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Welcome to 5 Star Forex Systems - Powerful Simplicity
A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. Feel free to submit papers/links of things you find interesting.
I hear people saying when trading on a demo account, they aim to find a concise Forex system that works. If one system doesn't work, they'll attempt to find another one. What does this exactly mean? Does it mean a different way to analyse the market etc?
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.
Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful. If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic. As ever please comment/reply below with questions or feedback and I'll do my best to get back to you. Part II
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Letting stops breathe
We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise. Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight. Imagine being long and stopped out on a meaningless retracement ... ouch! One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure. For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that. If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it. There are also more analytical approaches. Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves. For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size. ATR is available on pretty much all charting systems Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart). Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon? Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.
Reasons to change a stop
As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later. There are some good reasons to modify stops but they are rare. One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are. Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out. Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example. The mighty trailing stop loss order It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops. One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea. Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out. Otherwise, why even have a stop in the first place?
Entering and exiting winning positions
Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price. Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position. The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t. Sad to say but incredibly common: retail traders often take profits way too early This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter. Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid. The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.
Entering positions with limit orders
That covers exiting a position but how about getting into one? Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205. You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait. Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in. So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?! There are two more methods that traders often use for entering a position. Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action. You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market. Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders. Pyramiding into a position means buying more as it goes in your favour Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD. Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct. Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend. You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.
Risk:reward and win ratios
Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important! Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money. If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below. A combination of win % and risk:reward ratio determine if you are profitable A typical rule of thumb is that a ratio of 1:3 works well for most traders. That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips. One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline. Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.
Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad! The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below. The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility. Would you rather have the first trading record or the second? If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps . A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return. If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk. This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ... Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.
The Sharpe ratio works like this:
It takes the average returns of your strategy;
It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent. You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.
VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%. A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade. Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment. Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often. These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.
Coming up in part III
Available here 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.
When I first started trading, I used to add all indicators on my chart. MACD, RSI, super trend, ATR, ichimoku cloud, Bollinger Bands, everything! My chart was pretty messy. I understood nothing and my analysis was pretty much just a gamble. Nothing worked. DISCLOSURE- I've written this article on another sub reddit, if you've already read it, you make skip this one and come back tomorrow. Then I learned price action trading. And things started to change. It seemed difficult and unreliable at first. There's a saying in my country. "Bhav Bhagwan Che" it means "Price Is GOD". That holds true in the market. Amos Every indicator you see is based on price. RSI uses open/close price and so does moving average. MACD uses price. Price is what matters the most. Everything depends on the price, and then the indicators send a signal. Price Action trading is trading based on Candlestick patterns and support and resistance. You don't use any indicators (SMA sometimes), use plot trend lines and support and resistance zones, maybe Fibs or Pivot points. It is not 100% successful, but the win rate is quite high if you know how to analyse it correctly. How To Learn Price Action Trading? YouTube channels- 1. Trading with Rayner Teo. 2. Adam Khoo. 3. The Chart Guys. 4. The Trading Channel (and some other channels including regional ones). Books- 1. Technical Analysis Explained. 2. The trader's book of volume. 3. Trading price action trends. 4. Trading price action reversals. 5. Trading price actions ranges. 6. Naked forex. 7. Technical analysis of the financial markets. I think this is enough information to help you get started. Price Action trading includes a few parts.
Candlestick patterns You'll have to be able to spot a bullish engulfing or a bearish engulfing pattern. Or a doji or a morning star.
Chart Patterns. The flag, wedge, channels or triangles. These are often quite helpful in chart analysis without using indicators.
Support or Resistance. I've seen people draw 15 lines of support and resistance, this just makes your chart messy and you don't know where the price will take a support.
You can also you the demand and supply zone concept if you're more comfortable with that.
Volume. There's a quote "Boule precedes price". Volume analysis is a bit hard, but it's totally worth learning. Divergence is also a great concept.
Multiple time frames. To confirm a trend or find the long term support or resistance, you can use a higher time frame. Plus, it is more reliable and divergence is way stronger on it.
