Hi guys, I have been using reddit for years in my personal life (not trading!) and wanted to give something back in an area where i am an expert. I worked at an investment bank for seven years and joined them as a graduate FX trader so have lots of professional experience, by which i mean I was trained and paid by a big institution to trade on their behalf. This is very different to being a full-time home trader, although that is not to discredit those guys, who can accumulate a good amount of experience/wisdom through self learning. When I get time I'm going to write a mid-length posts on each topic for you guys along the lines of how i was trained. I guess there would be 15-20 topics in total so about 50-60 posts. Feel free to comment or ask questions. The first topic is Risk Management and we'll cover it in three parts Part I
Why it matters
Using stops sensibly
Picking a clear level
Why it matters
The first rule of making money through trading is to ensure you do not lose money. Look at any serious hedge fund’s website and they’ll talk about their first priority being “preservation of investor capital.” You have to keep it before you grow it. Strangely, if you look at retail trading websites, for every one article on risk management there are probably fifty on trade selection. This is completely the wrong way around. The great news is that this stuff is pretty simple and process-driven. Anyone can learn and follow best practices. Seriously, avoiding mistakes is one of the most important things: there's not some holy grail system for finding winning trades, rather a routine and fairly boring set of processes that ensure that you are profitable, despite having plenty of losing trades alongside the winners.
Capital and position sizing
The first thing you have to know is how much capital you are working with. Let’s say you have $100,000 deposited. This is your maximum trading capital. Your trading capital is not the leveraged amount. It is the amount of money you have deposited and can withdraw or lose. Position sizing is what ensures that a losing streak does not take you out of the market. A rule of thumb is that one should risk no more than 2% of one’s account balance on an individual trade and no more than 8% of one’s account balance on a specific theme. We’ll look at why that’s a rule of thumb later. For now let’s just accept those numbers and look at examples. So we have $100,000 in our account. And we wish to buy EURUSD. We should therefore not be risking more than 2% which $2,000. We look at a technical chart and decide to leave a stop below the monthly low, which is 55 pips below market. We’ll come back to this in a bit. So what should our position size be? We go to the calculator page, select Position Size and enter our details. There are many such calculators online - just google "Pip calculator". https://preview.redd.it/y38zb666e5h51.jpg?width=1200&format=pjpg&auto=webp&s=26e4fe569dc5c1f43ce4c746230c49b138691d14 So the appropriate size is a buy position of 363,636 EURUSD. If it reaches our stop level we know we’ll lose precisely $2,000 or 2% of our capital. You should be using this calculator (or something similar) on every single trade so that you know your risk. Now imagine that we have similar bets on EURJPY and EURGBP, which have also broken above moving averages. Clearly this EUR-momentum is a theme. If it works all three bets are likely to pay off. But if it goes wrong we are likely to lose on all three at once. We are going to look at this concept of correlation in more detail later. The total amount of risk in our portfolio - if all of the trades on this EUR-momentum theme were to hit their stops - should not exceed $8,000 or 8% of total capital. This allows us to go big on themes we like without going bust when the theme does not work. As we’ll see later, many traders only win on 40-60% of trades. So you have to accept losing trades will be common and ensure you size trades so they cannot ruin you. Similarly, like poker players, we should risk more on trades we feel confident about and less on trades that seem less compelling. However, this should always be subject to overall position sizing constraints. For example before you put on each trade you might rate the strength of your conviction in the trade and allocate a position size accordingly: https://preview.redd.it/q2ea6rgae5h51.png?width=1200&format=png&auto=webp&s=4332cb8d0bbbc3d8db972c1f28e8189105393e5b To keep yourself disciplined you should try to ensure that no more than one in twenty trades are graded exceptional and allocated 5% of account balance risk. It really should be a rare moment when all the stars align for you. Notice that the nice thing about dealing in percentages is that it scales. Say you start out with $100,000 but end the year up 50% at $150,000. Now a 1% bet will risk $1,500 rather than $1,000. That makes sense as your capital has grown. It is extremely common for retail accounts to blow-up by making only 4-5 losing trades because they are leveraged at 50:1 and have taken on far too large a position, relative to their account balance. Consider that GBPUSD tends to move 1% each day. If you have an account balance of $10k then it would be crazy to take a position of $500k (50:1 leveraged). A 1% move on $500k is $5k. Two perfectly regular down days in a row — or a single day’s move of 2% — and you will receive a margin call from the broker, have the account closed out, and have lost all your money. Do not let this happen to you. Use position sizing discipline to protect yourself.
If you’re wondering - why “about 2%” per trade? - that’s a fair question. Why not 0.5% or 10% or any other number? The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round. This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The payout is $2 per $1 bet. Well, absolutely you should bet. The odds are in your favour. But if you have, say, $100 it is less obvious how much you should bet to avoid ruin. Say you bet $50, the odds that it could land on tails twice in a row are 16%. You could easily be out after the first two flips. Equally, betting $1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting $1 is likely too conservative. The Kelly Criterion is a formula that produces the long-run optimal bet size, given the odds. Applying the formula to forex trading looks like this: Position size % = Winning trade % - ( (1- Winning trade %) / Risk-reward ratio If you have recorded hundreds of trades in your journal - see next chapter - you can calculate what this outputs for you specifically. If you don't have hundreds of trades then let’s assume some realistic defaults of Winning trade % being 30% and Risk-reward ratio being 3. The 3 implies your TP is 3x the distance of your stop from entry e.g. 300 pips take profit and 100 pips stop loss. So that’s 0.3 - (1 - 0.3) / 3 = 6.6%. Hold on a second. 6.6% of your account probably feels like a LOT to risk per trade.This is the main observation people have on Kelly: whilst it may optimise the long-run results it doesn’t take into account the pain of drawdowns. It is better thought of as the rational maximum limit. You needn’t go right up to the limit! With a 30% winning trade ratio, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of nearly a quarter of your starting account balance. Could you really stomach that and put on the fifth trade, cool as ice? Most of us could not. Accordingly people tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account. Well, the simplest way is to divide the Kelly output by four. You have effectively hidden 75% of your account balance from Kelly and it is now optimised to avoid a total wipeout of just the 25% it can see. This gives 6.6% / 4 = 1.65%. Of course different trading approaches and different risk appetites will provide different optimal bet sizes but as a rule of thumb something between 1-2% is appropriate for the style and risk appetite of most retail traders. Incidentally be very wary of systems or traders who claim high winning trade % like 80%. Invariably these don’t pass a basic sense-check:
How many live trades have you done? Often they’ll have done only a handful of real trades and the rest are simulated backtests, which are overfitted. The model will soon die.
What is your risk-reward ratio on each trade? If you have a take profit $3 away and a stop loss $100 away, of course most trades will be winners. You will not be making money, however! In general most traders should trade smaller position sizes and less frequently than they do. If you are going to bias one way or the other, far better to start off too small.
How to use stop losses sensibly
Stop losses have a bad reputation amongst the retail community but are absolutely essential to risk management. No serious discretionary trader can operate without them. A stop loss is a resting order, left with the broker, to automatically close your position if it reaches a certain price. For a recap on the various order types visit this chapter. The valid concern with stop losses is that disreputable brokers look for a concentration of stops and then, when the market is close, whipsaw the price through the stop levels so that the clients ‘stop out’ and sell to the broker at a low rate before the market naturally comes back higher. This is referred to as ‘stop hunting’. This would be extremely immoral behaviour and the way to guard against it is to use a highly reputable top-tier broker in a well regulated region such as the UK. Why are stop losses so important? Well, there is no other way to manage risk with certainty. You should always have a pre-determined stop loss before you put on a trade. Not having one is a recipe for disaster: you will find yourself emotionally attached to the trade as it goes against you and it will be extremely hard to cut the loss. This is a well known behavioural bias that we’ll explore in a later chapter. Learning to take a loss and move on rationally is a key lesson for new traders. A common mistake is to think of the market as a personal nemesis. The market, of course, is totally impersonal; it doesn’t care whether you make money or not. Bruce Kovner, founder of the hedge fund Caxton Associates There is an old saying amongst bank traders which is “losers average losers”. It is tempting, having bought EURUSD and seeing it go lower, to buy more. Your average price will improve if you keep buying as it goes lower. If it was cheap before it must be a bargain now, right? Wrong. Where does that end? Always have a pre-determined cut-off point which limits your risk. A level where you know the reason for the trade was proved ‘wrong’ ... and stick to it strictly. If you trade using discretion, use stops.
Picking a clear level
Where you leave your stop loss is key. Typically traders will leave them at big technical levels such as recent highs or lows. For example if EURUSD is trading at 1.1250 and the recent month’s low is 1.1205 then leaving it just below at 1.1200 seems sensible. If you were going long, just below the double bottom support zone seems like a sensible area to leave a stop You want to give it a bit of breathing room as we know support zones often get challenged before the price rallies. This is because lots of traders identify the same zones. You won’t be the only one selling around 1.1200. The “weak hands” who leave their sell stop order at exactly the level are likely to get taken out as the market tests the support. Those who leave it ten or fifteen pips below the level have more breathing room and will survive a quick test of the level before a resumed run-up. Your timeframe and trading style clearly play a part. Here’s a candlestick chart (one candle is one day) for GBPUSD. https://preview.redd.it/moyngdy4f5h51.png?width=1200&format=png&auto=webp&s=91af88da00dd3a09e202880d8029b0ddf04fb802 If you are putting on a trend-following trade you expect to hold for weeks then you need to have a stop loss that can withstand the daily noise. Look at the downtrend on the chart. There were plenty of days in which the price rallied 60 pips or more during the wider downtrend. So having a really tight stop of, say, 25 pips that gets chopped up in noisy short-term moves is not going to work for this kind of trade. You need to use a wider stop and take a smaller position size, determined by the stop level. There are several tools you can use to help you estimate what is a safe distance and we’ll look at those in the next section. There are of course exceptions. For example, if you are doing range-break style trading you might have a really tight stop, set just below the previous range high. https://preview.redd.it/ygy0tko7f5h51.png?width=1200&format=png&auto=webp&s=34af49da61c911befdc0db26af66f6c313556c81 Clearly then where you set stops will depend on your trading style as well as your holding horizons and the volatility of each instrument. Here are some guidelines that can help:
Use technical analysis to pick important levels (support, resistance, previous high/lows, moving averages etc.) as these provide clear exit and entry points on a trade.
Ensure that the stop gives your trade enough room to breathe and reflects your timeframe and typical volatility of each pair. See next section.
