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THROW YOUR FD's in FDS
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focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and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.
In all industries there are people credited to being the simplest . In design, the late Steve Jobs is credited to being the simplest in his industry. In boxing, Muhammad Ali was credited to being the simplest boxer of all time. In U.S. politics, there's a consensus that Lincoln was the nation’s greatest President by every measure applied. In the trading world, a variety of traders are known worldwide for his or her skills. From Jesse Livermore to George Soros, we are sharing these tales of past and present traders who had to claw their thanks to the highest . Here, we'll check out the five most famous traders of all time and canopy a touch bit about each trader and why they became so famous. Jesse Livermore Jesse Livermore jumped into the stock exchange with incredible calculations at the age of 15, amassed huge profits, then lost all of them , then mastered two massive crises and came out the opposite side while following his own rules, earning him the nickname “The Great Bear of Wall Street.” Livermore was born in 1877 in Shrewsbury, Massachusetts. Visit شركة اكويتي السعودية He is remembered for his incredible risk taking, his gregarious method of reading the potential moves within the stock exchange , derivatives and commodities, and for sustaining vast losses also as rising to fortune. He began his career having run far away from home by carriage to flee a lifetime of farming that his father had planned for him, instead choosing city life and finding work posting stock quotes at Paine Webber, a Boston stockbroker. Livermore bought his first share at 15 and earned a profit of $3.12 from $5 after teaching himself about trends. George Soros George Soros has a fantastic backstory. Born in Hungary in 1930 to Jewish parents, Soros survived the Holocaust and later fled the country when the Communists took power. He went on to become one among the richest men and one among the foremost famous philanthropists within the world. Most day traders know him for his long and prolific career as a trader who famously “broke the Bank of England” in 1992. Soros made an enormous bet against British Pound, which earned him $1 billion in profit in only 24 hours. Along with other currency speculators, he placed a bet against the bank’s ability to carry the road on the pound. He borrowed pounds, then sold them, helping to down the worth of the currency on forex markets and ultimately forcing the united kingdom to crash out of the ecu rate of exchange Mechanism. It was perhaps the quickest billion dollars anyone has ever made and one among the foremost famous trades ever taken, which later became referred to as “breaking the Bank of England”. Soros is believed to have netted a complete of about $44 billion through financial speculation. And he has used his fortune to find thousands of human rights, democracy, health, and education projects. Richard Dennis There are only a couple of traders which will take a little amount of cash and switch it into millions and Richard Dennis was one among them. Known as the “Prince of the Pit”, Dennis is claimed to have borrowed $1,600 when he was around 23 years old and turned it into $200 million in about 10 years trading commodities. Even more interesting to notice , he only traded $400 of the $1,600. Not only did he achieve great success as a commodities trader, he also went on to launch the famous “Turtle Traders Group”. Using mini contracts, Dennis began to trade his own account at the Mid America commodities exchange . He made a profit of $100,000 in 1973. The subsequent year, he capitalized on a runway soybean market to earn $500,000 in profits. He became an impressive millionaire at the top of the year. However, he incurred massive losses within the Black Monday stock exchange crash in 1987 and therefore the dot-com bubble burst in 2000. While he's famous for creating and losing tons of cash , Dennis is additionally famous for something else – an experiment. He and his friend William Eckhardt recruited and trained traders, a couple of men and ladies, the way to trade futures. These so-called Turtle Traders went on to form profits of $175 million in 4 years, consistent with a former student. Paul Tudor Jones Paul Tudor Jones thrust into the limelight within the 80s when he successfully predicted the 1987 stock exchange , as shown within the riveting one hour documentary called “Trader”. The legendary trader was born in Memphis, Tennessee in 1954. His father ran a financial and legal trade newspaper. While he was in college, he want to write articles for the newspaper under the pseudonym, “Eagle Jones”. Jones began his journey within the finance business by trading cotton. He started trading on his own following 4 years of non-trading experience, made profits from his trades but got bored, and later hired people to trade for him so he would not get bored. But the trade that shot him to fame came on Black Monday in 1987, when he made an estimated $100 million whilst the Dow Jones Industrial Average plunged 22%. He became a pioneer within the area of worldwide macro investing and was an enormous player within the meteoric growth of the hedge fund industry. He's also known for depending on currencies and interest rates. He founded his hedge fund, Tudor Investment Corp, in 1980. The fund currently has around $21 billion in assets under management and he himself has an estimated net worth of nearly $5.8 Billion. John Paulson Super-trader John Paulson built a private fortune worth $4.4 billion from managing other people’s money. Born in 1955, Paulson made his name and far of his money betting a huge amount of money against the U.S. housing market during the worldwide financial crisis of 2007–2008. Paulson bought insurance against defaults by subprime mortgages before the market collapse in 2007. He netted an estimated $20 billion on the collapse of the subprime mortgage market, dubbed the best trade ever. However, his diary since that bet has been patchy at the best . Within the years following the financial crisis, Paulson struggled to match this success. Failed bets on gold, healthcare and pharmaceutical stocks caused investors to escape his hedge fund Paulson & Co, cutting its assets under management to $10 billion as of January 2020 from a high of $36 billion in 2011. Earlier this year, Paulson announced the fund would stop managing money for outdoor clients and switch it into a family office. He launched the fund in 1994.