You can conclude everything to make a powerful system. Like if there's a divergence (price up volume down) and there's a major resistance on some upper level and a double top is formed, That's a very reliable strategy to go short. Combinations of various systems work very good imo. Does this mean that indicators are useless? No, I use moving averages and RSI quite frequently. Using price action and confirming it through indicators gives me a higher win rate. "Bhav Bhagwan Che". -Vikrant C.
Factset: How You can Invest in Hedge Funds’ Biggest Investment Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now: Their latest 8k filing reported the following: Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions. Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic. Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019. Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results. The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020. FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders. As you can see, there’s not much of a negative sign in sight here. It makes sense considering how FactSet’s FCF has never slowed down: https://preview.redd.it/frmtdk8e9hk51.png?width=276&format=png&auto=webp&s=1c0ff12539e0b2f9dbfda13d0565c5ce2b6f8f1a https://preview.redd.it/6axdb6lh9hk51.png?width=593&format=png&auto=webp&s=9af1673272a5a2d8df28f60f4707e948a00e5ff1 FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with. Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis: https://www.investopedia.com/terms/f/factset.asp https://preview.redd.it/yo71y6qj9hk51.png?width=355&format=png&auto=webp&s=a9414bdaa03c06114ca052304a26fae2773c3e45 FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015: https://preview.redd.it/oxaa1wel9hk51.png?width=443&format=png&auto=webp&s=13d60d2518980360c403364f7150392ab83d07d7 So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33% https://preview.redd.it/e4trju3p9hk51.png?width=387&format=png&auto=webp&s=6f6bee15f836c47e73121054ec60459f147d353e EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded. https://preview.redd.it/yl7f58tr9hk51.png?width=489&format=png&auto=webp&s=68906b9ecbcf6d886393c4ff40f81bdecab9e9fd P/E has declined in the past 2 years, making it a great time to buy. https://preview.redd.it/4mqw3t4t9hk51.png?width=445&format=png&auto=webp&s=e8d719f4913883b044c4150f11b8732e14797b6d Increasing ROE despite lowering of leverage post 2016 https://preview.redd.it/lt34avzu9hk51.png?width=441&format=png&auto=webp&s=f3742ed87cd1c2ccb7a3d3ee71ae8c7007313b2b Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself. https://preview.redd.it/fliirmpx9hk51.png?width=370&format=png&auto=webp&s=1216eddeadb4f84c8f4f48692a2f962ba2f1e848 SGA expense/Gross profit has been declining despite expansion of offices I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful. Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in. Calls have shitty greeks, but if you're ballsy October 450s LOL, I'm holding shares I’d say it’s a great long term investment, and it should at least be on your watchlist.
I'm apparently some kind of moron- I'm unable to figure out how to get set up with automated trading on interactive brokers. Currently I'm paper trading forex on OandA using some simple curl requests on a headless server. I'd like to start trading futures, and ibkr was the top recommendation. Goals: -When my own (already developed) system generates an entry or exit alert, execute a market order on a NASDAQ micro futures contact. -Do it on a headless Google cloud server From chatting with some folks, I've heard I need to use IB Gateway, and there may be a need to initially use GUI for authentication. That's fine, as long as GUI elements aren't needed later when it's running. I don't need any kind of data feed from IBKR, since I already have a system that generates alerts when I want it to. I just need the bare minimum to actually execute these market orders. I've signed up for IBKR and gotten my account approved and all that. Then I thought I'd go over to the education library and work through the TWS materials (just to get acquainted) and then go through the TWS programming Python course. At this point, the website wants me to register or login. I click the button that says I already have an ibkr account, it asks me to login, I do, then it takes me to the account page. Where is the course!?😵 After going through that loop every which way, I've given up on that for now and I'm here asking you for help. Anyone willing to give some guidance, either in this thread or through DM? I feel like what I want to do is extremely simple and I will be barely scratching the surface of what's available to me through IBKR. I just want to get started. Advice, resources, guides, and insults are all welcome! Thanks!
