays for Binay Bhushan Chaudhuri. Colombia University Press Hickel, Jason (2018). How the British stole $45 trillion from India. The Guardian Bhuyan, Aroonim & Sharma, Krishan (2019). The Great Loot: How the British stole $45 trillion from India. Indiapost Monbiot, George (2020). English Landowners have stolen our rights. It is time to reclaim them. The Guardian Tsjeng, Zing (2020). How Britain Stole $45 trillion from India with trains | Empires of Dirt. Vice Chaudhury, Dipanjan (2019). British looted $45 trillion from India in today’s value: Jaishankar. The Economic Times Roy, Tirthankar (2019). How British rule changed India's economy: The Paradox of the Raj. Palgrave Macmillan Patnaik, Utsa (2018). How the British impoverished India. Hindustan Times Tuovila, Alicia (2019). Expenditure method. Investopedia Dewey, Clive (2019). Changing the guard: The dissolution of the nationalist–Marxist orthodoxy in the agrarian and agricultural history of India. The Indian Economic & Social History Review Chandra, Bipan et al. (1989). India's Struggle for Independence, 1857-1947. Penguin Books Frankema, Ewout & Booth, Anne (2019). Fiscal Capacity and the Colonial State in Asia and Africa, c. 1850-1960. Cambridge University Press Dalal, Sucheta (2019). IL&FS Controversy: Centre is Paying Up on Sovereign Guarantees to ADB, KfW for Group's Loan. TheWire Chaudhuri, K.N. (1983). X - Foreign Trade and Balance of Payments (1757–1947). Cambridge University Press Sunderland, David (2013). Financing the Raj: The City of London and Colonial India, 1858-1940. Boydell Press Dewey, Clive (1978). Patwari and Chaukidar: Subordinate officials and the reliability of India’s agricultural statistics. Athlone Press Smith, Lisa (2015). The great Indian calorie debate: Explaining rising undernourishment during India’s rapid economic growth. Food Policy Duh, Josephine & Spears, Dean (2016). Health and Hunger: Disease, Energy Needs, and the Indian Calorie Consumption Puzzle. The Economic Journal Vankatesh, P. et al. (2016). Relationship between Food Production and Consumption Diversity in India – Empirical Evidences from Cross Section Analysis. Agricultural Economics Research Review Gupta, Shaibal (1980). Potential of Industrial Revolution in Pre-British India. Economic and Political Weekly Raychaudhuri, Tapan (1983). I - The mid-eighteenth-century background. Cambridge University Press Yasuba, Yasukichi (1986). Standard of Living in Japan Before Industrialization: From what Level did Japan Begin? A Comment. The Journal of Economic History Tomblinson, B.R. (1985). Writing History Sideways: Lessons for Indian Economic Historians from Meiji Japan. Cambridge University Press Rajan, M.S. (1969). The Impact of British Rule in India. Journal of Contemporary History Bryant, G.J. (2000). Indigenous Mercenaries in the Service of European Imperialists: The Case of the Sepoys in the Early British Indian Army, 1750-1800. War in History
Factset: How You can Invest in Hedge Funds’ Biggest Investment Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now: Their latest 8k filing reported the following: Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions. Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic. Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019. Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results. The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020. FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders. As you can see, there’s not much of a negative sign in sight here. It makes sense considering how FactSet’s FCF has never slowed down FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with. Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis: https://www.investopedia.com/terms/f/factset.asp FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015: So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33% EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded. P/E has declined in the past 2 years, making it a great time to buy. Increasing ROE despite lowering of leverage post 2016 Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself. SGA expense/Gross profit has been declining despite expansion of offices I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful. Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
The majority of this sub is focused on technical analysis. I regularly ridicule such "tea leaf readers" and advocate for trading based on fundamentals and economic news instead, so I figured I should take the time to write up something on how exactly you can trade economic news releases. This post is long as balls so I won't be upset if you get bored and go back to your drooping dick patterns or whatever.
How economic news is released
First, it helps to know how economic news is compiled and released. Let's take Initial Jobless Claims, the number of initial claims for unemployment benefits around the United States from Sunday through Saturday. Initial in this context means the first claim for benefits made by an individual during a particular stretch of unemployment. The Initial Jobless Claims figure appears in the Department of Labor's Unemployment Insurance Weekly Claims Report, which compiles information from all of the per-state departments that report to the DOL during the week. A typical number is between 100k and 250k and it can vary quite significantly week-to-week. The Unemployment Insurance Weekly Claims Report contains data that lags 5 days behind. For example, the Report issued on Thursday March 26th 2020 contained data about the week ending on Saturday March 21st 2020. In the days leading up to the Report, financial companies will survey economists and run complicated mathematical models to forecast the upcoming Initial Jobless Claims figure. The results of surveyed experts is called the "consensus"; specific companies, experts, and websites will also provide their own forecasts. Different companies will release different consensuses. Usually they are pretty close (within 2-3k), but for last week's record-high Initial Jobless Claims the reported consensuses varied by up to 1M! In other words, there was essentially no consensus. The Unemployment Insurance Weekly Claims Report is released each Thursday morning at exactly 8:30 AM ET. (On Thanksgiving the Report is released on Wednesday instead.) Media representatives gather at the Frances Perkins Building in Washington DC and are admitted to the "lockup" at 8:00 AM ET. In order to be admitted to the lockup you have to be a credentialed member of a media organization that has signed the DOL lockup agreement. The lockup room is small so there is a limited number of spots. No phones are allowed. Reporters bring their laptops and connect to a local network; there is a master switch on the wall that prevents/enables Internet connectivity on this network. Once the doors are closed the Unemployment Insurance Weekly Claims Report is distributed, with a heading that announces it is "embargoed" (not to be released) prior to 8:30 AM. Reporters type up their analyses of the report, including extracting key figures like Initial Jobless Claims. They load their write-ups into their companies' software, which prepares to send it out as soon as Internet is enabled. At 8:30 AM the DOL representative in the room flips the wall switch and all of the laptops are connected to the Internet, releasing their write-ups to their companies and on to their companies' partners. Many of those media companies have externally accessible APIs for distributing news. Media aggregators and squawk services (like RanSquawk and TradeTheNews) subscribe to all of these different APIs and then redistribute the key economic figures from the Report to their own subscribers within one second after Internet is enabled in the DOL lockup. Some squawk services are text-based while others are audio-based. FinancialJuice.com provides a free audio squawk service; internally they have a paid subscription to a professional squawk service and they simply read out the latest headlines to their own listeners, subsidized by ads on the site. I've been using it for 4 months now and have been pretty happy. It usually lags behind the official release times by 1-2 seconds and occasionally they verbally flub the numbers or stutter and have to repeat, but you can't beat the price! Important - I’m not affiliated with FinancialJuice and I’m not advocating that you use them over any other squawk. If you use them and they misspeak a number and you lose all your money don’t blame me. If anybody has any other free alternatives please share them!