Wiseling investment starting at 0.8 daily profit, invest with BTC, ETH or USD
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From the first half of the news trading note we learned some ways to estimate what is priced in by the market. We learned that we are trading any gap in market expectations rather than the result itself. A good result when the market expected a fantastic result is disappointing! We also looked at second order thinking. After all that, I hope the reaction of prices to events is starting to make more sense to you. Before you understand the core concepts of pricing in and second order thinking, price reactions to events can seem mystifying at times We'll add one thought-provoking quote. Keynes (that rare economist who also managed institutional money) offered this analogy. He compared selecting investments to a beauty contest in which newspaper readers would write in with their votes and win a prize if their votes most closely matched the six most popularly selected women across all readers: It is not a case of choosing those (faces) which, to the best of one’s judgment, are really the prettiest, nor even those which average opinions genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. Trading is no different. You are trying to anticipate how other traders will react to news and how that will move prices. Perhaps you disagree with their reaction. Still, if you can anticipate what it will be you would be sensible to act upon it. Don't forget: meanwhile they are also trying to anticipate what you and everyone else will do. Part II
Preparing for quantitative and qualitative releases
Data surprise index
Using recent events to predict future reactions
Buy the rumour, sell the fact
The trimming position effect
Some key FX releases
Preparing for quantitative and qualitative releases
The majority of releases are quantitative. All that means is there’s some number. Like unemployment figures or GDP. Historic results provide interesting context. We are looking below the Australian unemployment rate which is released monthly. If you plot it out a few years back you can spot a clear trend, which got massively reversed. Knowing this trend gives you additional information when the figure is released. In the same way prices can trend so do economic data. A great resource that's totally free to use This makes sense: if for example things are getting steadily better in the economy you’d expect to see unemployment steadily going down. Knowing the trend and how much noise there is in the data gives you an informational edge over lazy traders. For example, when we see the spike above 6% on the above you’d instantly know it was crazy and a huge trading opportunity since a) the fluctuations month on month are normally tiny and b) it is a huge reversal of the long-term trend. Would all the other AUDUSD traders know and react proportionately? If not and yet they still trade, their laziness may be an opportunity for more informed traders to make some money. Tradingeconomics.com offers really high quality analysis. You can see all the major indicators for each country. Clicking them brings up their history as well as an explanation of what they show. For example, here’s German Consumer Confidence. Helpful context There are also qualitative events. Normally these are speeches by Central Bankers. There are whole blogs dedicated to closely reading such texts and looking for subtle changes in direction or opinion on the economy. Stuff like how often does the phrase "in a good place" come up when the Chair of the Fed speaks. It is pretty dry stuff. Yet these are leading indicators of how each member may vote to set interest rates. Ed Yardeni is the go-to guy on central banks.
Data surprise index
The other thing you might look at is something investment banks produce for their customers. A data surprise index. I am not sure if these are available in retail land - there's no reason they shouldn't be but the economic calendars online are very basic. You’ll remember we talked about data not being good or bad of itself but good or bad relative to what was expected. These indices measure this difference. If results are consistently better than analysts expect then you’ll see a positive number. If they are consistently worse than analysts expect a negative number. You can see they tend to swing from positive to negative. Mean reversion at its best! Data surprise indices measure how much better or worse data came in vs forecast There are many theories for this but in general people consider that analysts herd around the consensus. They are scared to be outliers and look ‘wrong’ or ‘stupid’ so they instead place estimates close to the pack of their peers. When economic conditions change they may therefore be slow to update. When they are wrong consistently - say too bearish - they eventually flip the other way and become too bullish. These charts can be interesting to give you an idea of how the recent data releases have been versus market expectations. You may try to spot the turning points in macroeconomic data that drive long term currency prices and trends.
Using recent events to predict future reactions
The market reaction function is the most important thing on an economic calendar in many ways. It means: what will happen to the price if the data is better or worse than the market expects? That seems easy to answer but it is not. Consider the example of consumer confidence we had earlier.