Always pick your stop level first. Then use a calculator to determine the appropriate lot size for the position, based on the % of your account balance you wish to risk on the trade.
So far we have talked about price-based stops. There is another sort which is more of a fundamental stop, used alongside - not instead of - price stops. If either breaks you’re out. For example if you stop understanding why a product is going up or down and your fundamental thesis has been confirmed wrong, get out. For example, if you are long because you think the central bank is turning hawkish and AUDUSD is going to play catch up with rates … then you hear dovish noises from the central bank and the bond yields retrace lower and back in line with the currency - close your AUDUSD position. You already know your thesis was wrong. No need to give away more money to the market.
Coming up in part II
EDIT: part II here Letting stops breathe When to change a stop Entering and exiting winning positions Risk:reward ratios Risk-adjusted returns
Coming up in part III
Squeezes and other risks Market positioning Bet correlation Crap trades, timeouts and monthly limits *** Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
As PTI comes onto two years, I felt like making this post on account of seeing multiple people supporting PML-N for having an allegedly better economy for Pakistan, particularly with allegations present that PTI has done nothing for the economy. So here's a short list of some major achievements done by PTI in contrast to PML-N.
Stopping Pakistan from defaulting: The move to devalue the rupee was one done despite knowing the backlash that would be faced. Under Nawaz Sharif the rupee was artificially overvalued through loans and forex reserves, this meant Pakistan had no sustainable way for repaying those massive loans. Imran Khan on the other hand had to approach the IMF due to these overlaying maturing debts, lack of growth in exports under PMLN, decline in Foreign Direct Investment and an ever higher import bill. This was done at the cost of letting the rupee massively devalue against the dollar, however paved the path for economic stability as noted by the IMF.
Renewed focus on taxation: Easily the most controversial facet of the economic policy by PTI, but one that has shown merit and results. Overall, there has been a 40% increase in returns filers and a 17% revenue increase. This coupled with a massive austerity scheme, meant that the government has started an incline towards increasing it's revenues. While this hasn't been met with open arms, it presents a solution to the everpresent crisis that the Pakistan government has faced, in it's inability to increase it's revenues. Not only that, but the general taxation system was streamlined, making it easier for individuals to file taxes. Introductions of new apps and consolidating activities for the FBR were among the efforts as well. Moreover, businesses that were entitled to tax refunds are finally being granted them, under PMLN they were held onto so as to inflate collection numbers, however under PTI that has changed and it's not inflated. It is worth noting, that because of the covid-19 pandemic, the effect of the austerity schemes and feasibility have seriously dampened, and it's created a bigger problem for increasing revenue collection.
It is worth noting, that some may criticise the overall decrease in the account deficit to be a result of the decrease in imports, and the increase in worker remittances, however this was indeed a result of the overall economic impact from the covid-19 pandemic. And that general trends support the notion of exports increasing and the account deficit decreasing in the second quarter of 2019.
Tourism: The reforms and measures taken to facilitate tourism in Pakistan were evidently among the most successful — Pakistan went from being sidelined to being amongst the worlds top destinations to visit. There were multiple reasons for this, the removal of the mandatory NOC, the initiative for online visas for upto 175 countries alongside visa-on-arrival for 50 countries were among the facilitating measures taken for tourism.
Foreign Direct Investment: What can be appreciated is the general reception of Pakistan's economic outlook, where FDI climbed by upto 137% within this fiscal year, gathering upto nearly $2.1 billion. Yet, once again — the pandemic will undoubtedly cause most countries to rethink their economic policies for now, and the overall FDI might see a downward trend with regards to global decrease in FDI. Despite, the increases in FDI are welcomed, especially considering total foreign investment rose 380 percent to $2.375 billion in July-March FY2020. Yet the sustainability of this remains to be seen.
Dealing with covid: Despite all odds, Pakistan has somehow managed to deal well with the pandemic. Coming out relatively alright, in perspective of countries such as India, Mexico, Italy, Brazil etc. The factor that plays out, is that despite being incredibly vulnerable, the country managed to pull through and has markedly reduced the impact of the virus. With regards to the economy, taking a bold risk of abating a complete lockdown, whilst met with criticism was once again a factor that showed competency. Keeping in mind that 51 million Pakistanis lived below the poverty line, and the adverse effect it would have on the economy. Pakistan managed to come through the economic contraction with only a -0.38% growth. Although the full effects are still not abated or understood, what's commendable is the fact that Pakistan under PTI has kept itself from an even worse situation. Whilst managing to keep covid under relative control. Especially given increases in exports despite the pandemic in countries such as Qatar, Saudi Arabia, and Italy.
This is by no means a highly comprehensive list, just my opinion on some of the bigger achievements; saving the economy from defaulting, adopting tax reforms, tourism reforms, export reforms among them whilst managing covid and economic stability with relative success. There are of course a multitude of other factors, successfully avoiding a blacklist from the FATF, macroeconomic reforms, attempts to strengthen the working class; ehsaas programs, Naya Pakistan housing schemes alongside other relief efforts. These are measures in accordance with curtailing the effect of increasing taxation and attempts to abate the economic slowdown that came as a result of forcing an increase in government revenue. Alongside the focus on multiple new hydroelectric dams, industrial cities, reduction of the PM office staff from 552 to 298, 10 billion tree project and an overall renewed interest in renewable energy and green Pakistan. The list is comprehensive. Pakistan remains on a rocky path, it is not out of the woods yet. Covid-19 has seriously hampered the overall projections, and caused a worldwide economic contraction. Not only that, but there are criticisms that can be attributed to the government as well, as they are not without fault. However, the overall achievements of the government with regards to the economy do present hope for the long-term fiscal policy and development of Pakistan.
RBI & how its policies can start to affect the market
Disclaimer: This DD is to help start forming a market view as per RBI announcements. Also a gentle reminder that fundamentals play out over a longer time frame than intraday. The authors take no responsiblity for your yolos. With contributions by Asli Bakchodi, Bran OP & dragononweed! What is the RBI? RBI is the central bank of India. They are one of the key players who affect India’s economic trajectory. They control currency supply, banking rules and more. This means that it is not a bank in which retailers or corporates can open an account with. Instead they are a bank for bankers and the Government of India. Their functions can be broadly classified into 6. · Monetary authority · Financial supervisor for financial system · Issuer of currency · Manages Foreign exchange · Bankers bank · Banker to the government This DD will take a look at each of these functions. It will be followed by a list of rates the RBI sets, and how changes in them can affect the market. 1.Monetary Authority One of RBI’s functions is to achieve the goal of “Price Stability” in the economy. This essentially means achieving an inflation rate that is within a desired limit. A monetary policy committee (MPC) decides on the desired inflation rate and its limits through majority vote of its 6 members, in consultation with the GoI. The current inflation target for RBI is as follows Consumer Price Inflation (CPI): 4% Upper Limit: 6% Lower Limit: 2% An increase in CPI means less purchasing power. Generally speaking, if inflation is too high, the public starts cutting down on spending, leading to a negative impact on the markets. And vice versa. Lower inflation leads to more purchasing power, more spending, more investments leading to a positive impact on the market. 2.Financial Supervisor For Financial System A financial system consists of financial markets (Capital market, money market, forex market etc.), financial institutions (banks, stock exchanges, NBFC etc) & financial assets (currencies, bills, bonds etc) RBI supervises this entire system and lays down the rules and regulations for it. It can also use further ‘Selective Credit Controls’ to regulate banks. 3.Issues of currency The RBI is responsible for the printing of currency notes. RBI is free to print as much as it wants as long as the minimum reserve of Rs 200 Cr (Gold 112 Cr) is maintained. The RBI has total assets or a balance size sheet of Rs. 51 trillion (April 2020). (1 Trillion = 1 Lakh crore) India’s current reserves mean our increase in currency circulation is well managed. 4.Manages Foreign Exchange RBI regulates all of India’s foreign exchange transactions. It is the custodian of all of foreign currencies in India. It allows for the foreign exchange value of the rupee to be controlled. RBI also buy and sell rupees in the foreign exchange market at its discretion. In case of any currency movement, a country’s central bank can directly intervene to either push the currency up, as India has been doing, or to keep it artificially low, as the Chinese central bank does. To push up a currency, a central bank can sell dollars, which is the global reserve currency, or the currency against which all others are measured. To push down a currency, a central bank can buy dollars. The RBI deciding this depends on the import/export and financial health of the country. Generally a weaker rupee means imports are more expensive, but are favourable for exports. And a stronger rupee means imports are cheaper but are unfavourable for exports. A weaker rupee can make foreign investment more lucrative driving up FII. A stronger rupee can have an adverse effect of FII investing in markets. 5.Banker’s Bank Every bank has to maintain a certain amount of reserve with the RBI. A certain percentage of a bank’s liabilities (anywhere between 3-15% as decided by RBI) has to be maintained in this account. This is called the Cash Reserve Ratio. This is determined by the MPC during the monetary policy review (which happens every six weeks at present). It lends money from this reserve to other banks if they are short on cash, but generally, it is seen as a last resort move. Banks are encouraged to meet their shortfalls of cash from other resources. 