How the news affects forex markets
Institutional forex traders subscribe to these squawk services and use custom software to consume the emerging data programmatically and then automatically initiate trades based on the perceived change to the fundamentals that the figures represent. It's important to note that every institution will have "priced in" their own forecasted figures well in advance of an actual news release. Forecasts and consensuses all come out at different times in the days leading up to a news release, so by the time the news drops everybody is really only looking for an unexpected result. You can't really know what any given institution expects the value to be, but unless someone has inside information you can pretty much assume that the market has collectively priced in the experts' consensus. When the news comes out, institutions will trade based on the difference between the actual and their forecast. Sometimes the news reflects a real change to the fundamentals with an economic effect that will change the demand for a currency, like an interest rate decision. However, in the case of the Initial Jobless Claims figure, which is a backwards-looking metric, trading is really just self-fulfilling speculation that market participants will buy dollars when unemployment is low and sell dollars when unemployment is high. Generally speaking, news that reflects a real economic shift has a bigger effect than news that only matters to speculators. Massive and extremely fast news-based trades happen within tenths of a second on the ECNs on which institutional traders are participants. Over the next few seconds the resulting price changes trickle down to retail traders. Some economic news, like Non Farm Payroll Employment, has an effect that can last minutes to hours as "slow money" follows behind on the trend created by the "fast money". Other news, like Initial Jobless Claims, has a short impact that trails off within a couple minutes and is subsequently dwarfed by the usual pseudorandom movements in the market. The bigger the difference between actual and consensus, the bigger the effect on any given currency pair. Since economic news releases generally relate to a single currency, the biggest and most easily predicted effects are seen on pairs where one currency is directly effected and the other is not affected at all. Personally I trade USD/JPY because the time difference between the US and Japan ensures that no news will be coming out of Japan at the same time that economic news is being released in the US. Before deciding to trade any particular news release you should measure the historical correlation between the release (specifically, the difference between actual and consensus) and the resulting short-term change in the currency pair. Historical data for various news releases (along with historical consensus data) is readily available. You can pay to get it exported into Excel or whatever, or you can scroll through it for free on websites like TradingEconomics.com. Let's look at two examples: Initial Jobless Claims and Non Farm Payroll Employment (NFP). I collected historical consensuses and actuals for these releases from January 2018 through the present, measured the "surprise" difference for each, and then correlated that to short-term changes in USD/JPY at the time of release using 5 second candles. I omitted any releases that occurred simultaneously as another major release. For example, occasionally the monthly Initial Jobless Claims comes out at the exact same time as the monthly Balance of Trade figure, which is a more significant economic indicator and can be expected to dwarf the effect of the Unemployment Insurance Weekly Claims Report. USD/JPY correlation with Initial Jobless Claims (2018 - present) USD/JPY correlation with Non Farm Payrolls (2018 - present) The horizontal axes on these charts is the duration (in seconds) after the news release over which correlation was calculated. The vertical axis is the Pearson correlation coefficient: +1 means that the change in USD/JPY over that duration was perfectly linearly correlated to the "surprise" in the releases; -1 means that the change in USD/JPY was perfectly linearly correlated but in the opposite direction, and 0 means that there is no correlation at all. For Initial Jobless Claims you can see that for the first 30 seconds USD/JPY is strongly negatively correlated with the difference between consensus and actual jobless claims. That is, fewer-than-forecast jobless claims (fewer newly unemployed people than expected) strengthens the dollar and greater-than-forecast jobless claims (more newly unemployed people than expected) weakens the dollar. Correlation then trails off and changes to a moderate/weak positive correlation. I interpret this as algorithms "buying the dip" and vice versa, but I don't know for sure. From this chart it appears that you could profit by opening a trade for 15 seconds (duration with strongest correlation) that is long USD/JPY when Initial Jobless Claims is lower than the consensus and short USD/JPY when Initial Jobless Claims is higher than expected. The chart for Non Farm Payroll looks very different. Correlation is positive (higher-than-expected payrolls strengthen the dollar and lower-than-expected payrolls weaken the dollar) and peaks at around 45 seconds, then slowly decreases as time goes on. This implies that price changes due to NFP are quite significant relative to background noise and "stick" even as normal fluctuations pick back up. I wanted to show an example of what the USD/JPY S5 chart looks like when an "uncontested" (no other major simultaneously news release) Initial Jobless Claims and NFP drops, but unfortunately my broker's charts only go back a week. (I can pull historical data going back years through the API but to make it into a pretty chart would be a bit of work.) If anybody can get a 5-second chart of USD/JPY at March 19, 2020, UTC 12:30 and/or at February 7, 2020, UTC 13:30 let me know and I'll add it here.
So without too much effort we determined that (1) USD/JPY is strongly negatively correlated with the Initial Jobless Claims figure for the first 15 seconds after the release of the Unemployment Insurance Weekly Claims Report (when no other major news is being released) and also that (2) USD/JPY is strongly positively correlated with the Non Farms Payroll figure for the first 45 seconds after the release of the Employment Situation report. Before you can assume you can profit off the news you have to backtest and consider three important parameters. Entry speed: How quickly can you realistically enter the trade? The correlation performed above was measured from the exact moment the news was released, but realistically if you've got your finger on the trigger and your ear to the squawk it will take a few seconds to hit "Buy" or "Sell" and confirm. If 90% of the price move happens in the first second you're SOL. For back-testing purposes I assume a 5 second delay. In practice I use custom software that opens a trade with one click, and I can reliably enter a trade within 2-3 seconds after the news drops, using the FinancialJuice free squawk. Minimum surprise: Should you trade every release or can you do better by only trading those with a big enough "surprise" factor? Backtesting will tell you whether being more selective is better long-term or not. Hold time: The optimal time to hold the trade is not necessarily the same as the time of maximum correlation. That's a good starting point but it's not necessarily the best number. Backtesting each possible hold time will let you find the best one. The spread: When you're only holding a position open for 30 seconds, the spread will kill you. The correlations performed above used the midpoint price, but in reality you have to buy at the ask and sell at the bid. Brokers aren't stupid and the moment volume on the ECN jumps they will widen the spread for their retail customers. The only way to determine if the news-driven price movements reliably overcome the spread is to backtest. Stops: Personally I don't use stops, neither take-profit nor stop-loss, since I'm automatically closing the trade after a fixed (and very short) amount of time. Additionally, brokers have a minimum stop distance; the profits from scalping the news are so slim that even the nearest stops they allow will generally not get triggered. I backtested trading these two news releases (since 2018), using a 5 second entry delay, real historical spreads, and no stops, cycling through different "surprise" thresholds and hold times to find the combination that returns the highest net profit. It's important to maximize net profit, not expected value per trade, so you don't over-optimize and reduce the total number of trades taken to one single profitable trade. If you want to get fancy you can set up a custom metric that combines number of trades, expected value, and drawdown into a single score to be maximized. For the Initial Jobless Claims figure I found that the best combination is to hold trades open for 25 seconds (that is, open at 5 seconds elapsed and hold until 30 seconds elapsed) and only trade when the difference between consensus and actual is 7k or higher. That leads to 30 trades taken since 2018 and an expected return of... drumroll please... -0.0093 yen per unit per trade. Yep, that's a loss of approx. $8.63 per lot. Disappointing right? That's the spread and that's why you have to backtest. Even though the release of the Unemployment Insurance Weekly Claims Report has a strong correlation with movement in USD/JPY, it's simply not something that a retail trader can profit from. Let's turn to the NFP. There I found that the best combination is to hold trades open for 75 seconds (that is, open at 5 seconds elapsed and hold until 80 seconds elapsed) and trade every single NFP (no minimum "surprise" threshold). That leads to 20 trades taken since 2018 and an expected return of... drumroll please... +0.1306 yen per unit per trade. That's a profit of approx. $121.25 per lot. Not bad for 75 seconds of work! That's a +6% ROI at 50x leverage.
Make it real
If you want to do this for realsies, you need to run these numbers for all of the major economic news releases. Markit Manufacturing PMI, Factory Orders MoM, Trade Balance, PPI MoM, Export and Import Prices, Michigan Consumer Sentiment, Retail Sales MoM, Industrial Production MoM, you get the idea. You keep a list of all of the releases you want to trade, when they are released, and the ideal hold time and "surprise" threshold. A few minutes before the prescribed release time you open up your broker's software, turn on your squawk, maybe jot a few notes about consensuses and model forecasts, and get your finger on the button. At the moment you hear the release you open the trade in the correct direction, hold it (without looking at the chart!) for the required amount of time, then close it and go on with your day. Some benefits of trading this way: * Most major economic releases come out at either 8:30 AM ET or 10:00 AM ET, and then you're done for the day. * It's easily backtestable. You can look back at the numbers and see exactly what to expect your return to be. * It's fun! Packing your trading into 30 seconds and knowing that institutions are moving billions of dollars around as fast as they can based on the exact same news you just read is thrilling. * You can wow your friends by saying things like "The St. Louis Fed had some interesting remarks on consumer spending in the latest Beige Book." * No crayons involved. Some downsides: * It's tricky to be fast enough without writing custom software. Some broker software is very slow and requires multiple dialog boxes before a position is opened, which won't cut it. * The profits are very slim, you're not going to impress your instagram followers to join your expensive trade copying service with your 30-second twice-weekly trades. * Any friends you might wow with your boring-ass economic talking points are themselves the most boring people in the world. I hope you enjoyed this long as fuck post and you give trading economic news a try!