I’ve been looking for a broker that has an API for index futures and ideally also futures options. I’m looking to use the API to build a customized view of my risk based on balances, positions, and market conditions. Searching the algotrading sub I found many API-related posts, but then when I actually read them and their comments, I found they’re often lacking in real substance. It turns out many brokers or data services that have APIs don’t actually support index futures and options via the API, and instead they focus on equities, forex, or cypto. So here’s the list of what I’ve found so far. This isn’t a review of these brokers or APIs and note that I have a specific application in mind (index futures and futures options). Perhaps you’re looking for an API for equities, or you just want data and not a broker, in which case there may be a few options. Also, I’m based in the US so I didn’t really look for brokers or platforms outside the US. If you have experience with these APIs, please chime in with your thoughts. Also, I may have missed some brokers or platforms. If I did or if you see anything that needs correction please let me know.
Broker with a variety of platforms including CQG, Rithmic, TT, some with APIs
Wow, this list grew longer than I originally thought it would be. If you spot a mistake, please let me know and I’ll correct it. Edit: - added Lightspeed API - updated Dashprime to indicate some of the APIs available - added Medved Trader to table - added marketstack to table
This thread is the direct continuation of my previous entry, which you can find here. I have the feeling my rambles may be long, so I'm not going to repeat anything I already said in my previous post for the sake of keeping this brief. What is this? I am backtesting the strategy shared by ParallaxFx. I have just completed my second run of testing, and I am here to share my results with those who are interested. If you want to read more about the strategy, go to my previous thread where I linked it. What changed? Instead of using a fixed target of the -100.0 Fibonacci extension, I tracked both the -61.8 and the -100.0 targets. ParallaxFx used the -61.8 as a target, but never tried the second one, so I wanted to compare the two and see what happens. Where can I see your backtested result? I am going to do something I hope I won't regret and share the link to my spreadsheet. Hopefully I won't be doxxed, but I think I should be fine. You can find my spreadsheet at this link. There are a lot of entries, so it may take a while for them to load. In the "Trades" tab, you will find every trade I backtested with an attached screenshot and the results it would have had with the extended and the unextended target. You can see the UNCOMPOUNDED equity curve in the Summary tab, together with the overall statistics for the system. What was the sample size? I backtested on the Daily chart, from January 2017 to December 2019, over 28 currency pairs. I took a total of 310 trades - although keep in mind that every position is most often composed by two entries, meaning that you can roughly halve this number. What is the bottom line? If you're not interested in the details, here are the stats of the strategy based on how I traded it.
Extended: 223.46 R of return, 2.34 of profit factor, 0.72 R of expected value, 46.13% winrate. The average win is 2.72 R while the average loss is -1.00 R.
Unextended: 172.20 R of return, 2.19 of profit factor, 0.56 R of expected value, 53.23% winrate. The average win is 1.92 R while the average loss is -1.00 R.
The highest drawdown for both systems was 18 R. This seems like a lot, but remember you're splitting risk in half.
Here you can see the two uncompounded equity curves side by side: red is unextended and blue is extended. Who wins? The test suggests the strategy to be more profitable with the extended target. In addition, most of the trades that reached the unextended target but reversed before reaching the extended, were trades that I would have most likely not have taken with the extented target. This is because there was a resistance/support area in the way of the -100.0 extension level, but there was enough room for price to reach the -61.8 level. I will probably trade this strategy using the -100.0 level as target, unless there is an area in the way. In that case I will go for the unextended target. Drawdown management The expected losing streak for this system, using the extended target, is 7 trades in a row in a sample size of 100 trades. My goal is to have a drawdown cap of 4%, so my risk per trade will be 0.54%. If I ever find myself in a losing streak of more than 8 trades, I will reduce my risk per trade further. What's next? I'll be taking this strategy live. The wisest move would be to repeat the same testing over lower timeframes to verify the edge plays out there as well, but I would not be able to trust my results because I would have vague memories of where price went because of the testing I just did. I also believe markets are fractals, so I see no reason why this wouldn't work on lower timeframes. Before going live, I will expand this spreadsheet to include more specific analysis and I will continue backtesting at a slower pace. The goal is to reach 20 years of backtesting over these 28 pairs and put everything into this spreadsheet. It's not something I will do overnight, but I'll probably do one year every odd day, and maybe a couple more during the weekend. I think I don't have much else to add. I like the strategy. Feel free to ask questions.