6.Banker to the government RBI is the entity that carries out ALL monetary transactions on behalf of the Government. It holds custody of the cash balance of the Government, gives temporary loans to both central and state governments and manages the debt operations of the central Government, through instruments of debt and the interest rates associated with them - like bonds. The different rates set & managed by RBI - Repo rate The rate at which RBI is willing to lend to commercial banks is called as Repo Rate. Banks sometimes need money for emergency or to maintain the SLR and CRR (explained below). They borrow this from RBI but have to pay some interest on it. The interest that is to be paid on the amount to the RBI is called as Repo Rate. It does not function like a normal loan but acts like a forward contract. Banks have to provide collateral like government bonds, T-bills etc. Repo means Repurchase Option is the true meaning of Repo an agreement where the bank promises to repurchase these government securities after the repo period is over. As a tool to control inflation, RBI increases the Repo Rate making it more expensive for banks to borrow from the RBI with a view to restrict availability of money. Exact opposite stance shall be taken in case of deflationary environment. The change of repo rate is aimed to affect the flow of money in the economy. An increase in repo rate decreases the flow of money in the economy, while the decrease in repo rate increases the flow of money in the economy. RBI by changing these rates shows its stance to the economy at large whether they prioritize growth or inflation. - Reverse Repo Rate The rate at which the RBI is willing to borrow from the Banks is called as Reverse Repo Rate. If the RBI increases the reverse repo rate, it means that the RBI is willing to offer lucrative interest rate to banks to park their money with the RBI. Banks in this case agree to resell government securities after reverse repo period. Generally, an increase in reverse repo rate that banks will have a higher incentive to park their money with RBI. It decreases liquidity, affecting the market in a negative manner. Decrease in reverse repo rate increases liquidity affecting the market in a positive manner. Both the repo rate and reverse repo rate fall under the Liquidity Adjustment Facility tools for RBI. - Cash reserve ratio (CRR) Banks in India are required to deposit a specific percentage of their net demand and time liabilities (NDTL) in the form of CASH with the RBI. This minimum ratio (that is the part of the total deposits to be held as cash) is stipulated by the RBI and is known as the CRR or Cash Reserve Ratio. These reserves will not be in circulation at any point in time. For example, if a bank had a NDTL (like current Account, Savings Account and Fixed Deposits) of 100Cr and the CRR is at 3%, it would have to keep 3Cr as Cash reserve ratio to the RBI. This amount earns no interest. Currently it is at 3%. A lower cash ratio means banks can deposit just a lower amount and use the remaining money leading to higher liquidity. This translates to more money to invest which is seen as positive for the market. Inversely, a higher cash ratio equates to lower liquidity which translates to a negative market sentiment. Thus, the RBI uses the CRR to control excess money flow and regulate liquidity in the economy. - Statutory liquidity ratio (SLR) Banks in India have to keep a certain percentage of their net demand and time liabilities WITH THEMSELVES. And this can be in the form of liquid assets like gold and government securities, not just cash. A lot of banks keep them in government bonds as they give a decent interest. The current SLR ratio of 18.25%, which means that for every Rs.100 deposited in a bank, it has to invest Rs.18.50 in any of the asset classes approved by RBI. A low SLR means higher levels of loans to the private sector. This boosts investment and acts as a positive sentiment for the market. Conversely a high SLR means tighter levels of credit and can cause a negative effect on the market. Essentially, the RBI uses the SLR to control ease of credit in the economy. It also ensures that the banks maintain a certain level of funds to meet depositor’s demands instead of over liquidation. - Bank Rate Bank rate is a rate at which the Reserve Bank of India provides the loan to commercial banks without keeping any security. There is no agreement on repurchase that will be drawn up or agreed upon with no collateral as well. This is different from repo rate as loans taken with repo rate are taken on the basis of securities. Bank rate hence is higher than the repo rate. Currently the bank rate is 4.25%. Since bank rate is essentially a loan interest rate like repo rate, it affects the market in similar ways. - Marginal Cost of Funds based Lending Rate (MCLR) This is the minimum rate below which the banks are not allowed to lend. Raising this rate, makes loans more expensive, drying up liquidity, affecting the market in a negative way. Similarly, lower MCLR rates will bring in high liquidity, affecting the market in a positive way. MCLR is a varying lending rate instead of a single rate according to the kind of loans. Currently, the MCLR rate is between 6.65% - 7.15% - Marginal Standing facility Marginal Standing Facility is the interest rate at which a depository institution (generally banks) lends or borrows funds with another depository institution in the overnight market. Overnight market is the part of financial market which offers the shortest term loans. These loans have to be repaid the next day. MSF can be used by a bank after it exhausts its eligible security holdings for borrowing under other options like the Liquidity adjustment facilities. The MSF would be a penal rate for banks and the banks can borrow funds by pledging government securities within the limits of the statutory liquidity ratio. The current rate stands at 4.25%. The effect it has on the market is synonymous with the other lending rates such as repo rate & bank rate. - Loan to value ratio The loan-to-value (LTV) ratio is an assessment of lending risk that financial institutions and other lenders examine before approving a mortgage. Typically, loan assessments with high LTV ratios are considered higher risk loans. Basically, if a companies preferred form of collateral rises in value and leads the market (growing faster than the market), then the company will see the loans that it signed with higher LTV suddenly reduce (but the interest rate remains the same). Let’s consider an example of gold as a collateral. Consider a loan was approved with gold as collateral. The market price for gold is Rs 2000/g, and for each g, a loan of Rs 1500 was given. (The numbers are simplified for understanding). This would put LTV of the loan at 1500/2000 = 0.75. Since it is a substantial LTV, say the company priced the loan at 20% interest rate. Now the next year, the price of gold rose to Rs 3000/kg. This would mean that the LTV of the current loan has changed to 0.5 but the company is not obligated to change the interest rate. This means that even if the company sees a lot of defaults, it is fairly protected by the unexpected surge in the underlying asset. Moreover, since the underlying asset is more valuable, default rates for the loans goes down as people are more protective of the collateral they have placed. The same scenario for gold is happening right now and is the reason for gold backed loan providers like MUTHOOT to hit ATHs as gold is leading the economy right now. Also, these in these scenarios, it also enables companies to offer additional loan on same gold for those who are interested Instead of keeping the loan amount same most of the gold loan companies. Based on above, we can see that as RBI changes LTV for certain assets, we are in a position to identify potential institutions that could get a good Quarterly result and try to enter it early. Conclusion The above rates contain the ways in the Central Bank manages the monetary policy, growth and inflation in the country. Its impact on Stock market is often seen when these rates are changed, they act as triggers for the intraday positions on that day. But overall, the outlook is always maintained on how the RBI sees the country is doing, and knee jerk reactions are limited to intraday positions. The long term stance is always well within the limits of the outlook the big players in the market are expecting. The important thing to keep in mind is that the problems facing the economy needn’t be uni-dimensional. Problems with inflation, growth, liquidity, currency depreciation all can come together, for which the RBI will have to play a balancing role with all it powers to change these rates and the forex reserve. So the effect on the market needs to be given more thought than simply extrapolated as ‘rates go low, markets go up’. But understanding these individual effects of these rates allows you to start putting together the puzzle of how and where the market and the economy could go.
Former investment bank FX trader: Risk management part 3/3
Welcome to the third and final part of this chapter. Thank you all for the 100s of comments and upvotes - maybe this post will take us above 1,000 for this topic! Keep any feedback or questions coming in the replies below. Before you read this note, please start with Part I and then Part II so it hangs together and makes sense. Part III
Squeezes and other risks
Crap trades, timeouts and monthly limits
Squeezes and other risks
We are going to cover three common risks that traders face: events; squeezes, asymmetric bets.
Economic releases can cause large short-term volatility. The most famous is Non Farm Payrolls, which is the most widely watched measure of US employment levels and affects the price of many instruments.On an NFP announcement currencies like EURUSD might jump (or drop) 100 pips no problem. This is fine and there are trading strategies that one may employ around this but the key thing is to be aware of these releases.You can find economic calendars all over the internet - including on this site - and you need only check if there are any major releases each day or week. For example, if you are trading off some intraday chart and scalping a few pips here and there it would be highly sensible to go into a known data release flat as it is pure coin-toss and not the reason for your trading. It only takes five minutes each day to plan for the day ahead so do not get caught out by this. Many retail traders get stopped out on such events when price volatility is at its peak.
Short squeezes bring a lot of danger and perhaps some opportunity. The story of VW and Porsche is the best short squeeze ever. Throughout these articles we've used FX examples wherever possible but in this one instance the concept (which is also highly relevant in FX) is best illustrated with an historical lesson from a different asset class. A short squeeze is when a participant ends up in a short position they are forced to cover. Especially when the rest of the market knows that this participant can be bullied into stopping out at terrible levels, provided the market can briefly drive the price into their pain zone. There's a reason for the car, don't worry Hedge funds had been shorting VW stock. However the amount of VW stock available to buy in the open market was actually quite limited. The local government owned a chunk and Porsche itself had bought and locked away around 30%. Neither of these would sell to the hedge-funds so a good amount of the stock was un-buyable at any price. If you sell or short a stock you must be prepared to buy it back to go flat at some point. To cut a long story short, Porsche bought a lot of call options on VW stock. These options gave them the right to purchase VW stock from banks at slightly above market price. Eventually the banks who had sold these options realised there was no VW stock to go out and buy since the German government wouldn’t sell its allocation and Porsche wouldn’t either. If Porsche called in the options the banks were in trouble. Porsche called in the options which forced the shorts to buy stock - at whatever price they could get it. The price squeezed higher as those that were short got massively squeezed and stopped out. For one brief moment in 2008, VW was the world’s most valuable company. Shorts were burned hard. Incredible event Porsche apparently made $11.5 billion on the trade. The BBC described Porsche as “a hedge fund with a carmaker attached.” If this all seems exotic then know that the same thing happens in FX all the time. If everyone in the market is talking about a key level in EURUSD being 1.2050 then you can bet the market will try to push through 1.2050 just to take out any short stops at that level. Whether it then rallies higher or fails and trades back lower is a different matter entirely. This brings us on to the matter of crowded trades. We will look at positioning in more detail in the next section. Crowded trades are dangerous for PNL. If everyone believes EURUSD is going down and has already sold EURUSD then you run the risk of a short squeeze. For additional selling to take place you need a very good reason for people to add to their position whereas a move in the other direction could force mass buying to cover their shorts. A trading mentor when I worked at the investment bank once advised me: Always think about which move would cause the maximum people the maximum pain. That move is precisely what you should be watching out for at all times.
Also known as picking up pennies in front of a steamroller. This risk has caught out many a retail trader. Sometimes it is referred to as a "negative skew" strategy. Ideally what you are looking for is asymmetric risk trade set-ups: that is where the downside is clearly defined and smaller than the upside. What you want to avoid is the opposite. A famous example of this going wrong was the Swiss National Bank de-peg in 2012. The Swiss National Bank had said they would defend the price of EURCHF so that it did not go below 1.2. Many people believed it could never go below 1.2 due to this. Many retail traders therefore opted for a strategy that some describe as ‘picking up pennies in front of a steam-roller’. They would would buy EURCHF above the peg level and hope for a tiny rally of several pips before selling them back and keep doing this repeatedly. Often they were highly leveraged at 100:1 so that they could amplify the profit of the tiny 5-10 pip rally. Then this happened. Something that changed FX markets forever The SNB suddenly did the unthinkable. They stopped defending the price. CHF jumped and so EURCHF (the number of CHF per 1 EUR) dropped to new lows very fast. Clearly, this trade had horrific risk : reward asymmetry: you risked 30% to make 0.05%. Other strategies like naively selling options have the same result. You win a small amount of money each day and then spectacularly blow up at some point down the line.