I think leverage is probably the most important factor in all trading. It controls all about your career in trading. Let's think about it. When we're over leverage, there's a little part inside of us that we feel, and we know we 're doing something wrong. Like a natural survival instinct that we have made a mistake or are in danger. That feeling is 100 percent going on for a reason. It's a valid feeling. It's the first subconscious signal that something's wrong. Something is wrong, and we're in danger of it. We risked too much equity, and it could be a very bad day. Trading is a game based on percent. Yes, you might have a percentage-based chance, hit a huge deal, and make an incredible percent return. The impact \" Leverage \" has on a Trader’s Psychology But how long can the trading system last until it does more harm than good? That one "perfect" trade isn't always perfect. Personally, I can say that I did the exact thing and saw that my account had been wiped out. That moment of post account depletion is terrible, yet completely avoidable. The first step is that feeling, the second is a psychological attack. We all know that feeling of not being able to leave the screen in fear of what might happen. At that point, we were totally lost. Money is controlling us now, rather than controlling us. It's not trading, it's high-quality gambling. That's why it's so important to leverage it properly. We 're not players, we 're strategic risk-takers in a percentage-based game. The next moments are when we really see the power of leverage. Psychology is starting to make us question ourselves. We are vulnerable to ourselves now in the heat of the moment. In moments like these, when we're going to be our worst enemies. This order flow of decay began with an undisciplined desire to be greedy. Based your trade on hope rather than statistics. Your psyche and your influence are married to each other. We have lost all control of a situation in which we have complete control. This is all so avoidable by simply risking the 2% standard. We see it in every book, every picture, every effective trader ... The same thing they all claim. 'The risk management.' Like all traders, they did the same thing, every trader has blown an account, and that's all right! It's a step toward becoming a profitable trader. This is the moment when we truly learn the power of psychology and what it can do to us. The question now is, what happens next. Do we have to learn our lesson? Or go back to the mass statistics that are the cause of a trader's failure. It's absolutely okay, if you don't have to lose big on trade. That's the wake-up call, and every trader must go through it to understand how much power we have as traders. YOU control the money, do not let the money control you. This is coming from someone who has probably blown 10 accounts… I hope this is helpful, happy trading! This comes from someone who has probably blown 10 or more accounts ... So I hope this read has been helpful, The impact \" Leverage \" has on a Trader’s Psychology (meme) Cheers and Profitable Trading to All. Eva " Forex " Canares . About FTMO - They fund forex traders. Just Pass their risk management rules and begin trading for their company. They'll provide you capital up to $300k USD for trading the financial markets. 70% of profits you keep and losses are covered by them. How does it work? How to Become a Funded Forex,Stocks,or CryptoCurrency Trader?
Thoughts On The Market Series #1 - The New Normal?
Market Outlook: What to Make of This “New Normal”
By ****\* March 16, 2020 After an incredibly volatile week – which finished with the Dow Jones Industrial Average rallying over 9% on Friday – I suppose my readers might expect me to be quite upbeat about the markets. Unfortunately, I persist in my overall pessimistic outlook for stocks, and for the economy in general. Friday’s rally essentially negated Thursday’s sell-off, but I don’t expect it to be the start of a sustained turnaround. We’re getting a taste of that this morning, with the Dow opening down around 7%. This selloff is coming on the back of an emergency interest rate cut by the Federal Reserve of 100 basis points (to 0%-0.25%) on Sunday… along with the announcement of a new quantitative easing program of $700 billion. (I will write about this further over the next several days.) As I have been writing for many weeks, the financial bubble – which the Fed created by pumping trillions of dollars into the financial system – has popped. It will take some time for the bubble to deflate to sustainable levels. Today I’ll walk you through what’s going on in the markets and the economy… what I expect going forward and why… and what it means for us as traders. (You’ll see it’s not all bad news.)
Coronavirus’ Strain on the Global Economy
To start, let’s put things in perspective: This asset deflation was coming one way or another. Covid19 (or coronavirus) has simply accelerated the process. Major retailers are closing, tourism is getting crushed, universities and schools are sending students home, conventions, sporting events, concerts, and other public gatherings have been cancelled, banks and other financial service firms are going largely virtual, and there has been a massive loss of wealth. Restaurant data suggests that consumer demand is dropping sharply, and the global travel bans will only worsen the situation. Commercial real estate is another sector that looks particularly vulnerable. We are almost certain to see a very sharp and pronounced economic slowdown here in the United States, and elsewhere. In fact, I expect a drop of at least 5% of GDP over the next two quarters, which is quite severe by any standard. Sure, when this cycle is complete, there will be tremendous amounts of pent-up demand by consumers, but for the time being, the consumer is largely on the sidelines. Of course, the problems aren’t just in the U.S. China’s numbers look awful. In fact, the government there may have to “massage” their numbers a bit to show a positive GDP in the first quarter. Europe’s numbers will also look dreadful, and South Korea’s economy has been hit badly. All around the world, borders are being shut, all non-essential businesses are being closed, and people in multiple countries are facing a lockdown of historic proportions. The coronavirus is certainly having a powerful impact, and it looks certain that its impact will persist for a while. Consider global tourism. It added almost $9 trillion to the global economy in 2018, and roughly 320 million jobs. This market is in serious trouble. Fracking in the U.S. is another business sector that is in a desperate situation. Millions of jobs and tens of billions of loans are now in jeopardy. The derivative businesses that this sector supports will be likewise devastated as companies are forced to reduce their workforces or shut down due to the collapse in oil prices. This sector’s suffering will probably force banks to book some big losses despite attempts by the government to support this industry. In a similar way, the derivative businesses that are supported by the universities and colleges across America are going to really suffer. There are nearly 20 million students in colleges across the U.S. When they go home for spring vacation and do not return, the effect on the local businesses that colleges and university populations support will be devastating. What does this “new normal” mean going forward? Let’s take a look…
The new normal may become increasingly unpleasant for us. We need to be ready to hunker down for quite some time. Beyond that, the government needs to handle this crisis far better in the future. The level of stupidity associated with the massive throngs of people trapped in major airports yesterday, for example, was almost unimaginable. Instead of facilitating the reduction of social contact and halting the further spread of the coronavirus, the management of the crowds at the airports produced a perfect breeding ground for the spread of the virus. My guess is that more draconian travel restrictions will be implemented soon, matching to some extent the measures taken across Europe. This will in turn have a further dampening effect on economic activity in the U.S., putting more and more pressure on the Fed and the government to artificially support a rapidly weakening economy. Where does this end up? It is too early to say, but a very safe bet is that we will have some months of sharply negative growth. Too many sectors of the economy are going to take a hit to expect anything else. The Fed has already driven interest rates to zero. Will that help? Unlikely. In fact, as I mentioned at the beginning of this update, the markets are voting with a resounding NO. The businesses that are most affected by the current economic situation will still suffer. Quantitative easing is hardly a cure-all. In fact, it has been one of the reasons that we have such a mess in our markets today. The markets have become addicted to the easy money, so more of the same will have little or no impact. We will need real economic demand, not an easier monetary policy. It won’t help support tourism, for example, or the other sectors getting smashed right now. The government will need to spend at least 5% of GDP, or roughly $1 trillion, to offset the weakness I see coming. Is it surprising that the Fed and the government take emergency steps to try to stabilize economic growth? Not at all. This is essentially what they have been doing for a long time, so it is completely consistent with their playbook. Next, I would anticipate the government implementing some massive public-works and infrastructure programs over the coming months. That would be very helpful, and almost certainly quite necessary. But there’s a problem with this kind of intervention from the government…
What Happens When You Eliminate the Business Cycle
The Fed’s foolish attempt to eliminate business cycles is a significant contributing factor to the volatility we are currently experiencing. Quantitative easing is nothing more than printing lots and lots of money to support a weak economy and give the appearance of growth and prosperity. In fact, it is a devaluation of the currency’s true buying power. That in turn artificially drives up the prices of other assets, such as stocks, real estate and gold – but it does not create true wealth. That only comes with non-inflationary growth of goods and services and associated increases in economic output. Inflation is the government’s way to keep people thinking they are doing better. To that point: We have seen some traditional safe-haven assets getting destroyed during this time of risk aversion. That has certainly compounded the problems of many investors. Gold is a great example. As the stock market got violently slammed, people were forced to come up with cash to support their losing positions. Gold became a short-term source of liquidity as people sold their gold holdings in somewhat dramatic fashion. It was one of the few holdings of many people that was not dramatically under water, so people sold it. The move may have seemed perverse, particularly to people who bought gold as a safe-haven asset, but in times of crisis, all assets tend to become highly correlated, at least short term. We saw a similar thing happen with long yen exposures and long Bitcoin exposures recently. The dollar had its strongest one-day rally against the yen since November 2016 as people were forced to sell huge amounts of yen to generate liquidity. Many speculators had made some nice profits recently as the dollar dropped sharply from 112 to 101.30, but they have been forced to book whatever profits they had in this position. Again, this was due to massive losses elsewhere in their portfolios. Is the yen’s sell-off complete? If it is not complete, it is probably at least close to an attractive level for Japanese investors to start buying yen against a basket of currencies. The major supplies of yen have largely been taken off the table for now. For example, the yen had been a popular funding currency for “carry” plays. People were selling yen and buying higher-yielding currencies to earn the interest rate difference between the liability currency (yen) and the funding currency (for example, the U.S. dollar). Carry plays are very unpopular in times of great uncertainty and volatility, however, so that supply of yen will be largely gone for quite some time. Plus, the yield advantage of currencies such as the U.S. dollar, Canadian dollar, and Australian dollar versus the yen is nearly gone. In addition, at the end of the Japanese fiscal year , there is usually heavy demand for yen as Japanese corporations need to bring home a portion of their overseas holdings for balance sheet window dressing. I don’t expect that pressure to be different this year. Just as the safe-haven assets of yen and gold got aggressively sold, Bitcoin also got hammered. It was driven by a similar theme – people had big losses and they needed to produce liquidity quickly. Selling Bitcoin became one of the sources of that liquidity.