Many times the market will shrug and ignore it.
But when the economic recovery is predicated on a strong consumer it may move markets a lot.
Or consider the S&P index of US stocks (Wall Street).
If you get good economic data that beats analyst estimates surely it should go up? Well, sometimes that is certainly the case.
But good economic data might result in the US Central Bank raising interest rates. Raising interest rates will generally make the stock market go down!
So better than expected data could make the S&P go up (“the economy is great”) or down (“the Fed is more likely to raise rates”). It depends. The market can interpret the same data totally differently at different times. One clue is to look at what happened to the price of risk assets at the last event. For example, let’s say we looked at unemployment and it came in a lot worse than forecast last month. What happened to the S&P back then? 2% drop last time on a 'worse than expected' number ... so it it is 'better than expected' best guess is we rally 2% higher So this tells us that - at least for our most recent event - the S&P moved 2% lower on a far worse than expected number. This gives us some guidance as to what it might do next time and the direction. Bad number = lower S&P. For a huge surprise 2% is the size of move we’d expect. Again - this is a real limitation of online calendars. They should show next to the historic results (expected/actual) the reaction of various instruments.
Buy the rumour, sell the fact
A final example of an unpredictable reaction relates to the old rule of ‘Buy the rumour, sell the fact.’ This captures the tendency for markets to anticipate events and then reverse when they occur. Buy the rumour, sell the fact In short: people take profit and close their positions when what they expected to happen is confirmed. So we have to decide which driver is most important to the market at any point in time. You obviously cannot ask every participant. The best way to do it is to look at what happened recently. Look at the price action during recent releases and you will get a feel for how much the market moves and in which direction.
Trimming or taking off positions
One thing to note is that events sometimes give smart participants information about positioning. This is because many traders take off or reduce positions ahead of big news events for risk management purposes. Imagine we see GBPUSD rises in the hour before GDP release. That probably indicates the market is short and has taken off / flattened its positions. The price action before an event can tell you about speculative positioning If GDP is merely in line with expectations those same people are likely to add back their positions. They avoided a potential banana skin. This is why sometimes the market moves on an event that seemingly was bang on consensus. But you have learned something. The speculative market is short and may prove vulnerable to a squeeze.
Two kinds of reversals
Fairly often you’ll see the market move in one direction on a release then turn around and go the other way. These are known as reversals. Traders will often ‘fade’ a move, meaning bet against it and expect it to reverse.
Sometimes this happens when the data looks good at first glance but the details don’t support it. For example, say the headline is very bullish on German manufacturing numbers but then a minute later it becomes clear the company who releases the data has changed methodology or believes the number is driven by a one-off event. Or maybe the headline number is positive but buried in the detail there is a very negative revision to previous numbers. Fading the initial spike is one way to trade news. Try looking at what the price action is one minute after the event and thirty minutes afterwards on historic releases.
Some reversals don't make sense Sometimes a reversal happens for seemingly no fundamental reason. Say you get clearly positive news that is better than anyone expects. There are no caveats to the positive number. Yet the price briefly spikes up and then falls hard. What on earth? This is a pure supply and demand thing. Even on bullish news the market cannot sustain a rally. The market is telling you it wants to sell this asset. Try not to get in its way.
Some key releases
As we have already discussed, different releases are important at different times. However, we’ll look at some consistently important ones in this final section.
Interest rates decisions
These can sometimes be unscheduled. However, normally the decisions are announced monthly. The exact process varies for each central bank. Typically there’s a headline decision e.g. maintain 0.75% rate. You may also see “minutes” of the meeting in which the decision was reached and a vote tally e.g. 7 for maintain, 2 for lower rates. These are always top-tier data releases and have capacity to move the currency a lot. A hawkish central bank (higher rates) will tend to move a currency higher whilst a dovish central bank (lower rates) will tend to move a currency lower. A central banker speaking is always a big event
Non farm payrolls
These are released once per month. This is another top-tier release that will move all USD pairs as well as equities. There are three numbers:
The headline number of jobs created (bigger is better)
The unemployment rate (smaller is better)
Average hourly earnings (depends)
Bear in mind these headline numbers are often off by around 75,000. If a report comes in +/- 25,000 of the forecast, that is probably a non event. In general a positive response should move the USD higher but check recent price action. Other countries each have their own unemployment data releases but this is the single most important release.
There are various types of surveys: consumer confidence; house price expectations; purchasing managers index etc. Each one basically asks a group of people if they expect to make more purchases or activity in their area of expertise to rise. There are so many we won’t go into each one here. A really useful tool is the tradingeconomics.com economic indicators for each country. You can see all the major indicators and an explanation of each plus the historic results.