We have talked about short squeezes. But how do you know what the market position is? And should you care? Let’s start with the first. You should definitely care. Let’s imagine the entire market is exceptionally long EURUSD and positioning reaches extreme levels. This makes EURUSD very vulnerable. To keep the price going higher EURUSD needs to attract fresh buy orders. If everyone is already long and has no room to add, what can incentivise people to keep buying? The news flow might be good. They may believe EURUSD goes higher. But they have already bought and have their maximum position on. On the flip side, if there’s an unexpected event and EURUSD gaps lower you will have the entire market trying to exit the position at the same time. Like a herd of cows running through a single doorway. Messy. We are going to look at this in more detail in a later chapter, where we discuss ‘carry’ trades. For now this TRYJPY chart might provide some idea of what a rush to the exits of a crowded position looks like. A carry trade position clear-out in action Knowing if the market is currently at extreme levels of long or short can therefore be helpful. The CFTC makes available a weekly report, which details the overall positions of speculative traders “Non Commercial Traders” in some of the major futures products. This includes futures tied to deliverable FX pairs such as EURUSD as well as products such as gold. The report is called “CFTC Commitments of Traders” ("COT"). This is a great benchmark. It is far more representative of the overall market than the proprietary ones offered by retail brokers as it covers a far larger cross-section of the institutional market. Generally market participants will not pay a lot of attention to commercial hedgers, which are also detailed in the report. This data is worth tracking but these folks are simply hedging real-world transactions rather than speculating so their activity is far less revealing and far more noisy. You can find the data online for free and download it directly here. Raw format is kinda hard to work with However, many websites will chart this for you free of charge and you may find it more convenient to look at it that way. Just google “CFTC positioning charts”. But you can easily get visualisations You can visually spot extreme positioning. It is extremely powerful. Bear in mind the reports come out Friday afternoon US time and the report is a snapshot up to the prior Tuesday. That means it is a lagged report - by the time it is released it is a few days out of date. For longer term trades where you hold positions for weeks this is of course still pretty helpful information. As well as the absolute level (is the speculative market net long or short) you can also use this to pick up on changes in positioning. For example if bad news comes out how much does the net short increase? If good news comes out, the market may remain net short but how much did they buy back? A lot of traders ask themselves “Does the market have this trade on?” The positioning data is a good method for answering this. It provides a good finger on the pulse of the wider market sentiment and activity. For example you might say: “There was lots of noise about the good employment numbers in the US. However, there wasn’t actually a lot of position change on the back of it. Maybe everyone who wants to buy already has. What would happen now if bad news came out?” In general traders will be wary of entering a crowded position because it will be hard to attract additional buyers or sellers and there could be an aggressive exit. If you want to enter a trade that is showing extreme levels of positioning you must think carefully about this dynamic.
Retail traders often drastically underestimate how correlated their bets are. Through bitter experience, I have learned that a mistake in position correlation is the root of some of the most serious problems in trading. If you have eight highly correlated positions, then you are really trading one position that is eight times as large. Bruce Kovner of hedge fund, Caxton Associates For example, if you are trading a bunch of pairs against the USD you will end up with a simply huge USD exposure. A single USD-trigger can ruin all your bets. Your ideal scenario — and it isn’t always possible — would be to have a highly diversified portfolio of bets that do not move in tandem. Look at this chart. Inverted USD index (DXY) is green. AUDUSD is orange. EURUSD is blue. Chart from TradingView So the whole thing is just one big USD trade! If you are long AUDUSD, long EURUSD, and short DXY you have three anti USD bets that are all likely to work or fail together. The more diversified your portfolio of bets are, the more risk you can take on each. There’s a really good video, explaining the benefits of diversification from Ray Dalio. A systematic fund with access to an investable universe of 10,000 instruments has more opportunity to make a better risk-adjusted return than a trader who only focuses on three symbols. Diversification really is the closest thing to a free lunch in finance. But let’s be pragmatic and realistic. Human retail traders don’t have capacity to run even one hundred bets at a time. More realistic would be an average of 2-3 trades on simultaneously. So what can be done? For example:
You might diversify across time horizons by having a mix of short-term and long-term trades.
You might diversify across asset classes - trading some FX but also crypto and equities.
You might diversify your trade generation approach so you are not relying on the same indicators or drivers on each trade.
You might diversify your exposure to the market regime by having some trades that assume a trend will continue (momentum) and some that assume we will be range-bound (carry).
And so on. Basically you want to scan your portfolio of trades and make sure you are not putting all your eggs in one basket. If some trades underperform others will perform - assuming the bets are not correlated - and that way you can ensure your overall portfolio takes less risk per unit of return. The key thing is to start thinking about a portfolio of bets and what each new trade offers to your existing portfolio of risk. Will it diversify or amplify a current exposure?
Crap trades, timeouts and monthly limits
One common mistake is to get bored and restless and put on crap trades. This just means trades in which you have low conviction. It is perfectly fine not to trade. If you feel like you do not understand the market at a particular point, simply choose not to trade. Flat is a position. Do not waste your bullets on rubbish trades. Only enter a trade when you have carefully considered it from all angles and feel good about the risk. This will make it far easier to hold onto the trade if it moves against you at any point. You actually believe in it. Equally, you need to set monthly limits. A standard limit might be a 10% account balance stop per month. At that point you close all your positions immediately and stop trading till next month. Be strict with yourself and walk away Let’s assume you started the year with $100k and made 5% in January so enter Feb with $105k balance. Your stop is therefore 10% of $105k or $10.5k . If your account balance dips to $94.5k ($105k-$10.5k) then you stop yourself out and don’t resume trading till March the first. Having monthly calendar breaks is nice for another reason. Say you made a load of money in January. You don’t want to start February feeling you are up 5% or it is too tempting to avoid trading all month and protect the existing win. Each month and each year should feel like a clean slate and an independent period. Everyone has trading slumps. It is perfectly normal. It will definitely happen to you at some stage. The trick is to take a break and refocus. Conserve your capital by not trading a lot whilst you are on a losing streak. This period will be much harder for you emotionally and you’ll end up making suboptimal decisions. An enforced break will help you see the bigger picture. Put in place a process before you start trading and then it’ll be easy to follow and will feel much less emotional. Remember: the market doesn’t care if you win or lose, it is nothing personal. When your head has cooled and you feel calm you return the next month and begin the task of building back your account balance.
That's a wrap on risk management
Thanks for taking time to read this three-part chapter on risk management. I hope you enjoyed it. Do comment in the replies if you have any questions or feedback. Remember: the most important part of trading is not making money. It is not losing money. Always start with that principle. I hope these three notes have provided some food for thought on how you might approach risk management and are of practical use to you when trading. Avoiding mistakes is not a sexy tagline but it is an effective and reliable way to improve results. Next up I will be writing about an exciting topic I think many traders should look at rather differently: news trading. Please follow on here to receive notifications and the broad outline is below. News Trading Part I
Why use the economic calendar
Reading the economic calendar
Knowing what's priced in
First order thinking vs second order thinking
News Trading 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 mysterious 'position trim' effect
Some key FX releases
*** Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
Former investment bank FX trader: news trading and second order thinking
Thanks to everyone who responded to the previous pieces on risk management. We ended up with nearly 2,000 upvotes and I'm delighted so many of you found it useful. This time we're going to focus on a new area: reacting to and trading around news and fundamental developments. A lot of people get this totally wrong and the main reason is that they trade the news at face value, without considering what the market had already priced in. If you've ever seen what you consider to be "good" or "better than forecast" news come out and yet been confused as the pair did nothing or moved in the opposite direction to expected, read on... We are going to do this in two parts. Part I
Why use an economic calendar
How to read the calendar
Knowing what's priced in
First order thinking vs second order thinking
Knowing how to use and benefit from the economic calendar is key for all traders - not just news traders. In this chapter we are going to take a practical look at how to use the economic calendar. We are also going to look at how to interpret news using second order thinking. The key concept is learning what has already been ‘priced in’ by the market so we can estimate how the market price might react to the new information.
Why use an economic calendar
The economic calendar contains all the scheduled economic releases for that day and week. Even if you purely trade based on technical analysis, you still must know what is in store. https://preview.redd.it/20xdiq6gq4k51.png?width=1200&format=png&auto=webp&s=6cd47186db1039be7df4d7ad6782de36da48f1db Why? Three main reasons. Firstly, releases can help provide direction. They create trends. For example if GBPUSD has been fluctuating aimlessly within a range and suddenly the Bank of England starts raising rates you better believe the British Pound will start to move. Big news events often start long-term trends which you can trade around. Secondly, a lot of the volatility occurs around these events. This is because these events give the market new information. Prior to a big scheduled release like the US Non Farm Payrolls you might find no one wants to take a big position. After it is released the market may move violently and potentially not just in a single direction - often prices may overshoot and come back down. Even without a trend this volatility provides lots of trading opportunities for the day trader. https://preview.redd.it/u17iwbhiq4k51.png?width=1200&format=png&auto=webp&s=98ea8ed154c9468cb62037668c38e7387f2435af Finally, these releases can change trends. Going into a huge release because of a technical indicator makes little sense. Everything could reverse and stop you out in a moment. You need to be aware of which events are likely to influence the positions you have on so you can decide whether to keep the positions or flatten exposure before the binary event for which you have no edge. Most traders will therefore ‘scan’ the calendar for the week ahead, noting what the big events are and when they will occur. Then you can focus on each day at a time.
Reading the economic calendar
Most calendars show events cut by trading day. Helpfully they adjust the time of each release to your own timezone. For example we can see that the Bank of Japan Interest Rate decision is happening at 4am local time for this particular London-based trader. https://preview.redd.it/lmx0q9qoq4k51.jpg?width=1200&format=pjpg&auto=webp&s=c6e9e1533b1ba236e51296de8db3be55dfa78ba1 Note that some events do not happen at a specific time. Think of a Central Banker’s speech for example - this can go on for an hour. It is not like an economic statistic that gets released at a precise time. Clicking the finger emoji will open up additional information on each event.
How do you define importance? Well, some events are always unimportant. With the greatest of respect to Italian farmers, nobody cares about mundane releases like Italian farm productivity figures. Other events always seem to be important. That means, markets consistently react to them and prices move. Interest rate decisions are an example of consistently high importance events. So the Medium and High can be thought of as guides to how much each event typically affects markets. They are not perfect guides, however, as different events are more or less important depending on the circumstances. For example, imagine the UK economy was undergoing a consumer-led recovery. The Central Bank has said it would raise interest rates (making GBPUSD move higher) if they feel the consumer is confident. Consumer confidence data would suddenly become an extremely important event. At other times, when the Central Bank has not said it is focused on the consumer, this release might be near irrelevant.