Heavy Price Deflation Ahead
Overall, there is a chance that this scenario turns into something truly ugly, with sustained price deflation across many parts of the economy. We will certainly have price deflation in many sectors, at least on a temporary basis. Why does that matter over the long term? Price deflation is the most debilitating economic development in a society that is debt-laden – like the U.S. today. Prices of assets come down… and the debt becomes progressively bigger and bigger. The balance sheet of oil company Chesapeake Energy is a classic example. It’s carrying almost $10 billion worth of debt… versus a market cap of only about $600 million. Talk about leverage! When the company had a market cap of $10 billion, that debt level didn’t appear so terrifying. Although this is an extreme example for illustrative purposes, the massive debt loads of China would seem more and more frightening if we were to sink into flat or negative growth cycles for a while. The government’s resources are already being strained, and it can artificially support only so many failing companies. The U.S. has gigantic levels of debt as well, but it has the advantage of being the world’s true hegemon, and the U.S. dollar is the world’s reserve currency. This creates a tremendous amount of leverage and power in financing its debt. The U.S. has been able to impose its will on its trading partners to trade major commodities in dollars. This has created a constant demand for the dollar that offsets, to a large extent, the massive trade deficit that the U.S. runs. For example, if a German company wants to buy oil, then it needs to hold dollars. This creates a constant demand for dollar assets. In short, the dollar’s status as the true global reserve currency is far more important than most people realize. China does not hold this advantage.
What to Do Now
In terms of how to position ourselves going forward, I strongly recommend that people continue with a defensive attitude regarding stocks. There could be a lot more downside to come. Likewise, we could see some panic selling in other asset classes. The best thing right now is to be liquid and patient, ready to pounce on special opportunities when they present themselves. For sure, there will be some exceptional opportunities, but it is too early to commit ourselves to just one industry. These opportunities could come in diverse sectors such as commercial real estate, hospitality, travel and leisure, and others. As for the forex markets, the volatility in the currencies is extreme, so we are a bit cautious. I still like the yen as a safe-haven asset. I likewise still want to sell the Australian dollar, the New Zealand dollar, and the Canadian dollar as liability currencies. Why? The Bank of Canada, the Reserve Bank of Australia, and the Reserve Bank of New Zealand have all taken aggressive steps recently, slashing interest rates. These currencies are all weak, and they will get weaker. Finding an ideal entry for a trade, however, is tricky. Therefore, we are being extra careful with our trading. We always prioritize the preservation of capital over generating profits, and we will continue with this premise. At the same time, volatility in the markets is fantastic for traders. We expect many excellent opportunities to present themselves over the coming days and weeks as prices get driven to extreme levels and mispricings appear. So stay tuned.
https://preview.redd.it/gp18bjnlabr41.jpg?width=768&format=pjpg&auto=webp&s=6054e7f52e8d52da403016139ae43e0e799abf15 Download PDF of this article here:https://docdro.id/6eLgUPo In light of the recent fall in oil prices due to the Saudi-Russian dispute and dampening demand for oil due to the lockdowns implemented globally, O&G stocks have taken a severe beating, falling approximately 50% from their highs at the beginning of the year. Not spared from this onslaught is Hibiscus Petroleum Berhad (Hibiscus), a listed oil and gas (O&G) exploration and production (E&P) company. Why invest in O&G stocks in this particularly uncertain period? For one, valuations of these stocks have fallen to multi-year lows, bringing the potential ROI on these stocks to attractive levels. Oil prices are cyclical, and are bound to return to the mean given a sufficiently long time horizon. The trick is to find those companies who can survive through this downturn and emerge into “normal” profitability once oil prices rebound. In this article, I will explore the upsides and downsides of investing in Hibiscus. I will do my best to cater this report to newcomers to the O&G industry – rather than address exclusively experts and veterans of the O&G sector. As an equity analyst, I aim to provide a view on the company primarily, and will generally refrain from providing macro views on oil or opinions about secular trends of the sector. I hope you enjoy reading it! Stock code: 5199.KL Stock name: Hibiscus Petroleum Berhad Financial information and financial reports: https://www.malaysiastock.biz/Corporate-Infomation.aspx?securityCode=5199 Company website: https://www.hibiscuspetroleum.com/
Hibiscus Petroleum Berhad (5199.KL) is an oil and gas (O&G) upstream exploration and production (E&P) company located in Malaysia. As an E&P company, their business can be basically described as: · looking for oil, · drawing it out of the ground, and · selling it on global oil markets. This means Hibiscus’s profits are particularly exposed to fluctuating oil prices. With oil prices falling to sub-$30 from about $60 at the beginning of the year, Hibiscus’s stock price has also fallen by about 50% YTD – from around RM 1.00 to RM 0.45 (as of 5 April 2020). https://preview.redd.it/3dqc4jraabr41.png?width=641&format=png&auto=webp&s=7ba0e8614c4e9d781edfc670016a874b90560684 https://preview.redd.it/lvdkrf0cabr41.png?width=356&format=png&auto=webp&s=46f250a713887b06986932fa475dc59c7c28582e While the company is domiciled in Malaysia, its two main oil producing fields are located in both Malaysia and the UK. The Malaysian oil field is commonly referred to as the North Sabah field, while the UK oil field is commonly referred to as the Anasuria oil field. Hibiscus has licenses to other oil fields in different parts of the world, notably the Marigold/Sunflower oil fields in the UK and the VIC cluster in Australia, but its revenues and profits mainly stem from the former two oil producing fields. Given that it’s a small player and has only two primary producing oil fields, it’s not surprising that Hibiscus sells its oil to a concentrated pool of customers, with 2 of them representing 80% of its revenues (i.e. Petronas and BP). Fortunately, both these customers are oil supermajors, and are unlikely to default on their obligations despite low oil prices. At RM 0.45 per share, the market capitalization is RM 714.7m and it has a trailing PE ratio of about 5x. It doesn’t carry any debt, and it hasn’t paid a dividend in its listing history. The MD, Mr. Kenneth Gerard Pereira, owns about 10% of the company’s outstanding shares.