Gross Domestic Product is another big release. It is a measure of how much a country’s economy is growing. In general the market focuses more on ‘advance’ GDP forecasts more than ‘final’ numbers, which are often released at the same time. This is because the final figures are accurate but by the time they come around the market has already seen all the inputs. The advance figure tends to be less accurate but incorporates new information that the market may not have known before the release. In general a strong GDP number is good for the domestic currency.
Countries tend to release measures of inflation (increase in prices) each month. These releases are important mainly because they may influence the future decisions of the central bank, when setting the interest rate. See the FX fundamentals section for more details.
Things like factory orders or or inventory levels. These can provide a leading indicator of the strength of the economy. These numbers can be extremely volatile. This is because a one-off large order can drive the numbers well outside usual levels. Pay careful attention to previous releases so you have a sense of how noisy each release is and what kind of moves might be expected.
Often there is really good stuff in the comments/replies. Check out 'squitstoomuch' for some excellent observations on why some news sources are noisy but early (think: Twitter, ZeroHedge). The Softbank story is a good recent example: was in ZeroHedge a day before the FT but the market moved on the FT. Also an interesting comment on mistakes, which definitely happen on breaking news, and can cause massive reversals.
ASIC Regulation Thread - Regarding the proposed changes ( Australians effected the most )
I'm hopeless at formatting text, so if you think you can structure this post better take everything i write and put it into an easy to digest way. I'm just going to type out everything i know in text as fast as possible. I'm not a legal expert, I'm not somehow who understands every bit of information in the PDF's below, but i know I'm a retail trader that uses leverage to make profit which is why I'm posting this, in the hope that someone who can run a charge better than me, will. Some of you are already aware of what might be happening, this is just a post to educate retail traders on changes that might be coming to certain brokers. This effects Australian Customers the most, but also effects those living in other countries that use Australian brokers, such as Pepperstone and others. Last year in August 2019, ASIC ( Australian Securities and Investments Commission ) was concerned about retail traders going into Forex and Binary options without understanding these instruments properly and started sticking their noses in for tough regulation. ASIC asked brokers and anyone with interest in the industry to write to them and explain what should and should not change from the changes they proposed, some of the proposed changes are very misguided and come from a lack of understanding exactly how OTC derivatives actually work. I will provide the link to the paper further down so you can read it yourself and i will provide a link to all the submission made by all parties that sent submissions to ASIC, however the 2 main points of debate are: 1, To reduce the overall leverage available to retail traders to either 20:1 or 30:1. This means people who currently use leverage such as 100:1 to 500:1 and everything in between will be effected the most, even more so are those traders with relatively small accounts, meaning in order to get your foot in the door to trading you will need more capital for it to be viable. ^^ This point above is very important. 2, The removing of Binary options trading, which basically includes products like "Bet if gold will rise to this price in the next 30 seconds" This sort of stuff. So far from all the submissions from brokers and individuals nobody really cares if this changes as far as i know, though if you have concerns about this i would start voicing your disapproval. Though i would not waste your time here, all is pointing to this being eradicated completely with brokers also supporting the changes, I've never used such a product and know very little about them. ^^ This point above isn't very important and will probably be enforced in the future. Still to this day i see retail traders not understanding leverage, they think of it as "dangerous and scary", it's not, position size is the real danger, not leverage. So ASIC is aiming to limit retail traders access to high leverage, they are claiming it is a way to protect traders who don't really understand what they are getting into by attacking leverage and not the real problem which is position size relative to your capital. If it was truly about protecting retail traders from blowing up their accounts, they would look for ways to educate traders on "understanding position sizes and why it's important" rather than attacking leverage, but their goal is misguided or has an ulterior motive . I will give you a small example below. EXAMPLE - We will use 2 demo accounts for demonstration purposes. If you don't understand my example, i suggest you try it for yourself. - Skip if not interested in examples. Lets say we open 2 demo accounts with $1000 in both, one with 20:1 leverage and one with 500:1 leverage and we open an identical position on both accounts ( say a micro lot '0.01' on EURUSD ). You are safer on the 500:1 account as you don't need to put up as much margin as collateral as you would on the 20:1. If the trade we just opened goes against us and continues against us, the account with 20:1 leverage will run out of free margin a lot faster than the 500:1 account. In this simple example is shows you that leverage is not dangerous but safer and gives you a lot more breathing room. This trade was a small micro lot, so it would take hundreds of pips movements to get margin called and blow up that $1000 on each account. Lets now use