Knowing what's priced in
Next to each piece of economic data you can normally see three figures. Actual, Forecast, and Previous.
Actual refers to the number as it is released.
Forecast refers to the consensus estimate from analysts.
Previous is what it was last time.
We are going to look at this in a bit more detail later but what you care about is when numbers are better or worse than expected. Whether a number is ‘good’ or ‘bad’ really does not matter much. Yes, really. Once you understand that markets move based on the news vs expectations, you will be less confused by price action around events This is a common misunderstanding. Say everyone is expecting ‘great’ economic data and it comes out as ‘good’. Does the price go up? You might think it should. After all, the economic data was good. However, everyone expected it to be great and it was just … good. The great release was ‘priced in’ by the market already. Most likely the price will be disappointed and go down. By priced in we simply mean that the market expected it and already bought or sold. The information was already in the price before the announcement. Incidentally the official forecasts can be pretty stale and might not accurately capture what active traders in the market expect. See the following example.
An example of pricing in
For example, let’s say the market is focused on the number of Tesla deliveries. Analysts think it’ll be 100,000 this quarter. But Elon Musk tweets something that hints he’s really, really, really looking forward to the analyst call. Tesla’s price ticks higher after the tweet as traders put on positions, reflecting the sentiment that Tesla is likely to massively beat the 100,000. (This example is not a real one - it just serves to illustrate the concept.) Tesla deliveries are up hugely vs last quarter ... but they are disappointing vs market expectations ... what do you think will happen to the stock? On the day it turns out Tesla hit 101,000. A better than the officially forecasted result - sure - but only marginally. Way below what readers of Musk's twitter account might have thought. Disappointed traders may sell their longs and close out the positions. The stock might go down on ‘good’ results because the market had priced in something even better. (This example is not a real one - it just serves to illustrate the concept.)
We know that interest rates heavily affect currency prices. For major interest rate decisions there’s a great tool on the CME’s website that you can use. See the link for a demo This gives you a % probability of each interest rate level, implied by traded prices in the bond futures market. For example, in the case above the market thinks there’s a 20% chance the Fed will cut rates to 75-100bp. Obviously this is far more accurate than analyst estimates because it uses actual bond prices where market participants are directly taking risk and placing bets. It basically looks at what interest rate traders are willing to lend at just before/after the date of the central bank meeting to imply the odds that the market ascribes to a change on that date. Always try to estimate what the market has priced in. That way you have some context for whether the release really was better or worse than expected.
Second order thinking
You have to know what the market expects to try and guess how it’ll react. This is referred to by Howard Marks of Oaktree as second-level thinking. His explanation is so clear I am going to quote extensively. It really is hard to improve on this clarity of thought: First-level thinking is simplistic and superficial, and just about everyone can do it (a bad sign for anything involving an attempt at superiority). All the first-level thinker needs is an opinion about the future, as in “The outlook for the company is favorable, meaning the stock will go up.” Second-level thinking is deep, complex and convoluted. Howard Marks He explains first-level thinking: The first-level thinker simply looks for the highest quality company, the best product, the fastest earnings growth or the lowest p/e ratio. He’s ignorant of the very existence of a second level at which to think, and of the need to pursue it. Howard Marks The above describes the guy who sees a 101,000 result and buys Tesla stock because - hey, this beat expectations. Marks goes on to describe second-level thinking: The second-level thinker goes through a much more complex process when thinking about buying an asset. Is it good? Do others think it’s as good as I think it is? Is it really as good as I think it is? Is it as good as others think it is? Is it as good as others think others think it is? How will it change? How do others think it will change? How is it priced given: its current condition; how do I think its conditions will change; how others think it will change; and how others think others think it will change? And that’s just the beginning. No, this isn’t easy. Howard Marks In this version of events you are always thinking about the market’s response to Tesla results. What do you think they’ll announce? What has the market priced in? Is Musk reliable? Are the people who bought because of his tweet likely to hold on if he disappoints or exit immediately? If it goes up at which price will they take profit? How big a number is now considered ‘wow’ by the market? As Marks says: not easy. However, you need to start getting into the habit of thinking like this if you want to beat the market. You can make gameplans in advance for various scenarios. Here are some examples from Marks to illustrate the difference between first order and second order thinking. Some further examples Trying to react fast to headlines is impossible in today’s market of ultra fast computers. You will never win on speed. Therefore you have to out-think the average participant.
Coming up in part II
Now that we have a basic understanding of concepts such as expectations and what the market has priced in, we can look at some interesting trading techniques and tools. 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
Hope you enjoyed this note. As always, please reply with any questions/feedback - it is fun to hear from you. *** Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
I have a habit of backtesting every strategy I find as long as it makes sense. I find it fun, and even if the strategy ends up being underperforming, it gives me a good excuse to gain valuable chart experience that would normally take years to gather. After I backtest something, I compare it to my current methodology, and usually conclude that mine is better either because it has a better performance or the new method requires too much time to manage (Spoiler: until now, I like this better) During the last two days, I have worked on backtesting ParallaxFx strategy, as it seemed promising and it seemed to fit my personality (a lazy fuck who will happily halve his yearly return if it means he can spend 10% less time in front of the screens). My backtesting is preliminary, and I didn't delve very deep in the data gathering. I usually track all sort of stuff, but for this first pass, I sticked to the main indicators of performance over a restricted sample size of markets. Before I share my results with you, I always feel the need to make a preface that I know most people will ignore.
I am words on your screen. You cannot trust me. I could have edited this or literally just typed random numbers on a spreadsheet. Do your own research if you want to trust my conclusion.
Even if you trust me, you need to do backtesting for yourself. The goal of backtesting isn't simply to figure out whether a strategy has an edge: it's a way to get used to how the market flows (valuable experience you will bring on to any other strategy) and how the strategy behaves. You need to see it with your own eyes to allow your subconscious mind to be at ease when it comes time to trade it live: the only way to truly trust your strategy during a period of drawdown, is to have seen it work over hundreds of trades in the past.
Strategy I am not going to go into the strategy in this thread. If you haven't read the series of threads by the guy who shared it, go here. As suggested by my mentioned personality type, I went with the passive management options of ParallaxFx's strategy. After a valid setup forms, I place two orders of half my risk. I add or remove 1 pip from each level to account for spread.
The first at the 23.6 retracement.
The second at the 38.2 retracement.
Both orders have a stop loss at the 78.6 retracement.
Both orders have the same target at the -100.0 extension.
If price moves to the -38.2 extension, I delete any unfilled orders.
I do not scale out, I do not move to breakeven, I place my orders and walk away.
Sample I tested this strategy over the seven major currency pairs: AUDUSD, USDCAD, NZDUSD, GBPUSD, USDJPY, EURUSD, USDCHF. The time period started on January 1th 2018 and ended on July 1th 2020, so a 2.5 years backtest. I tested over the D1 timeframe, and I plan on testing other timeframes. My "protocol" for backtesting is that, if I like what I see during this phase, I will move to the second phase where I'll backtest over 5 years and 28 currency pairs. Units of measure I used R multiples to track my performance. If you don't know what they are, I'm too sleepy to explain right now. This article explains what they are. The gist is that the results you'll see do not take into consideration compounding and they normalize volatility (something pips don't do, and why pips are in my opinion a terrible unit of measure for performance) as well as percentage risk (you can attach variable risk profiles on your R values to optimize position sizing in order to maximize returns and minimize drawdowns, but I won't get into that). Results I am not going to link the spreadsheet directly, because it is in my GDrive folder and that would allow you to see my personal information. I will attach screenshots of both the results and the list of trades. In the latter, I have included the day of entry for each trade, so if you're up to the task, you can cross-reference all the trades I have placed to make sure I am not making things up. Overall results: R Curve and Segmented performance. List of trades: 1, 2, 3, 4, 5, 6, 7. Something to note: I treated every half position as an individual trade for the sake of simplicity. It should not mess with the results, but it simply means you will see huge streaks of wins and losses. This does not matter because I'm half risk in each of them, so a winstreak of 6 trades is just a winstreak of 3 trades. For reference:
Profit Factor: 2.34
Return: 100.47 R
Strike rate: 48.28%
Average win: 2.51 R
Average loss: -1.00 R
Thoughts Nice. I'll keep testing. As of now it is vastly better than my current strategy.
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
Someone posted on here a few days ago asking about forex and forex trading in Kenya, I have gone through the responses and clearly, most people don’t have an idea. It is 3am in the morning and am in a good mood so let me make this post. This will be a comprehensive and lengthy post so grab a pen and paper and sit down. We’ll be here a while. FIRST OF ALL, who am I..? I am a forex trader, in Nairobi, Kenya..i have been actively involved in forex since I found out about it in Feb 2016 when I somehow ended up in a wealth creation seminar (lol) in pride inn Westlands, the one close to Mpaka Rd. Luckily for me, it was not one of those AIM global meetings or I’d be on Facebook selling God knows what those guys sell. I did not take it seriously till August of the same year and I have been active ever since. I don’t teach, mentor or sell a course or signals, I trade my own money. I am also posting from a throwaway account because I don’t want KRA on my ass. What the fuck is forex and forex trading. In simple plain English, forex is like the stock market but for currencies. Stock Market = Shares, forex = currencies. If you want more in-depth explanation, google is your friend. These currencies are pegged on specific countries, united states- dollar, UK- pound, euro zone- euro, Switzerland- Swiss franc, Kenya- Kenya shilling.. you get the point. Now, there are specific events and happenings between these economies that affect the movement and values of the currencies, driving their value (purchasing power up and down). Forex trading exploits these movements to make money. When the value is going up, we buy and vice versa (down –sell) Is forex trading illegal in Kenya? Is it a scam? Illegal, no. scam, no. All the banks in the world do it (KCB made about 4 billion from trading forex in 2019) Have there been scams involving forex in Kenya? Yes. Here is one that happened recently. This one is the most infamous one yet. Best believe that this is not the end of these type of scams because the stupidity, greed and gullibility of human beings is unfathomable. However, by the end of this post, I hope you won’t fall for such silliness. What next how do I make it work..? Am glad you asked. Generally, there are two ways to go about it. One, you teach yourself. This is the equivalent of stealing our dad’s car and hoping that the pedal you hit is the brake and not the accelerator. It is the route I took, it is the most rewarding and a huge ego boost when you finally make it on your own. Typically, this involves scouring the internet for hours upon hours going down rabbit holes, thinking you have made it telling all your friends how you will be a millionaire then losing all your money. Some people do not have the stomach for that. The second route is more practical, structured and smarter. First Learn the basics. There is a free online forex course at www.babypips.com/learn/forex this is merely an introductory course. Basically it is learning the parts of a car before they let you inside the car. Second, start building your strategy. By the time you are done with the babypips, you will have a feel of what the forex market is, what interests you, etc. Tip..Babypips has a lot of garbage. It is good for introductory purposes but not good for much else, pick whatever stick to you or jumps at you the first time. Nonsense like indicators should be ignored. The next step is now the most important. Developing the skill and building your strategy. As a beginner, you want to exhaust your naivety before jumping into the more advanced stuff. Eg can you identify a trend, what is a pair, what is position sizing, what is metatrader 4 and how to operate it, what news is good for a currency, when can I trade, what are the different trading sessions, what is technical analysis, what is market sentiment, what are bullish conditions what is emotion management, how does my psychology affect my trading (more on this later) an I a swing, scalper or day trader etc Mentors and forex courses.. you have probably seen people advertising how they can teach and mentor you on how to trade forex and charging so much money for it. Somehow it seems that these people are focused on the teaching than the trading. Weird, right..? Truth is trading is hard, teaching not quite. A common saying in the industry is “Those who can’t trade, teach” you want to avoid all these gurus on Facebook and Instagram, some are legit but most are not. Sifting the wheat from the chaff is hard but I did that for you. The info is available online on YouTube, telegram channels etc. am not saying not to spend money on a course, if you find a mentor whose style resonates with you and the course is reasonably priced, please, go ahead and buy..it will cut your learning curve in half. People are different. What worked for me might not work for you. Here are some nice YouTube channels to watch. These guys are legit..