Reserves (Total recoverable oil) & Production (bbl/day)
To begin analyzing the company, it’s necessary to understand a little of the industry jargon. We’ll start with Reserves and Production. In general, there are three types of categories for a company’s recoverable oil volumes – Reserves, Contingent Resources and Prospective Resources. Reserves are those oil fields which are “commercial”, which is defined as below: As defined by the SPE PRMS,Reservesare “… quantities of petroleum anticipated to be commercially recoverable by application of development projects to known accumulations from a given date forward under defined conditions.” Therefore, Reserves must be discovered (by drilling, recoverable (with current technology), remaining in the subsurface (at the effective date of the evaluation) and “commercial” based on the development project proposed.) Note that Reserves are associated with development projects. To be considered as “commercial”, there must be a firm intention to proceed with the project in a reasonable time frame (typically 5 years, and such intention must be based upon all of the following criteria:) - A reasonable assessment of the future economics of the development project meeting defined investment and operating criteria;- A reasonable expectation that there will be a market for all or at least the expected sales quantities of production required to justify development;- Evidence that the necessary production and transportation facilities are available or can be made available; and- Evidence that legal, contractual, environmental and other social and economic concerns will allow for the actual implementation of the recovery project being evaluated. Contingent Resources and Prospective Resources are further defined as below: -Contingent Resources: potentially recoverable volumes associated with a development plan that targets discovered volumes but is not (yet commercial (as defined above); and)-Prospective Resources: potentially recoverable volumes associated with a development plan that targets as yet undiscovered volumes. In the industry lingo, we generally refer to Reserves as ‘P’ and Contingent Resources as ‘C’. These ‘P’ and ‘C’ resources can be further categorized into 1P/2P/3P resources and 1C/2C/3C resources, each referring to a low/medium/high estimate of the company’s potential recoverable oil volumes: - Low/1C/1P estimate: there should be reasonable certainty that volumes actually recovered will equal or exceed the estimate;- Best/2C/2P estimate: there should be an equal likelihood of the actual volumes of petroleum being larger or smaller than the estimate; and- High/3C/3P estimate: there is a low probability that the estimate will be exceeded. Hence in the E&P industry, it is easy to see why most investors and analysts refer to the 2P estimate as the best estimate for a company’s actual recoverable oil volumes. This is because 2P reserves (‘2P’ referring to ‘Proved and Probable’) are a middle estimate of the recoverable oil volumes legally recognized as “commercial”. However, there’s nothing stopping you from including 2C resources (riskier) or utilizing 1P resources (conservative) as your estimate for total recoverable oil volumes, depending on your risk appetite. In this instance, the company has provided a snapshot of its 2P and 2C resources in its analyst presentation: https://preview.redd.it/o8qejdyc8br41.png?width=710&format=png&auto=webp&s=b3ab9be8f83badf0206adc982feda3a558d43e78 Basically, what the company is saying here is that by 2021, it will have classified as 2P reserves at least 23.7 million bbl from its Anasuria field and 20.5 million bbl from its North Sabah field – for total 2P reserves of 44.2 million bbl (we are ignoring the Australian VIC cluster as it is only estimated to reach first oil by 2022). Furthermore, the company is stating that they have discovered (but not yet legally classified as “commercial”) a further 71 million bbl of oil from both the Anasuria and North Sabah fields, as well as the Marigold/Sunflower fields. If we include these 2C resources, the total potential recoverable oil volumes could exceed 100 million bbl. In this report, we shall explore all valuation scenarios giving consideration to both 2P and 2C resources. https://preview.redd.it/gk54qplf8br41.png?width=489&format=png&auto=webp&s=c905b7a6328432218b5b9dfd53cc9ef1390bd604 The company further targets a 2021 production rate of 20,000 bbl (LTM: 8,000 bbl), which includes 5,000 bbl from its Anasuria field (LTM: 2,500 bbl) and 7,000 bbl from its North Sabah field (LTM: 5,300 bbl). This is a substantial increase in forecasted production from both existing and prospective oil fields. If it materializes, annual production rate could be as high as 7,300 mmbbl, and 2021 revenues (given FY20 USD/bbl of $60) could exceed RM 1.5 billion (FY20: RM 988 million). However, this targeted forecast is quite a stretch from current production levels. Nevertheless, we shall consider all provided information in estimating a valuation for Hibiscus. To understand Hibiscus’s oil production capacity and forecast its revenues and profits, we need to have a better appreciation of the performance of its two main cash-generating assets – the North Sabah field and the Anasuria field. North Sabah oil field https://preview.redd.it/62nssexj8br41.png?width=1003&format=png&auto=webp&s=cd78f86d51165fb9a93015e49496f7f98dad64dd Hibiscus owns a 50% interest in the North Sabah field together with its partner Petronas, and has production rights over the field up to year 2040. The asset contains 4 oil fields, namely the St Joseph field, South Furious field, SF 30 field and Barton field. For the sake of brevity, we shall not delve deep into the operational aspects of the fields or the contractual nature of its production sharing contract (PSC). We’ll just focus on the factors which relate to its financial performance. These are: · Average uptime · Total oil sold · Average realized oil price · Average OPEX per bbl With regards to average uptime, we can see that the company maintains relative high facility availability, exceeding 90% uptime in all quarters of the LTM with exception of Jul-Sep 2019. The dip in average uptime was due to production enhancement projects and maintenance activities undertaken to improve the production capacity of the St Joseph and SF30 oil fields. Hence, we can conclude that management has a good handle on operational performance. It also implies that there is little room for further improvement in production resulting from increased uptime. As North Sabah is under a production sharing contract (PSC), there is a distinction between gross oil production and net oil production. The former relates to total oil drawn out of the ground, whereas the latter refers to Hibiscus’s share of oil production after taxes, royalties and expenses are accounted for. In this case, we want to pay attention to net oil production, not gross. We can arrive at Hibiscus’s total oil sold for the last twelve months (LTM) by adding up the total oil sold for each of the last 4 quarters. Summing up the figures yields total oil sold for the LTM of approximately 2,075,305 bbl. Then, we can arrive at an average realized oil price over the LTM by averaging the average realized oil price for the last 4 quarters, giving us an average realized oil price over the LTM of USD 68.57/bbl. We can do the same for average OPEX per bbl, giving us an average OPEX per bbl over the LTM of USD 13.23/bbl. Thus, we can sum up the above financial performance of the North Sabah field with the following figures: · Total oil sold: 2,075,305 bbl · Average realized oil price: USD 68.57/bbl · Average OPEX per bbl: USD 13.23/bbl Anasuria oil field https://preview.redd.it/586u4kfo8br41.png?width=1038&format=png&auto=webp&s=7580fc7f7df7e948754d025745a5cf47d4393c0f Doing the same exercise as above for the Anasuria field, we arrive at the following financial performance for the Anasuria field: · Total oil sold: 1,073,304 bbl · Average realized oil price: USD 63.57/bbl · Average OPEX per bbl: USD 23.22/bbl As gas production is relatively immaterial, and to be conservative, we shall only consider the crude oil production from the Anasuria field in forecasting revenues.
Valuation (Method 1)
Putting the figures from both oil fields together, we get the following data: https://preview.redd.it/7y6064dq8br41.png?width=700&format=png&auto=webp&s=2a4120563a011cf61fc6090e1cd5932602599dc2 Given that we have determined LTM EBITDA of RM 632m, the next step would be to subtract ITDA (interest, tax, depreciation & amortization) from it to obtain estimated LTM Net Profit. Using FY2020’s ITDA of approximately RM 318m as a guideline, we arrive at an estimated LTM Net Profit of RM 314m (FY20: 230m). Given the current market capitalization of RM 714.7m, this implies a trailing LTM PE of 2.3x. Performing a sensitivity analysis given different oil prices, we arrive at the following net profit table for the company under different oil price scenarios, assuming oil production rate and ITDA remain constant: https://preview.redd.it/xixge5sr8br41.png?width=433&format=png&auto=webp&s=288a00f6e5088d01936f0217ae7798d2cfcf11f2 From the above exercise, it becomes apparent that Hibiscus has a breakeven oil price of about USD 41.8863/bbl, and has a lot of operating leverage given the exponential rate of increase in its Net Profit with each consequent increase in oil prices. Considering that the oil production rate (EBITDA) is likely to increase faster than ITDA’s proportion to revenues (fixed costs), at an implied PE of 4.33x, it seems likely that an investment in Hibiscus will be profitable over the next 10 years (with the assumption that oil prices will revert to the mean in the long-term).