a different position size to truly understand why retail traders blow up accounts and is the reason why trading can be dangerous. This time instead of opening a micro lot of '0.01' on our $1000 dollar demo accounts, lets open a position size much larger, 5 lots. Remember we only have $1000 and we are about to open a position much larger relative to our capital ( which we should never do because we can't afford to do that ) the 20:1 probably wont even let you place that trade if you don't have enough margin as collateral or if you could open the position you would have a very tiny amount of free margin left over, meaning a small pip movement against you will instantly blow up your $1000 account. On the 500:1 account you wouldn't need to put up as much margin as collateral with more free margin if the trade goes bad, but again a small movement could blow up your account. In this example, both accounts were dangerous because the lack of understanding position sizes, opening a position you can't afford to open. This is what the true danger is, not the leverage. Even in the second example, the higher leverage would "margin call" you out later. So i would go as far to say that lower leverage is more dangerous for you because it margin calls you out faster and just by having a lower leverage doesn't stop you from opening big positions that can blow you up in a 5 pip movement anymore, any leverage size is dangerous if you're opening positions you can't afford to open. This is also taking into consideration that no risk management is being used, with risk management higher leverage is even more powerful. ASIC believes lowering leverage will stop people opening positions that they can't afford. When the reality is no matter how much capital you have $500, $1000, $5000, $50,000, $500,000, $5,000,000. You don't open position sizes that will blow that capital up completely with small movements. The same thing can happen on a 20:1 or 500:1 account. Leverage is a tool, use it, if your on a lower leverage already such as 20:1, 30:1 it means your country has been regulated and you already have harder trading conditions. Just remember higher leverage allows you to open larger position sizes in total for the amount of money you own, but the issue is NOT that your using the higher leverage but because you are opening positions you can't afford, for what ever reason that is, the only fix for this is education and will not be fixed by simply lowing leverage, since you can just as easy blow up your account on low leverage just as fast or if not faster. So what is going on? There might ( get your tinfoil hats on ) be more that is involved here, deeper than you think, other agendas to try and stop small time retail traders from making money via OTC products, theories such as governments not wanting their citizens to be traders, rather would prefer you to get out there and work a 9 to 5 instead. Effective ways to do this would be making conditions harder with a much larger barrier of entry and the best way to increase the barrier of entry for retail traders is to limit leverage, lower leverage means you need to put up more money, less breathing room for trades, lower potential. They are limiting your upside potential and the downside stays the same, a blown account is a blow account. Think of leverage as a weapon, a person wielding a butchers knife can probably destroy a person wielding a steak knife, but both knifes can prove fatal. They want to make sure your holding the butter knife then tell you to butcher a cow with it. 30:1 leverage is still workable and can still be profitable, but not as profitable as 500:1 accounts. This is why they are allowing professionals to use high leverage, this gives them another edge over successful retail traders who will still be trying to butcher a cow with a butter knife, while they are slaying limbs off the cow with machetes. It's a way to hamstring you and keep you away rather than trying to "protect" you. The real danger is not leverage, they are barking up the wrong tree, how convenient to be barking up the very tree most retail traders don't fully understand ( leverage) , pass legislation to make trading conditions harder and at the same time push the narrative that trading is dangerous by making it even harder. A full circle strategy to make your trading conditions worse, so you don't succeed. Listen carefully especially if you trade with any of the brokers that have provided their submissions to ASIC. Brokers want to seem like they are on your side and so far some of the submissions ( i haven't read them all ) have brokers willing to drop their leverage down to 30:1 because they know by dropping the leverage down it will start margin calling out their clients at a much faster rate, causing more blown up accounts / abandoned accounts with residual margin called funds, but they also know that if they make trading environments too hard less people will trade or even worse move their funds elsewhere offshore to unregulated brokers that offer higher leverage. Right now it's all just a proposal, but as governments expand and continue to gain more control over it's citizens, it's just a matter of time till it's law, it's up to you to be vocal about it, let your broker know that if they drop their leverage, you're out, force them to fight for you. If you have any more information related to this, or have anything to add, post below. I'm not an expert at this technical law talk, i know that i do well with 500:1 leverage and turn profits with it, it would be harder for me to do on a lower leverage, this is the reason for my post. All related documents HERE CP-322 ( Consultation paper 322 ) & Submissions from brokers and others. https://asic.gov.au/regulatory-resources/find-a-document/consultation-papers/cp-322-product-intervention-otc-binary-options-and-cfds/
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.
Immediate Edge Review, Is Immediate Edge SCAM Or Legit Trading App?