After a short period of time, you will be able to sniff out bs teachers with relative ease. You will also discover some of your own and expand the list. Two tips, start with the oldest videos first and whichever of these resonates with you, stick with till the wheels fall off. How long will it take until things start making sense Give yourself time to grow and learn. This is all new to you and you are allowed to make mistakes, to fail and discover yourself. Realistically, depending on the effort you put in, you will not start seeing results until after 6 months. Could take longeshorter so there is no guarantee. Social media, Mentality, Psychology and Books Online, forex trading might not have the best reputation online because it takes hard work and scammers and gurus give it a bad name. However, try to not get sucked into the Instagram trader lifestyle as it is nowhere close to what the reality is. You will not make millions tomorrow or the day after, you might never even make it in this market. But that is the reality of life. Nothing is promised, nothing is guaranteed. Your mentality, beliefs and ego will be challenged in this market. You will learn things that will make you blood boil, you will ask yourself daily, how is this possible, why don’t they teach this in school..bla bla bla..it will be hard but growth is painful, if it wasn’t we’d all be billionaires. Take a break, take a walk, drink a glass of whatever you like or roll one..detox. Chill with your girl (or man) Gradually you will develop mental toughness that will set you up for life. Personally, I sorta ditched religion and picked up stoicism. Whatever works for you. Psychology, this is unfortunately one of the most neglected aspects of your personal development in this journey. Do you believe in yourself? Can you stand by your convictions when everyone is against you? Can you get up every day uncertain of the future? There will be moments where you will question yourself, am I even doing the right thing? the right way? It is normal and essential for your growth. People who played competitive sports have a natural advantage here. Remember the game is first won in your head then on the pitch. Books: ironically, books that helped me the most were the mindset books, Think and grow rich, trading for a living, 4 hour work week, the monk who sold his Ferrari..just google mindset and psychology books, most trading books are garbage. Watch and listen to people who have made it in the investing business. Ray Dalio, warren, Bill Ackman and Carl Icahn. This is turning out to be lengthier than I anticipated so I’ll try to be brief for the remaining parts. Brokers You will need to open up an account with a broker. Get a broker who is regulated. Australian ones (IC Market and Pepperstone) are both legit, reliable and regulated. Do your research. I’d avoid local ones because I’ve heard stories of wide spreads and liquidity problems. International brokers have never failed me. There are plenty brokers, there is no one size fits all recommendation. If it ain’t broke..don’t fix it. Money transfer. All brokers accept wire transfers, you might need to call your bank to authorize that, avoid Equity bank. Stanchart and Stanbic are alright. Large withdrawals $10k+ you will have to call them prior. Get Skrill and Neteller if you don’t like banks like me, set up a Bitcoin wallet for faster withdrawals, (Payoneer and Paypal are accepted by some brokers, just check with them.) How much money can I make..? I hate this question because people have perceived ceilings of income in their minds, eg 1 million ksh is too much to make per month or 10,000ksh is too little. Instead, work backwards. What % return did I make this month/ on this trade. Safaricom made 19.5% last year, if you make 20% you have outperformed them. If you reach of consistency where you can make x% per month on whatever money you have, then there are no limits to how much you can make. How much money do I need to start with..? Zero. You have all the resources above, go forth. There are brokers who provide free bonuses and withdraw-able profits. However, to make a fulltime income you will need some serious cash. Generally, 50,000 kes. You can start lower or higher but if you need say 20k to live comfortably and that is a 10% return per month, then you can do the math on how big your account should be. Of course things like compound interest come into play but that is dependent on your skill level. I have seen people do spectacular things with very little funds. Taxes..? Talk to a lawyer or an accountant. I am neither. Family? Friends? Unfortunately, people will not understand why you spend hundreds of hours watching strangers on the internet so it is best to keep it from them. Eventually you will make it work and they will come to your corner talking about how they always knew you’d make it. The journey will be lonely, make some trading buddies along the way. You’d be surprised at how easy it is when people are united by their circumstances (and stupidity) I have guys who are my bros from South Africa and Lebanon who I have never met but we came up together and are now homies. Join forums, ask questions and grow. That is the only way to learn. Ideally, a group of 5-10 friends committed to learning and growth is the best model. Pushing each other to grow and discovering together. Forex is real and you can do amazing things with it. It is not a get rich quick scheme. If you want a quick guaranteed income, get a job. And now it is 5am, fuck. This is oversimplified and leaves out many many aspects. Happy to answer any questions.
Everything You Always Wanted To Know About Swaps* (*But Were Afraid To Ask)
Hello, dummies It's your old pal, Fuzzy. As I'm sure you've all noticed, a lot of the stuff that gets posted here is - to put it delicately - fucking ridiculous. More backwards-ass shit gets posted to wallstreetbets than you'd see on a Westboro Baptist community message board. I mean, I had a look at the daily thread yesterday and..... yeesh. I know, I know. We all make like the divine Laura Dern circa 1992 on the daily and stick our hands deep into this steaming heap of shit to find the nuggets of valuable and/or hilarious information within (thanks for reading, BTW). I agree. I love it just the way it is too. That's what makes WSB great. What I'm getting at is that a lot of the stuff that gets posted here - notwithstanding it being funny or interesting - is just... wrong. Like, fucking your cousin wrong. And to be clear, I mean the fucking your *first* cousin kinda wrong, before my Southerners in the back get all het up (simmer down, Billy Ray - I know Mabel's twice removed on your grand-sister's side). Truly, I try to let it slide. Idomybit to try and put you on the right path. Most of the time, I sleep easy no matter how badly I've seen someone explain what a bank liquidity crisis is. But out of all of those tens of thousands of misguided, autistic attempts at understanding the world of high finance, one thing gets so consistently - so *emphatically* - fucked up and misunderstood by you retards that last night I felt obligated at the end of a long work day to pull together this edition of Finance with Fuzzy just for you. It's so serious I'm not even going to make a u/pokimane gag. Have you guessed what it is yet? Here's a clue. It's in the title of the post. That's right, friends. Today in the neighborhood we're going to talk all about hedging in financial markets - spots, swaps, collars, forwards, CDS, synthetic CDOs, all that fun shit. Don't worry; I'm going to explain what all the scary words mean and how they impact your OTM RH positions along the way. We're going to break it down like this. (1) "What's a hedge, Fuzzy?" (2) Common Hedging Strategies and (3) All About ISDAs and Credit Default Swaps. Before we begin. For the nerds and JV traders in the back (and anyone else who needs to hear this up front) - I am simplifying these descriptions for the purposes of this post. I am also obviously not going to try and cover every exotic form of hedge under the sun or give a detailed summation of what caused the financial crisis. If you are interested in something specific ask a question, but don't try and impress me with your Investopedia skills or technical points I didn't cover; I will just be forced to flex my years of IRL experience on you in the comments and you'll look like a big dummy. TL;DR? Fuck you. There is no TL;DR. You've come this far already. What's a few more paragraphs? Put down the Cheetos and try to concentrate for the next 5-7 minutes. You'll learn something, and I promise I'll be gentle. Ready? Let's get started. 1.The Tao of Risk: Hedging as a Way of Life The simplest way to characterize what a hedge 'is' is to imagine every action having a binary outcome. One is bad, one is good. Red lines, green lines; uppie, downie. With me so far? Good. A 'hedge' is simply the employment of a strategy to mitigate the effect of your action having the wrong binary outcome. You wanted X, but you got Z! Frowny face. A hedge strategy introduces a third outcome. If you hedged against the possibility of Z happening, then you can wind up with Y instead. Not as good as X, but not as bad as Z. The technical definition I like to give my idiot juniors is as follows: Utilization of a defensive strategy to mitigate risk, at a fraction of the cost to capital of the risk itself. Congratulations. You just finished Hedging 101. "But Fuzzy, that's easy! I just sold a naked call against my 95% OTM put! I'm adequately hedged!". Spoiler alert: you're not (although good work on executing a collar, which I describe below). What I'm talking about here is what would be referred to as a 'perfect hedge'; a binary outcome where downside is totally mitigated by a risk management strategy. That's not how it works IRL. Pay attention; this is the tricky part. You can't take a single position and conclude that you're adequately hedged because risks are fluid, not static. So you need to constantly adjust your position in order to maximize the value of the hedge and insure your position. You also need to consider exposure to more than one category of risk. There are micro (specific exposure) risks, and macro (trend exposure) risks, and both need to factor into the hedge calculus. That's why, in the real world, the value of hedging depends entirely on the design of the hedging strategy itself. Here, when we say "value" of the hedge, we're not talking about cash money - we're talking about the intrinsic value of the hedge relative to the the risk profile of your underlying exposure. To achieve this, people hedge dynamically. In wallstreetbets terms, this means that as the value of your position changes, you need to change your hedges too. The idea is to efficiently and continuously distribute and rebalance risk across different states and periods, taking value from states in which the marginal cost of the hedge is low and putting it back into states where marginal cost of the hedge is high, until the shadow value of your underlying exposure is equalized across your positions. The punchline, I guess, is that one static position is a hedge in the same way that the finger paintings you make for your wife's boyfriend are art - it's technically correct, but you're only playing yourself by believing it. Anyway. Obviously doing this as a small potatoes trader is hard but it's worth taking into account. Enough basic shit. So how does this work in markets? 