Valuation (Method 2)
Of course, there are a lot of assumptions behind the above method of valuation. Hence, it would be prudent to perform multiple methods of valuation and compare the figures to one another. As opposed to the profit/loss assessment in Valuation (Method 1), another way of performing a valuation would be to estimate its balance sheet value, i.e. total revenues from 2P Reserves, and assign a reasonable margin to it. https://preview.redd.it/o2eiss6u8br41.png?width=710&format=png&auto=webp&s=03960cce698d9cedb076f3d5f571b3c59d908fa8 From the above, we understand that Hibiscus’s 2P reserves from the North Sabah and Anasuria fields alone are approximately 44.2 mmbbl (we ignore contribution from Australia’s VIC cluster as it hasn’t been developed yet). Doing a similar sensitivity analysis of different oil prices as above, we arrive at the following estimated total revenues and accumulated net profit: https://preview.redd.it/h8hubrmw8br41.png?width=450&format=png&auto=webp&s=6d23f0f9c3dafda89e758b815072ba335467f33e Let’s assume that the above average of RM 9.68 billion in total realizable revenues from current 2P reserves holds true. If we assign a conservative Net Profit margin of 15% (FY20: 23%; past 5 years average: 16%), we arrive at estimated accumulated Net Profit from 2P Reserves ofRM 1.452 billion. Given the current market capitalization of RM 714 million, we might be able to say that the equity is worth about twice the current share price. However, it is understandable that some readers might feel that the figures used in the above estimate (e.g. net profit margin of 15%) were randomly plucked from the sky. So how do we reconcile them with figures from the financial statements? Fortunately, there appears to be a way to do just that. Intangible Assets I refer you to a figure in the financial statements which provides a shortcut to the valuation of 2P Reserves. This is the carrying value of Intangible Assets on the Balance Sheet. As of 2QFY21, that amount was RM 1,468,860,000 (i.e. RM 1.468 billion). https://preview.redd.it/hse8ttb09br41.png?width=881&format=png&auto=webp&s=82e48b5961c905fe9273cb6346368de60202ebec Quite coincidentally, one might observe that this figure is dangerously close to the estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion we calculated earlier. But why would this amount matter at all? To answer that, I refer you to the notes of the Annual Report FY20 (AR20). On page 148 of the AR20, we find the following two paragraphs: E&E assets comprise of rights and concession and conventional studies. Following the acquisition of a concession right to explore a licensed area, the costs incurred such as geological and geophysical surveys, drilling, commercial appraisal costs and other directly attributable costs of exploration and appraisal including technical and administrative costs, are capitalised as conventional studies, presented as intangible assets. E&E assets are assessed for impairment when facts and circumstances suggest that the carrying amount of an E&E asset may exceed its recoverable amount. The Group will allocate E&E assets to cash generating unit (“CGU”s or groups of CGUs for the purpose of assessing such assets for impairment. Each CGU or group of units to which an E&E asset is allocated will not be larger than an operating segment as disclosed in Note 39 to the financial statements.) Hence, we can determine that firstly, the intangible asset value represents capitalized costs of acquisition of the oil fields, including technical exploration costs and costs of acquiring the relevant licenses. Secondly, an impairment review will be carried out when “the carrying amount of an E&E asset may exceed its recoverable amount”, with E&E assets being allocated to “cash generating units” (CGU) for the purposes of assessment. On page 169 of the AR20, we find the following: Carrying amounts of the Group’s intangible assets, oil and gas assets and FPSO are reviewed for possible impairment annually including any indicators of impairment. For the purpose of assessing impairment, assets are grouped at the lowest level CGUs for which there is a separately identifiable cash flow available. These CGUs are based on operating areas, represented by the 2011 North Sabah EOR PSC (“North Sabah”, the Anasuria Cluster, the Marigold and Sunflower fields, the VIC/P57 exploration permit (“VIC/P57”) and the VIC/L31 production license (“VIC/L31”).) So apparently, the CGUs that have been assigned refer to the respective oil producing fields, two of which include the North Sabah field and the Anasuria field. In order to perform the impairment review, estimates of future cash flow will be made by management to assess the “recoverable amount” (as described above), subject to assumptions and an appropriate discount rate. Hence, what we can gather up to now is that management will estimate future recoverable cash flows from a CGU (i.e. the North Sabah and Anasuria oil fields), compare that to their carrying value, and perform an impairment if their future recoverable cash flows are less than their carrying value. In other words, if estimated accumulated profits from the North Sabah and Anasuria oil fields are less than their carrying value, an impairment is required. So where do we find the carrying values for the North Sabah and Anasuria oil fields? Further down on page 184 in the AR20, we see the following: Included in rights and concession are the carrying amounts of producing field licenses in the Anasuria Cluster amounting to RM668,211,518 (2018: RM687,664,530, producing field licenses in North Sabah amounting to RM471,031,008 (2018: RM414,333,116)) Hence, we can determine that the carrying values for the North Sabah and Anasuria oil fields are RM 471m and RM 668m respectively. But where do we find the future recoverable cash flows of the fields as estimated by management, and what are the assumptions used in that calculation? Fortunately, we find just that on page 185: 17 INTANGIBLE ASSETS (CONTINUED) (a Anasuria Cluster) The Directors have concluded that there is no impairment indicator for Anasuria Cluster during the current financial year. In the previous financial year, due to uncertainties in crude oil prices, the Group has assessed the recoverable amount of the intangible assets, oil and gas assets and FPSO relating to the Anasuria Cluster. The recoverable amount is determined using the FVLCTS model based on discounted cash flows (“DCF” derived from the expected cash in/outflow pattern over the production lives.) The key assumptions used to determine the recoverable amount for the Anasuria Cluster were as follows: (i Discount rate of 10%;) (ii Future cost inflation factor of 2% per annum;) (iii Oil price forecast based on the oil price forward curve from independent parties; and,) (iv Oil production profile based on the assessment by independent oil and gas reserve experts.) Based on the assessments performed, the Directors concluded that the recoverable amount calculated based on the valuation model is higher than the carrying amount. (b North Sabah) The acquisition of the North Sabah assets was completed in the previous financial year. Details of the acquisition are as disclosed in Note 15 to the financial statements. The Directors have concluded that there is no impairment indicator for North Sabah during the current financial year. Here, we can see that the recoverable amount of the Anasuria field was estimated based on a DCF of expected future cash flows over the production life of the asset. The key assumptions used by management all seem appropriate, including a discount rate of 10% and oil price and oil production estimates based on independent assessment. From there, management concludes that the recoverable amount of the Anasuria field is higher than its carrying amount (i.e. no impairment required). Likewise, for the North Sabah field. How do we interpret this? Basically, what management is saying is that given a 10% discount rate and independent oil price and oil production estimates, the accumulated profits (i.e. recoverable amount) from both the North Sabah and the Anasuria fields exceed their carrying amounts of RM 471m and RM 668m respectively. In other words, according to management’s own estimates, the carrying value of the Intangible Assets of RM 1.468 billionapproximates the accumulated Net Profit recoverable from 2P reserves. To conclude Valuation (Method 2), we arrive at the following:
Accumulated Net Profit from 2P Reserves
RM 1.452 billion
RM 1.468 billion