[Secret] Response to the Oil Embargo Part 2: Retaliation, Covert and Chaotic
While overt operations will play a role in the retaliation, some more covert ones are needed. For these more... illegal... operations, we will have to take a different approach. North Korea: Cyberwar, Inc. North Korea has a well-established cyberwar capability and has recently begun selling its services to third parties. One of those third parties is about to become us, and we're going to buy out the entire shop, consisting of thousands of highly trained North Korean hackers. Are they the best, no, of course not--they are, after all, still North Korean. They certainly aren't as good as what we have in-house, even though they're surprisingly skilled all things considered. But they're extra talent, and talent with no official connections to China, and that's what counts here. At whatever exorbitant price that North Korea charges [we've budgeted up to $500 million, and they will get to keep whatever they steal] we're siccing every trained hacker they have on what we view as the mastermind behind these plots, the United Arab Emirates [M: Even though we don't know the contents of the closed diplo, it's not hard to come to that conclusion given that Saudi Arabia is in a civil war, the UAE leads the GCC which is leading the embargo, and it has rejected our peace offerings and stated that we are an existential threat--also, assaulting the UAE is likely to spook the other participants who are in a much more frail situation]. Attacks will aim to be diverse and encompass the entire spectrum, with one exception, which we will do. Chinese experts will provide advice and limited intelligence and cyber-reconnaissance, but will not openly involve themselves in the operations, taking especial care to ensure that they don't touch the code the North Koreans are working on. We will maintain only a very high-level management, leaving precise means, targets, and so on to the North Koreans. In addition, we'll ask the North Koreans to recruit criminal hacker groups across the globe to join on to this effort, with the North Koreans receiving additional payouts for every other criminal hacking group they bring onboard that has been verified by Chinese intelligence as actually existing [we don't trust the North Koreans that much, especially when money is on the line]. Targets are the following, in order of priority: UAE Foreign Exchange Reserves and Sovereign Wealth Fund: By far the most valuable target on the list for North Korea, the UAE's forex reserves are worth about $100 billion, and the sovereign wealth funds of the Emirates are valued at as much as $1 trillion. North Korean hackers will launch an all-out assault aiming to steal as much of this money as possible, destroying it if they must but, we imagine, preferably transferring it to North Korean accounts. Attacks via SWIFT like those conducted by North Korea in 2015-16 are possible--those attacks amounted to hundreds of millions of dollars in losses. We doubt that North Korea will be able to steal that much of this pile, especially given the fact that the UAE has an army of ex-Western cyberwarriors of its own, but even a relatively small quantity would be a significant psychological injury and would degrade global trust in the UAE. Vital Infrastructure: North Korea will target key pieces of infrastructure in the UAE. In particular, they will target the following facilities and attempt to force them offline. Even though the individual attacks won't do much damage, the cumulative impact will scare the public, damage investor confidence, and drive money out of the UAE.
Dubai International Airport
All 8 desalination plants, the only source of potable water in the UAE [top target]
UAE High-speed rail [as this system uses Chinese software the North Koreans will happen to find a copy of the source code to work this one over]
Barakah Nuclear Power Plant [as this system uses South Korean software North Korea may have added experience with it]
Ruwais Refinery, capacity 400,000 barrels of oil per day, the largest in the UAE
Influential Figures And Government Officials: North Korean hackers will also target the personal devices of government officials and influential figures in the UAE, especially politicians, military commanders, and media types. They will then leak anything remotely incriminating to the global media, possibly via Wikileaks or another such site of ill repute. In addition, for particularly important government officials, North Korea will be commissioned to produce deepfakes with which it will flood social media. These will mostly focus on baseless conspiracy theories and personal slanders, for instance, catching a top official on mike confessing to being a devil-worshiper, or portraying a popular imam as being with Western prostitutes. It is hoped that these operations will cause enough domestic trouble in the UAE that they will concede on the point of the oil embargo. If nothing else, though, they should keep the UAE distracted while we move elsewhere.
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