Immediate Edge Review: Is This Crypto Robot Legit or Scam Immediate Edge Review and investigation 20twenty. The Immediate Edge app is a crypto, forex and choices trading robot utilized by folks to automatically obtain and sell Bitcoin and create profits. Wanting at the website, many people claim it helped them move from rags-to-riches trading Bitcoin. Further, some claims linked it to Ronaldo and Sir Alex Ferguson https://preview.redd.it/rttn3i4hohm51.jpg?width=1280&format=pjpg&auto=webp&s=8f0dc345c3ace4032d571d44fabe356f13ff1a33 Is Immediate Edge app legit or scam? Whereas the claims of its linkage to the higher than celebrities are unverifiable, we tend to can verify that the app is not a scam and permits individuals to trade Bitcoin using the Fibonacci strategy with ten minutes time frames The app, that allows people to deposit at least $250 through mastercard and Sofort, scores 88% rate and a 5 stars as a real software Since there are several scam cryptos, forex and options brokers who trick individuals to depositing money, and then they run away with the funds, we have taken time to review this software to determine if it is real or a scam. Is Immediate Edge scam or legit High success rate is reported by users with this software. The Immediate Edge web site provides truthful claims about the service though it will not mean the crypto trading risks are eliminated with its use. 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With an investment of $250, you'll be able to expect to form a lot of lesser although some people claim to own made $12a pair of in a very few hours using this software. That will not mean Immediate Edge is error-free. There still is a heap of unpredictable high volatility in crypto and bots will make mistakes and errors to create losses. Auto trading robots are better employed in combination with manual trading strategies. https://preview.redd.it/1zkt9v3johm51.jpg?width=1280&format=pjpg&auto=webp&s=85f7e7f5d0e9d6b60b4a8a6e37bb344dbbb8305c Immediate Edge Review How will Immediate Edge work? All a user has to try and do is join up at the Immediate Edge web site, then deposit funds to have access to the robot, when which they can begin trading by switching on the bot. It will would like no control or intervention from humans, beyond beginning and stopping it. 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You also get to observe the profits/losses and decide if to continue and/or when to prevent. https://preview.redd.it/c9scw5fkohm51.jpg?width=1280&format=pjpg&auto=webp&s=3d127be2887c4c8960023a8cf1b1f55297dbf250 Withdrawals, user verification, cost of using the app and alternative options The payouts or withdrawals are made by filling letter of invitation type on the funds’ management page and it can take two operating days to replicate in your checking account. No fee is charged on withdrawals. You'll withdraw your cash including the capital while not a lot of problem on this app, that is better than several that don't enable withdrawals at any time While some bots need verifications by asking for your ID and statements, this one will not. You are done once uploading your payment details. The bot charges a commission on profit. Besides, you get twenty fouseven client support on Immediate Edge Immediate Edge may be a legit, secure, user-friendly trading application for crypto, stocks, and choices. It has a zealous customer service and reports a high success rate. Another smart robot we have recently reviewed is Bitcoin Professional We tend to hope that this review helped you to make a decision concerning this trading app. Additionally, subscribe to our web site to be invariably notified concerning new software from this industry. For live reviews subscribe to our Youtube Channel or FB Page. https://www.immediateedge.org/ https://www.facebook.com/immediateedge/ https://www.pinterest.co.uk/immediateedge/ https://twitter.com/EdgeImmediate https://www.instagram.com/immediateedge/
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
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T3 Newsbeat Live is run by Mark Melnick, a 20-year veteran trader from New York. According to him, he made his first million at the age of 19 during the dot-com boom back in the late 90s. He claims that his trading room is the fastest growing trading room at T3 and also the Wall Street’s #1 trading room. You can see this in the description of his videos on Youtube. He is a big proponent of reaching the highest win rate possible in trading. He openly shares some of his trading strategies in free videos and claims that some of his strategies are batting over 70% or even 80 %. He also often says that some of the members enjoy a win rate over 90% using his strategies. I will let you be the judge of this. Self-Promotion He makes a lot of videos to attract new people into his trading room. His daily videos are uploaded on Facebook and Youtube almost daily even on Weekends (mostly excluding Friday evening & Saturdays). In so many videos you’d hear him talking about how his trading room has an edge over other trading rooms while bashing other trading rooms as a whole. He often talks about how his trading room bought stocks/options at the near bottom or shorted at the near top using his “algorithmic analysis” which can be applied to all markets (stocks, future, forex, crypto). Piques your curiosity, right? In fact, that’s how I got to give his trading room a try. “Who in the hell wouldn’t want to catch the top & bottom in the markets, right?” So, you would think people in his room and himself are making a killing using his algorithmic analysis? Not so fast… (in fact, his algorithmic analysis is just drawing trendlines and identifying the most probable support