By now, we have established the basic economics of Hibiscus’s business, including its revenues (i.e. oil production and oil price scenarios), costs (OPEX, ITDA), profitability (breakeven, future earnings potential) and balance sheet value (2P reserves, valuation). Moving on, we want to gain a deeper understanding of the 3 statements to anticipate any blind spots and risks. We’ll refer to the financial statements of both the FY20 annual report and the 2Q21 quarterly report in this analysis. For the sake of brevity, I’ll only point out those line items which need extra attention, and skip over the rest. Feel free to go through the financial statements on your own to gain a better familiarity of the business. https://preview.redd.it/h689bss79br41.png?width=810&format=png&auto=webp&s=ed47fce6a5c3815dd3d4f819e31f1ce39ccf4a0b Income Statement First, we’ll start with the Income Statement on page 135 of the AR20. Revenues are straightforward, as we’ve discussed above. Cost of Sales and Administrative Expenses fall under the jurisdiction of OPEX, which we’ve also seen earlier. Other Expenses are mostly made up of Depreciation & Amortization of RM 115m. Finance Costs are where things start to get tricky. Why does a company which carries no debt have such huge amounts of finance costs? The reason can be found in Note 8, where it is revealed that the bulk of finance costs relate to the unwinding of discount of provision for decommissioning costs of RM 25m (Note 32). https://preview.redd.it/4omjptbe9br41.png?width=1019&format=png&auto=webp&s=eaabfc824134063100afa62edfd36a34a680fb60 This actually refers to the expected future costs of restoring the Anasuria and North Sabah fields to their original condition once the oil reserves have been depleted. Accounting standards require the company to provide for these decommissioning costs as they are estimable and probable. The way the decommissioning costs are accounted for is the same as an amortized loan, where the initial carrying value is recognized as a liability and the discount rate applied is reversed each year as an expense on the Income Statement. However, these expenses are largely non-cash in nature and do not necessitate a cash outflow every year (FY20: RM 69m). Unwinding of discount on non-current other payables of RM 12m relate to contractual payments to the North Sabah sellers. We will discuss it later. Taxation is another tricky subject, and is even more significant than Finance Costs at RM 161m. In gist, Hibiscus is subject to the 38% PITA (Petroleum Income Tax Act) under Malaysian jurisdiction, and the 30% Petroleum tax + 10% Supplementary tax under UK jurisdiction. Of the RM 161m, RM 41m of it relates to deferred tax which originates from the difference between tax treatment and accounting treatment on capitalized assets (accelerated depreciation vs straight-line depreciation). Nonetheless, what you should take away from this is that the tax expense is a tangible expense and material to breakeven analysis. Fortunately, tax is a variable expense, and should not materially impact the cash flow of Hibiscus in today’s low oil price environment. Note: Cash outflows for Tax Paid in FY20 was RM 97m, substantially below the RM 161m tax expense. https://preview.redd.it/1xrnwzm89br41.png?width=732&format=png&auto=webp&s=c078bc3e18d9c79d9a6fbe1187803612753f69d8 Balance Sheet The balance sheet of Hibiscus is unexciting; I’ll just bring your attention to those line items which need additional scrutiny. I’ll use the figures in the latest 2Q21 quarterly report (2Q21) and refer to the notes in AR20 for clarity. We’ve already discussed Intangible Assets in the section above, so I won’t dwell on it again. Moving on, the company has Equipment of RM 582m, largely relating to O&G assets (e.g. the Anasuria FPSO vessel and CAPEX incurred on production enhancement projects). Restricted cash and bank balances represent contractual obligations for decommissioning costs of the Anasuria Cluster, and are inaccessible for use in operations. Inventories are relatively low, despite Hibiscus being an E&P company, so forex fluctuations on carrying value of inventories are relatively immaterial. Trade receivables largely relate to entitlements from Petronas and BP (both oil supermajors), and are hence quite safe from impairment. Other receivables, deposits and prepayments are significant as they relate to security deposits placed with sellers of the oil fields acquired; these should be ignored for cash flow purposes. Note: Total cash and bank balances do not include approximately RM 105 m proceeds from the North Sabah December 2019 offtake (which was received in January 2020) Cash and bank balances of RM 90m do not include RM 105m of proceeds from offtake received in 3Q21 (Jan 2020). Hence, the actual cash and bank balances as of 2Q21 approximate RM 200m. Liabilities are a little more interesting. First, I’ll draw your attention to the significant Deferred tax liabilities of RM 457m. These largely relate to the amortization of CAPEX (i.e. Equipment and capitalized E&E expenses), which is given an accelerated depreciation treatment for tax purposes. The way this works is that the government gives Hibiscus a favorable tax treatment on capital expenditures incurred via an accelerated depreciation schedule, so that the taxable income is less than usual. However, this leads to the taxable depreciation being utilized quicker than accounting depreciation, hence the tax payable merely deferred to a later period – when the tax depreciation runs out but accounting depreciation remains. Given the capital intensive nature of the business, it is understandable why Deferred tax liabilities are so large. We’ve discussed Provision for decommissioning costs under the Finance Costs section earlier. They are also quite significant at RM 266m. Notably, the Other Payables and Accruals are a hefty RM 431m. What do they relate to? Basically, they are contractual obligations to the sellers of the oil fields which are only payable upon oil prices reaching certain thresholds. Hence, while they are current in nature, they will only become payable when oil prices recover to previous highs, and are hence not an immediate cash outflow concern given today’s low oil prices. Cash Flow Statement There is nothing in the cash flow statement which warrants concern. Notably, the company generated OCF of approximately RM 500m in FY20 and RM 116m in 2Q21. It further incurred RM 330m and RM 234m of CAPEX in FY20 and 2Q21 respectively, largely owing to production enhancement projects to increase the production rate of the Anasuria and North Sabah fields, which according to management estimates are accretive to ROI. Tax paid was RM 97m in FY20 and RM 61m in 2Q21 (tax expense: RM 161m and RM 62m respectively).
There are a few obvious and not-so-obvious risks that one should be aware of before investing in Hibiscus. We shall not consider operational risks (e.g. uptime, OPEX) as they are outside the jurisdiction of the equity analyst. Instead, we shall focus on the financial and strategic risks largely outside the control of management. The main ones are: · Oil prices remaining subdued for long periods of time · Fluctuation of exchange rates · Customer concentration risk · 2P Reserves being less than estimated · Significant current and non-current liabilities · Potential issuance of equity Oil prices remaining subdued Of topmost concern in the minds of most analysts is whether Hibiscus has the wherewithal to sustain itself through this period of low oil prices (sub-$30). A quick and dirty estimate of annual cash outflow (i.e. burn rate) assuming a $20 oil world and historical production rates is between RM 50m-70m per year, which considering the RM 200m cash balance implies about 3-4 years of sustainability before the company runs out of cash and has to rely on external assistance for financing. Table 1: Hibiscus EBITDA at different oil price and exchange rates https://preview.redd.it/gxnekd6h9br41.png?width=670&format=png&auto=webp&s=edbfb9621a43480d11e3b49de79f61a6337b3d51 The above table shows different EBITDA scenarios (RM ‘m) given different oil prices (left column) and USD:MYR exchange rates (top row). Currently, oil prices are $27 and USD:MYR is 1:4.36. Given conservative assumptions of average OPEX/bbl of $20 (current: $15), we can safely say that the company will be loss-making as long as oil remains at $20 or below (red). However, we can see that once oil prices hit $25, the company can tank the lower-end estimate of the annual burn rate of RM 50m (orange), while at RM $27 it can sufficiently muddle through the higher-end estimate of the annual burn rate of RM 70m (green). Hence, we can assume that as long as the average oil price over the next 3-4 years remains above $25, Hibiscus should come out of this fine without the need for any external financing. Customer Concentration Risk With regards to customer concentration risk, there is not much the analyst or investor can do except to accept the risk. Fortunately, 80% of revenues can be attributed to two oil supermajors (Petronas and BP), hence the risk of default on contractual obligations and trade receivables seems to be quite diminished. 2P Reserves being less than estimated 2P Reserves being less than estimated is another risk that one should keep in mind. Fortunately, the current market cap is merely RM 714m – at half of estimated recoverable amounts of RM 1.468 billion – so there’s a decent margin of safety. In addition, there are other mitigating factors which shall be discussed in the next section (‘Opportunities’). Significant non-current and current liabilities The significant non-current and current liabilities have been addressed in the previous section. It has been determined that they pose no threat to immediate cash flow due to them being long-term in nature (e.g. decommissioning costs, deferred tax, etc). Hence, for the purpose of assessing going concern, their amounts should not be a cause for concern. Potential issuance of equity Finally, we come to the possibility of external financing being required in this low oil price environment. While the company should last 3-4 years on existing cash reserves, there is always the risk of other black swan events materializing (e.g. coronavirus) or simply oil prices remaining muted for longer than 4 years. Furthermore, management has hinted that they wish to acquire new oil assets at presently depressed prices to increase daily production rate to a targeted 20,000 bbl by end-2021. They have room to acquire debt, but they may also wish to issue equity for this purpose. Hence, the possibility of dilution to existing shareholders cannot be entirely ruled out. However, given management’s historical track record of prioritizing ROI and optimal capital allocation, and in consideration of the fact that the MD owns 10% of outstanding shares, there is some assurance that any potential acquisitions will be accretive to EPS and therefore valuations.