2. A Hedging Taxonomy The best place to start here is a practical question. What does a business need to hedge against? Think about the specific risk that an individual business faces. These are legion, so I'm just going to list a few of the key ones that apply to most corporates. (1) You have commodity risk for the shit you buy or the shit you use. (2) You have currency risk for the money you borrow. (3) You have rate risk on the debt you carry. (4) You have offtake risk for the shit you sell. Complicated, right? To help address the many and varied ways that shit can go wrong in a sophisticated market, smart operators like yours truly have devised a whole bundle of different instruments which can help you manage the risk. I might write about some of the more complicated ones in a later post if people are interested (CDO/CLOs, strip/stack hedges and bond swaps with option toggles come to mind) but let's stick to the basics for now. (i) Swaps A swap is one of the most common forms of hedge instrument, and they're used by pretty much everyone that can afford them. The language is complicated but the concept isn't, so pay attention and you'll be fine. This is the most important part of this section so it'll be the longest one. Swaps are derivative contracts with two counterparties (before you ask, you can't trade 'em on an exchange - they're OTC instruments only). They're used to exchange one cash flow for another cash flow of equal expected value; doing this allows you to take speculative positions on certain financial prices or to alter the cash flows of existing assets or liabilities within a business. "Wait, Fuzz; slow down! What do you mean sets of cash flows?". Fear not, little autist. Ol' Fuzz has you covered. The cash flows I'm talking about are referred to in swap-land as 'legs'. One leg is fixed - a set payment that's the same every time it gets paid - and the other is variable - it fluctuates (typically indexed off the price of the underlying risk that you are speculating on / protecting against). You set it up at the start so that they're notionally equal and the two legs net off; so at open, the swap is a zero NPV instrument. Here's where the fun starts. If the price that you based the variable leg of the swap on changes, the value of the swap will shift; the party on the wrong side of the move ponies up via the variable payment. It's a zero sum game. I'll give you an example using the most vanilla swap around; an interest rate trade. Here's how it works. You borrow money from a bank, and they charge you a rate of interest. You lock the rate up front, because you're smart like that. But then - quelle surprise! - the rate gets better after you borrow. Now you're bagholding to the tune of, I don't know, 5 bps. Doesn't sound like much but on a billion dollar loan that's a lot of money (a classic example of the kind of 'small, deep hole' that's terrible for profits). Now, if you had a swap contract on the rate before you entered the trade, you're set; if the rate goes down, you get a payment under the swap. If it goes up, whatever payment you're making to the bank is netted off by the fact that you're borrowing at a sub-market rate. Win-win! Or, at least, Lose Less / Lose Less. That's the name of the game in hedging. There are many different kinds of swaps, some of which are pretty exotic; but they're all different variations on the same theme. If your business has exposure to something which fluctuates in price, you trade swaps to hedge against the fluctuation. The valuation of swaps is also super interesting but I guarantee you that 99% of you won't understand it so I'm not going to try and explain it here although I encourage you to google it if you're interested. Because they're OTC, none of them are filed publicly. Someeeeeetimes you see an ISDA (dsicussed below) but the confirms themselves (the individual swaps) are not filed. You can usually read about the hedging strategy in a 10-K, though. For what it's worth, most modern credit agreements ban speculative hedging. Top tip: This is occasionally something worth checking in credit agreements when you invest in businesses that are debt issuers - being able to do this increases the risk profile significantly and is particularly important in times of economic volatility (ctrl+f "non-speculative" in the credit agreement to be sure). (ii) Forwards A forward is a contract made today for the future delivery of an asset at a pre-agreed price. That's it. "But Fuzzy! That sounds just like a futures contract!". I know. Confusing, right? Just like a futures trade, forwards are generally used in commodity or forex land to protect against price fluctuations. The differences between forwards and futures are small but significant. I'm not going to go into super boring detail because I don't think many of you are commodities traders but it is still an important thing to understand even if you're just an RH jockey, so stick with me. Just like swaps, forwards are OTC contracts - they're not publicly traded. This is distinct from futures, which are traded on exchanges (see The Ballad Of Big Dick Vick for some more color on this). In a forward, no money changes hands until the maturity date of the contract when delivery and receipt are carried out; price and quantity are locked in from day 1. As you now know having read about BDV, futures are marked to market daily, and normally people close them out with synthetic settlement using an inverse position. They're also liquid, and that makes them easier to unwind or close out in case shit goes sideways. People use forwards when they absolutely have to get rid of the thing they made (or take delivery of the thing they need). If you're a miner, or a farmer, you use this shit to make sure that at the end of the production cycle, you can get rid of the shit you made (and you won't get fucked by someone taking cash settlement over delivery). If you're a buyer, you use them to guarantee that you'll get whatever the shit is that you'll need at a price agreed in advance. Because they're OTC, you can also exactly tailor them to the requirements of your particular circumstances. These contracts are incredibly byzantine (and there are even crazier synthetic forwards you can see in money markets for the true degenerate fund managers). In my experience, only Texan oilfield magnates, commodities traders, and the weirdo forex crowd fuck with them. I (i) do not own a 10 gallon hat or a novelty size belt buckle (ii) do not wake up in the middle of the night freaking out about the price of pork fat and (iii) love greenbacks too much to care about other countries' monopoly money, so I don't fuck with them. (iii) Collars No, not the kind your wife is encouraging you to wear try out to 'spice things up' in the bedroom during quarantine. Collars are actually the hedging strategy most applicable to WSB. Collars deal with options! Hooray! To execute a basic collar (also called a wrapper by tea-drinking Brits and people from the Antipodes), you buy an out of the money put while simultaneously writing a covered call on the same equity. The put protects your position against price drops and writing the call produces income that offsets the put premium. Doing this limits your tendies (you can only profit up to the strike price of the call) but also writes down your risk. If you screen large volume trades with a VOL/OI of more than 3 or 4x (and they're not bullshit biotech stocks), you can sometimes see these being constructed in real time as hedge funds protect themselves on their shorts. (3) All About ISDAs, CDS and Synthetic CDOs You may have heard about the mythical ISDA. Much like an indenture (discussed in my post on $F), it's a magic legal machine that lets you build swaps via trade confirms with a willing counterparty. They are very complicated legal documents and you need to be a true expert to fuck with them. Fortunately, I am, so I do. They're made of two parts; a Master (which is a form agreement that's always the same) and a Schedule (which amends the Master to include your specific terms). They are also the engine behind just about every major credit crunch of the last 10+ years. First - a brief explainer. An ISDA is a not in and of itself a hedge - it's an umbrella contract that governs the terms of your swaps, which you use to construct your hedge position. You can trade commodities, forex, rates, whatever, all under the same ISDA. Let me explain. Remember when we talked about swaps? Right. So. You can trade swaps on just about anything. In the late 90s and early 2000s, people had the smart idea of using other people's debt and or credit ratings as the variable leg of swap documentation. These are called credit default swaps. I was actually starting out at a bank during this time and, I gotta tell you, the only thing I can compare people's enthusiasm for this shit to was that moment in your early teens when you discover jerking off. Except, unlike your bathroom bound shame sessions to Mom's Sears catalogue, every single person you know felt that way too; and they're all doing it at once. It was a fiscal circlejerk of epic proportions, and the financial crisis was the inevitable bukkake finish. WSB autism is absolutely no comparison for the enthusiasm people had during this time for lighting each other's money on fire. Here's how it works. You pick a company. Any company. Maybe even your own! And then you write a swap. In the swap, you define "Credit Event" with respect to that company's debt as the variable leg . And you write in... whatever you want. A ratings downgrade, default under the docs, failure to meet a leverage ratio or FCCR for a certain testing period... whatever. Now, this started out as a hedge position, just like we discussed above. The purest of intentions, of course. But then people realized - if bad shit happens, you make money. And banks... don't like calling in loans or forcing bankruptcies. Can you smell what the moral hazard is cooking? Enter synthetic CDOs. CDOs are basically pools of asset backed securities that invest in debt (loans or bonds). They've been around for a minute but they got famous in the 2000s because a shitload of them containing subprime mortgage debt went belly up in 2008. This got a lot of publicity because a lot of sad looking rednecks got foreclosed on and were interviewed on CNBC. "OH!", the people cried. "Look at those big bad bankers buying up subprime loans! They caused this!". Wrong answer, America. The debt wasn't the problem. What a lot of people don't realize is that the real meat of the problem was not in regular way CDOs investing in bundles of shit mortgage debts in synthetic CDOs investing in CDS predicated on that debt. They're synthetic because they don't have a stake in the actual underlying debt; just the instruments riding on the coattails. The reason these are so popular (and remain so) is that smart structured attorneys and bankers like your faithful correspondent realized that an even more profitable and efficient way of building high yield products with limited downside was investing in instruments that profit from failure of debt and in instruments that rely on that debt and then hedging that exposure with other CDS instruments in paired trades, and on and on up the chain. The problem with doing this was that everyone wound up exposed to everybody else's books as a result, and when one went tits up, everybody did. Hence, recession, Basel III, etc. Thanks, Obama. Heavy investment in CDS can also have a warping effect on the price of debt (something else that happened during the pre-financial crisis years and is starting to happen again now). This happens in three different ways. (1) Investors who previously were long on the debt hedge their position by selling CDS protection on the underlying, putting downward pressure on the debt price. (2) Investors who previously shorted the debt switch to buying CDS protection because the relatively illiquid debt (partic. when its a bond) trades at a discount below par compared to the CDS. The resulting reduction in short selling puts upward pressure on the bond price. (3) The delta in price and actual value of the debt tempts some investors to become NBTs (neg basis traders) who long the debt and purchase CDS protection. If traders can't take leverage, nothing happens to the price of the debt. If basis traders can take leverage (which is nearly always the case because they're holding a hedged position), they can push up or depress the debt price, goosing swap premiums etc. Anyway. Enough technical details. I could keep going. This is a fascinating topic that is very poorly understood and explained, mainly because the people that caused it all still work on the street and use the same tactics today (it's also terribly taught at business schools because none of the teachers were actually around to see how this played out live). But it relates to the topic of today's lesson, so I thought I'd include it here. Work depending, I'll be back next week with a covenant breakdown. Most upvoted ticker gets the post. *EDIT 1\* In a total blowout, $PLAY won. So it's D&B time next week. Post will drop Monday at market open.