and resistance) When it works (of course, nothing works 100% of the time), you are able to catch just few cents off the top and bottom when it works if you follow his trade. However, you have no idea how long you’d have to hold your position. Mark doesn’t know either. So, he usually goes for nickels and dimes and rarely holds a position longer than 5 minutes. Even if he’s good at picking bottoms and tops, you’d often risk more than nickels and dimes just to make nickels and dimes. Make sense, right? ……. ……. ……. Also, because he gets out of his positions fast, he misses out on riding some potentially big trades. Oh, how I wish stay in that position a bit longer. He doesn’t say but one can surmise that he often leave too much on the table. Of course, it’s important to take your profit fast when you scalp but you consistently leave too much on the table like he does, one has to wonder if he has any system for taking profits (otherwise, it’s all discretionary guessing). This type of bottom/top picking is not his main strategy, though. The strategy that makes him the most amount of money might surprise you. I will get to this later. How Mark Trades (Mark’s Trading Setups and Strategies) Mainly, he scans the market in the morning for earnings reports, analysts’ upgrades/downgrades and other catalysts that have potential to make moves in the market. He openly shares his mockery or insult of analysts, calling certain analysts “idiots” or “imbeciles”. He puts on his first trade(s) early in the morning (from 9:30AM to 10:00AM Eastern Standard Time) when the market move is the most volatile. Some of his strategies use market order during this period of volatile time using options. You can see why this can be very risky and especially on thinly traded options with side spread. He does point out this but sometimes you hear people in the room stuck in an options position that they can’t get out. Just like his trades from calling the top/bottom of a stock, he gets in and gets out of a position within minutes if not seconds while going for nickels and dimes while staring at 1minute and 5-minutes charts. That applies to most, if not all of his strategies. (Yes, sometimes he does catch bigger moves than nickels and dimes.) When you trade during the most volatile time in the morning, you’re subjected to wild moves in both directions. If you’re overly prudent or inexperienced in trading, your stop (unless very wide), has a very high chance of hitting. A lot of times it might stop you out and go in the direction that you predicted. So, when you’ve been trading during this time, you’d probably don’t set a stoploss order or a hard stop to avoid getting fleeced. You do have to be proactive at cutting your loss as quickly as possible. Otherwise you’d find yourself scrambling to get out your position while the bid keeps dropping. I have to say that Mark is very cautious and he does get out of trades very fast if he has doubt. A lot of times he lets out exhausting, heavy sighs and even murmurs some swear words when things don’t seem to go the way he wants in a trade. Besides calling certain analysts, “imbeciles” and “idiots”, this is quite unprofessional but no one in the room has the gut to point things out like this. The irony is that he is the “head of trading psychology” at T3 and it doesn’t seem like that he doesn’t have much control over his trading psychology and let alone his emotion. People in trading chatrooms, like a herd of sheep, as a whole exhibit herd mentality. Even in an online chatroom, you don’t often see someone ruffling feathers and say what they really want to say. This is probably because of the certain amount of people believing whatever he says without questioning the validity and quality of his comments. He has several strategies and according to him all of them have win rate over %70. However, he also comes up with new strategies as often as every month. He either comes up with new strategy or tweaks his existing strategies. According to him, the reason is that the market is always evolving and you need to constantly adapt yourself to the ever-changing market environment. What do you think? Does this sound like someone with an edge? And for someone who scalps for nickels and dimes, he claims to have the highest Sharpe Ratio that he has ever seen in the industry. I’m NOT making this up. He often utters remarks like “My Sharpe Ratio is one of the highest I’ve seen in my twenty-year trading career.”, “I want to create a of traders with a very high Sharpe Ratio. How can you achieve a high Sharpe Ratio when you scalp all the time? And let’s not even talk about commissions generated from frequent scalping. Who cares about commissions when you can be a scalper with high Sharpe Ratio? Now, I want to talk about something controversial about his most profitable strategy. Chatters According to him, he makes the most amount of money using what he calls “Chatters”. He admits he bets on this kind of trades heavily. His chatter trades are based on the “newsflow” of big funds making a move in certain stocks and piggybacking on the same trade before others catch on. No one knows how he exactly gets his “newsflow” and he doesn’t give a straight answer when asked. Maybe he pays a lot for this kind of information or maybe it’s given to him for free. Who knows? But it makes sense. The name of the room is Newsbeat Live. Without this the name wouldn’t be the same. This is probably the only real edge that he has and it’s understandable that he doesn’t want to reveal how he get this kind of newsflow and from where. By joining his trading room he’ll make a callout on these trades for you to take advantage of. In order to do this kind of trade, you have to be very quick on your trigger