As with the existence of risk, the presence of material opportunities also looms over the company. Some of them are discussed below: · Increased Daily Oil Production Rate · Inclusion of 2C Resources · Future oil prices exceeding $50 and effects from coronavirus dissipating Increased Daily Oil Production Rate The first and most obvious opportunity is the potential for increased production rate. We’ve seen in the last quarter (2Q21) that the North Sabah field increased its daily production rate by approximately 20% as a result of production enhancement projects (infill drilling), lowering OPEX/bbl as a result. To vastly oversimplify, infill drilling is the process of maximizing well density by drilling in the spaces between existing wells to improve oil production. The same improvements are being undertaken at the Anasuria field via infill drilling, subsea debottlenecking, water injection and sidetracking of existing wells. Without boring you with industry jargon, this basically means future production rate is likely to improve going forward. By how much can the oil production rate be improved by? Management estimates in their analyst presentation that enhancements in the Anasuria field will be able to yield 5,000 bbl/day by 2021 (current: 2,500 bbl/day). Similarly, improvements in the North Sabah field is expected to yield 7,000 bbl/day by 2021 (current: 5,300 bbl/day). This implies a total 2021 expected daily production rate from the two fields alone of 12,000 bbl/day (current: 8,000 bbl/day). That’s a 50% increase in yields which we haven’t factored into our valuation yet. Furthermore, we haven’t considered any production from existing 2C resources (e.g. Marigold/Sunflower) or any potential acquisitions which may occur in the future. By management estimates, this can potentially increase production by another 8,000 bbl/day, bringing total production to 20,000 bbl/day. While this seems like a stretch of the imagination, it pays to keep them in mind when forecasting future revenues and valuations. Just to play around with the numbers, I’ve come up with a sensitivity analysis of possible annual EBITDA at different oil prices and daily oil production rates: Table 2: Hibiscus EBITDA at different oil price and daily oil production rates https://preview.redd.it/jnpfhr5n9br41.png?width=814&format=png&auto=webp&s=bbe4b512bc17f576d87529651140cc74cde3d159 The left column represents different oil prices while the top row represents different daily oil production rates. The green column represents EBITDA at current daily production rate of 8,000 bbl/day; the orange column represents EBITDA at targeted daily production rate of 12,000 bbl/day; while the purple column represents EBITDA at maximum daily production rate of 20,000 bbl/day. Even conservatively assuming increased estimated annual ITDA of RM 500m (FY20: RM 318m), and long-term average oil prices of $50 (FY20: $60), the estimated Net Profit and P/E ratio is potentially lucrative at daily oil production rates of 12,000 bbl/day and above. 2C Resources Since we’re on the topic of improved daily oil production rate, it bears to pay in mind the relatively enormous potential from Hibiscus’s 2C Resources. North Sabah’s 2C Resources alone exceed 30 mmbbl; while those from the yet undiagnosed Marigold/Sunflower fields also reach 30 mmbbl. Altogether, 2C Resources exceed 70 mmbbl, which dwarfs the 44 mmbbl of 2P Reserves we have considered up to this point in our valuation estimates. To refresh your memory, 2C Resources represents oil volumes which have been discovered but are not yet classified as “commercial”. This means that there is reasonable certainty of the oil being recoverable, as opposed to simply being in the very early stages of exploration. So, to be conservative, we will imagine that only 50% of 2C Resources are eligible for reclassification to 2P reserves, i.e. 35 mmbbl of oil. https://preview.redd.it/mto11iz7abr41.png?width=375&format=png&auto=webp&s=e9028ab0816b3d3e25067447f2c70acd3ebfc41a This additional 35 mmbbl of oil represents an 80% increase to existing 2P reserves. Assuming the daily oil production rate increases similarly by 80%, we will arrive at 14,400 bbl/day of oil production. According to Table 2 above, this would yield an EBITDA of roughly RM 630m assuming $50 oil. Comparing that estimated EBITDA to FY20’s actual EBITDA:
FY21 (incl. 2C)
Daily oil production (bbl/day)
Average oil price (USD/bbl)
Average OPEX/bbl (USD)
EBITDA (RM ‘m)
Hence, even conservatively assuming lower oil prices and higher OPEX/bbl (which should decrease in the presence of higher oil volumes) than last year, we get approximately the same EBITDA as FY20. For the sake of completeness, let’s assume that Hibiscus issues twice the no. of existing shares over the next 10 years, effectively diluting shareholders by 50%. Even without accounting for the possibility of the acquisition of new oil fields, at the current market capitalization of RM 714m, the prospective P/E would be about 10x. Not too shabby. Future oil prices exceeding $50 and effects from coronavirus dissipating Hibiscus shares have recently been hit by a one-two punch from oil prices cratering from $60 to $30, as a result of both the Saudi-Russian dispute and depressed demand for oil due to coronavirus. This has massively increased supply and at the same time hugely depressed demand for oil (due to the globally coordinated lockdowns being implemented). Given a long enough timeframe, I fully expect OPEC+ to come to an agreement and the economic effects from the coronavirus to dissipate, allowing oil prices to rebound. As we equity investors are aware, oil prices are cyclical and are bound to recover over the next 10 years. When it does, valuations of O&G stocks (including Hibiscus’s) are likely to improve as investors overshoot expectations and begin to forecast higher oil prices into perpetuity, as they always tend to do in good times. When that time arrives, Hibiscus’s valuations are likely to become overoptimistic as all O&G stocks tend to do during oil upcycles, resulting in valuations far exceeding reasonable estimates of future earnings. If you can hold the shares up until then, it’s likely you will make much more on your investment than what we’ve been estimating.
Wrapping up what we’ve discussed so far, we can conclude that Hibiscus’s market capitalization of RM 714m far undershoots reasonable estimates of fair value even under conservative assumptions of recoverable oil volumes and long-term average oil prices. As a value investor, I hesitate to assign a target share price, but it’s safe to say that this stock is worth at least RM 1.00 (current: RM 0.45). Risk is relatively contained and the upside far exceeds the downside. While I have no opinion on the short-term trajectory of oil prices, I can safely recommend this stock as a long-term Buy based on fundamental research.
So a profit factor equal 1 means that if you invest 1 dollar you get back exactly the dollar you invested not that good deal while taking the risk of losing it. What is metatrader 4 and how do you use it. Profit factor indicator software gives you buy and sell signals. After installation of this forex indicator you ll see green or red arrows ... A profit factor equal to 1 tells us that for every dollar we lose we will win 1. A profit factor equal to 2.5 tells us that this system has earned two and a half dollars for every dollar it has lost. In this way, with the profit factor, we can have a clear vision of the performance of the trading system. Disadvantages of this indicator Profit Factor for this report is 2.50, but what really is profit factor?It is the ratio between Gross profits 895.57$ and Gross loss 357.86$ in this model.. Profit Factor = 897.57 / 357.86 = 2.508159615492091879505952048287. Basically Profit Factor means that if I invest 1 dollar I can expect to get 2.5$ back from trading that model.So I can expect to take back my dollar and earn a profit of 1 ... Profit factor, Statistical Expectancy (average profitability per trade), Expectation (mathematical outcome). Your Trade Plan Win Loss Ratio Win rate is usually the metric that is first considered by new traders and often pitched by trading system or service sellers in aggressive and “over the top” advertising . If something has a high profit factor, this is a good thing - eg 5.0 ($5 gained for every $1 risked). Wrong, the vast majority of high profit factors come from curve fitting and they dont last very long. Large returns come from large risks, or impecable timing with huge runs or from the famous 99% win ratio threads. A PF of 2.0 is quite high. Like all things backtested, past results are not an ... Profit Factor is simply defined as gross profits divided by gross losses. That’s it in a nutshell, but sometimes the simplest things hold the most value. So let’s imagine your trading system’s gross profit for the past year was $40,000 and your gross losses were $20,000. Your Profit Factor would be 2. ($40k / $20k = 2). The formula is simply giving you a reading as to the difference ... No profit factor is the total ratio of how much you actually gained in winning trades to how much you actually lost in losing trades. It has nothing to do with how much you risk. Anything over 1 and you're profitable. However just the profit factor alone is not a good way to evaluate someone's results as it tells you nothing about their potential drawdown or % return over time.
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