Financial negligence *Small claims*? Was I duped, or just led down a bad path??
Hi All, Location: South England First time poster here (and weirdly, hopefully only a one time poster I suppose). I'll just straight into it!.. I'm from the UK and this happened 3 years ago In 2017 my father passed away and I was left with some money as an inheritance. A colleague/manager of mine at the time was an "Investment Manager".. A Forex Trader... and agreed to take me on as a client... I put in an initial amount of £10,000 (I know... Crazy looking back on that decision but I was young and naïve)... Well a few months go by and the £10000 from april hadn't materialised into any real gain.. I believe 1 or 2 possible trades were successful over a 2 month period. In July I get a message that he has messed up, that he left a trade on over the weekend that his broker wouldn't let him close. This resulted in a HUGE loss, my portfolio now being at £2400 (Roughly). This was a scary scary time and I asked for him to pay out the money that was left in the account (2400)... There was a 3 month lock-in period however he didn't mention this again and was happy to transfer the money out to me. It was a few weeks later and he was suddenly paying off parts of his loans, buying expensive drones and computer equipment, all the while having said he lost close to £100k from his investment account. Being that he was a manager of mine it took me some time to gain the courage to question his decisions and later decided that I would ask for proof of the trades being lost. Something that seems fair after a 70% loss and I would've thought any reasonable IM would have done this and given proof. He said he was unable to provide proof of the loss of trades and things never really went anywhere. well, it's been 3 years now... and I've done some growing up. I would like to see if he can at least provide the proof I require, but I also believe that he has some part to play in this as this might fall under the pretences of Financial Investment Negligence. I've had a few conversations with solicitors on the phone who have all said that because of their hourly rates it wouldn't be viable for me to go through them for legal advice, however one did mention that this might actually constitute criminal charges?? I should say.. Since investing, I found out he was not on the FCA and registered, and I couldn't find any information about his company online to say this was registered. For all intensive purposes he was a solo man doing this as a firm with some very good production quality to his welcome pack and pitches. ANY advice would be well received, even if that's "Sorry, you don't have a case".. Thanks again all. Happy Weekend!
Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are. TL;DR at the bottom for those not interested in the details. This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.
For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX! I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose. This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem. I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.
I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:
I'm using the stop entry version - so I wait for the price to trade beyond the confirmation candle(in the direction of my trade) before entering. I don't have any data to support this decision, but I've always preferred this method over retracement-limit entries. Maybe I just like the feeling of a higher winrate even though there can be greater R:R using a limit entry. Variety is the spice of life.
I put my stop loss right at the opposite edge of the confirmation candle. NOT at the edge of the 2-candle pattern that makes up the system. I'll get into this more below - not enough trades are saved to justify the wider stops. (Wider stop means less $ per pip won, assuming you still only risk 1%).
All my profit/loss statistics are based on a 1% risk per trade. Because 1 is real easy to multiply.
There are definitely some questionable trades in here, but I tried to make it as mechanical as possible for evaluation purposes. They do fit the definitions of the system, which is why I included them. You could probably improve the winrate by being more discretionary about your trades by looking at support/resistance or other techniques.
I didn't use MBB much for either entering trades, or as support/resistance indicators. Again, trying to be pretty mechanical here just for data collection purposes. Plus, we all make bad trading decisions now and then, so let's call it even.
As stated in the title, this is for H1 only. These results may very well not play out for other time frames - who knows, it may not even work on H1 starting this Monday. Forex is an unpredictable place.
I collected data to show efficacy of taking profit at three different levels: -61.8%, -100% and -161.8% fib levels described in the system using the passive trade management method(set it and forget it). I'll have more below about moving up stops and taking off portions of a position.
And now for the fun. Results!
Total Trades: 241
TP at -61.8%: 177 out of 241: 73.44%
TP at -100%: 156 out of 241: 64.73%
TP at -161.8%: 121 out of 241: 50.20%
Adjusted Proft % (takes spread into account):
TP at -61.8%: 5.22%
TP at -100%: 23.55%
TP at -161.8%: 29.14%
As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker. EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.
A Note on Spread
As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits. Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way). However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades. You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term. Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.
Time of Day
Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either. On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
7pm-4am: Fewer setups, but winrate high.
5am-6am: Lots of setups, but but winrate low.
12pm-3pm Medium number of setups, but winrate low.
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate. That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.
Moving stops up to breakeven
This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers. Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability. One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)? Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Adjusted Proft % (takes spread into account): 5.36%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Adjusted Proft % (takes spread into account): -1.01% (yes, a net loss)
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right? Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Winrate(breakeven doesn't count as a win): 46.4%
Adjusted Proft % (takes spread into account): 17.97%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Winrate(breakeven doesn't count as a win): 65.97%
Adjusted Proft % (takes spread into account): 11.60%
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert. I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall. The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.
2-Candle vs Confirmation Candle Stops
Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it. Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL. Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.
As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular. Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system. This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here). Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses. Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels). Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant. One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak. EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
Total Trades: 75
TP at -61.8%: 84.00%
TP at -100%: 73.33%
TP at -161.8%: 60.00%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 53.33%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 53.33% (yes, oddly the exact same winrate. but different trades/profits)
Adjusted Proft % (takes spread into account):
TP at -61.8%: 18.13%
TP at -100%: 26.20%
TP at -161.8%: 34.01%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 19.20%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 17.29%
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much. I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system. This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions. There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated. I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful. Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.
What I will trade
Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
"System Details" I described above.
TP at -161.8%
Static SL at opposite side of confirmation candle - I won't move stops up to breakeven.
Trade only 7am-11am and 4pm-11pm signals.
Nothing where spread is more than 25% of trade width.
Looking at the data for these rules, test results are:
Adjusted Proft % (takes spread into account): 47.43%
I'll be sure to let everyone know how it goes!
Other Technical Details
ATR is only slightly elevated in this date range from historical levels, so this should fairly closely represent reality even after the COVID volatility leaves the scalpers sad and alone.
The sample size is much too small for anything really meaningful when you slice by hour or pair. I wasn't particularly looking to test a specific pair here - just the system overall as if you were going to trade it on all pairs with a reasonable spread.
Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.) I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.
I'm on the East Coast in the US, so the timestamps are Eastern time.
Time stamp is from the confirmation candle, not the indecision candle. So 7am would mean the indecision candle was 6:00-6:59 and the confirmation candle is 7:00-7:59 and you'd put in your order at 8:00.
I found a couple AM/PM typos as I was reviewing the data, so let me know if a trade doesn't make sense and I'll correct it.
Insanely detailed spreadsheet notes
For you real nerds out there. Here's an explanation of what each column means:
Pair - duh
Date/Time - Eastern time, confirmation candle as stated above
Win to -61.8%? - whether the trade made it to the -61.8% TP level before it hit the original SL.
Win to -100%? - whether the trade made it to the -100% TP level before it hit the original SL.
Win to -161.8%? - whether the trade made it to the -161.8% TP level before it hit the original SL.
Retracement level between -61.8% and -100% - how deep the price retraced after hitting -61.8%, but before hitting -100%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -61.8% to -100%. Positive 100 means it hit the original SL.
Retracement level between -100% and -161.8% - how deep the price retraced after hitting -100%, but before hitting -161.8%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -100% to -161.8%. Positive 100 means it hit the original SL.
Trade Width(Pips) - the size of the confirmation candle, and thus the "width" of your trade on which to determine position size, draw fib levels, etc.
Loser saved by 2 candle stop? - for all losing trades, whether or not the 2-candle stop loss would have saved the trade and how far it ended up getting if so. "No" means it didn't save it, N/A means it wasn't a losing trade so it's not relevant.
Spread(ThinkorSwim) - these are typical spreads for these pairs on ToS.
Spread % of Width - How big is the spread compared to the trade width? Not used in any calculations, but interesting nonetheless.
True Risk(Trade Width + Spread) - I set my SL at the opposite side of the confirmation candle knowing that I'm actually exposing myself to slightly more risk because of the spread(stop order = market order when submitted, so you pay the spread). So this tells you how many pips you are actually risking despite the Trade Width. I prefer this over setting the stop inside from the edge of the candle because some pairs have a wide spread that would mess with the system overall. But also many, many of these trades retraced very nearly to the edge of the confirmation candle, before ending up nicely profitable. If you keep your risk per trade at 1%, you're talking a true risk of, at most, 1.25% (in worst-case scenarios with the spread being 25% of the trade width as I am going with above).
Win or Loss in %(1% risk) including spread TP -61.8% - not going to go into huge detail, see the spreadsheet for calculations if you want. But, in a nutshell, if the trade was a win to 61.8%, it returns a positive # based on 61.8% of the trade width, minus the spread. Otherwise, it returns the True Risk as a negative. Both normalized to the 1% risk you started with.
Win or Loss in %(1% risk) including spread TP -100% - same as the last, but 100% of Trade Width.
Win or Loss in %(1% risk) including spread TP -161.8% - same as the last, but 161.8% of Trade Width.
Win or Loss in %(1% risk) including spread TP -100%, and move SL to breakeven at 61.8% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you moved SL to 0% fib level after price hit -61.8%. Then full TP at 100%.
Win or Loss in %(1% risk) including spread take off half of position at -61.8%, move SL to breakeven, TP 100% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you took of half the position and moved SL to 0% fib level after price hit -61.8%. Then TP the remaining half at 100%.
Overall Growth(-161.8% TP, 1% Risk) - pretty straightforward. Assuming you risked 1% on each trade, what the overall growth level would be chronologically(spreadsheet is sorted by date).
Based on the reasonable rules I discovered in this backtest:
Date range: 6/11-7/3
Adjusted Proft % (takes spread into account): 47.43%
Demo Trading Results
Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc). A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade. I'm heading out of town next week, then after that it'll be time to take this sucker live!
Date range: 7/9-7/30
Adjusted Proft % (takes spread into account): 20.73%
Starting Balance: $5,000
Ending Balance: $6,036.51
Live Trading Results
I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
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