finger. Almost always the initial move is done within a couple of minutes, if not seconds. If you get in late, you find yourself a sucker buying at or near the top. Also, because you want to get in as soon as you hear his “chatter” announcements, he advised people to get in within 5 seconds of each chatter announcement and use market order to get in. He said that if he had a small account, he’d bet 100% on this kind of “high-octane” chatter trades and get in and get out fast for “easy” money. This was how chatter trades were done …Until one they when many people got burned badly. Back in September or October of 2019, a lot of people in the room lost a lot money because they market ordered call options contracts on a chatter trade. The spread on that trade was something like BID: 0.5 ASK: 5.00 few seconds after he announced it. I didn’t take that trade. No way, I’m going to buy something that has a spread like that. If you’ve been trading options you know that this kind of spread can happen. Many people that day in the room marketed-in on the trade, taking the offer at ASK. They found themselves buying at $5.0 per contract when someone probably bought the same contract at $0.40 or $0.50 just few seconds ago. Someone walked away with decent profits on that trade. This was the biggest trading chatroom fiasco I’ve ever seen. People in the room grieving and throwing numbers of how much they had just lost. 10K, 20K, 30K and even $60K. Could it be also that someone who lost more and didn’t want to talk about it because it’d hurt too much? And how embarrassing to talk about such a loss. I give credit to people who spoke up about it. People were obviously distressed and what did Mr. Mark Melnick do at this moment? Initially, he didn’t say much. But what he said he was going to walk away from the trading desk to clear his mind. It took a while for him to come back and he mentioned that it hurt him a lot that people lost a lot of money and encouraged people not to hesitate to contact him. I don’t think he ever said anything about that he made a mistake insinuating to load up on chatter trades. No apology since everyone who took the trade did it at their own risk. He advised people to reach out to their broker and do whatever it takes to get their trades annulled because the market makers in that trades were despicable crooks and evil. But let’s get one thing clear. Perhaps the cold hard truth. Since Mark is the one who announces chatter trades. he basically frontruns everyone who gets in on these trades after him. There were times when he doesn’t take his own chatter trades and lets the room have it. But when he does, it’s a guarantee win for him. He has some sycophantic followers in his trading room and these people are always hungry for chatter plays. I can imagine drooling over the idea of next chatter trades. It’s human to naturally seek the least path of resistance and this type of trade requires no skill but having fast trigger finger and a platform that allows fast execution. By taking his chatter trades, you are most likely to make money as long as you act fast to get in and get out. The thing is, you don’t know when it’s exactly the next chatter trade is going to happen. If you take a bathroom break, you just miss it. If you take a phone call or answer a door bell, you just missed it. So, it requires you to be glued to your monitor(s) if you want to make the most of your subscription. So, we went over Mark’s most profitable strategy. But wait we haven’t yet to talk about his overnight swing trades. Mark’s Swing Trades His overnight swing trades jokes. Yes, jokes. A lot of his overnight trades are done just before earnings announcements when implied volatility is at the highest. You’ve ever bought a call option just before earnings, predicted the right direction but only to find out that you still lost money next morning? This is because of the implied volatility crush post earnings. A lot of people new to options don’t know this and get taken advantage by veterans this way. I don’t know if Mark knows or not but I witnessed him buying options this way. I think he understand the concept of implied volatility but why he gets on such trades is a mystery. I haven’t exactly checked the result of all of his swing trades but I wouldn’t be surprised if people lost more money following his swing trades than anything in the room. Final Word Mark offers “free-consultation” on the phone for people who struggle in their trading. He said that he takes a lot of phone calls but often you’d get the feeling that he is distracted, unable to give an undivided attention for his consultation. “How would you like to get on a free consultation with a millionaire scalper who can take your trading to the next level?” Appealing isn’t it? But would you want to get on the phone with someone who is going to give a consultation, even if he or she is distracted? Oh, it’s a free consultation. Ok, why not? What do I got to lose? In his videos, you’d hear him saying that he cares for everyone in his trading room and considers them as part of his family. And he runs the trading room out of his good heart and intention more than making money. Besides he says that he makes more money from his trading than running the room. My suggestion is that you have a look and you’d be the judge. He does hold “open house” for his trading room from time to time. Also, I believe that if you try his trading room for the first time, you try it for a month for about $50. As for me, he’s just another front runner using his trading room to profit with a bad sense of humor and exaggeration that make you cringe.
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.
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