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
Market positioning
Bet correlation
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.

Events

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.

Squeezes

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.

Asymmetric losses

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.

Market positioning

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.

Bet correlation

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

Introduction
Why use the economic calendar
Reading the economic calendar
Knowing what's priced in
Surveys
Interest rates
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
Reversals
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.

The majority of this sub is focused on technical analysis. I regularly ridicule such "tea leaf readers" and advocate for trading based on fundamentals and economic news instead, so I figured I should take the time to write up something on how exactly you can trade economic news releases.
This post is long as balls so I won't be upset if you get bored and go back to your drooping dick patterns or whatever.

How economic news is released

First, it helps to know how economic news is compiled and released. Let's take Initial Jobless Claims, the number of initial claims for unemployment benefits around the United States from Sunday through Saturday. Initial in this context means the first claim for benefits made by an individual during a particular stretch of unemployment. The Initial Jobless Claims figure appears in the Department of Labor's Unemployment Insurance Weekly Claims Report, which compiles information from all of the per-state departments that report to the DOL during the week. A typical number is between 100k and 250k and it can vary quite significantly week-to-week.
The Unemployment Insurance Weekly Claims Report contains data that lags 5 days behind. For example, the Report issued on Thursday March 26th 2020 contained data about the week ending on Saturday March 21st 2020.
In the days leading up to the Report, financial companies will survey economists and run complicated mathematical models to forecast the upcoming Initial Jobless Claims figure. The results of surveyed experts is called the "consensus"; specific companies, experts, and websites will also provide their own forecasts. Different companies will release different consensuses. Usually they are pretty close (within 2-3k), but for last week's record-high Initial Jobless Claims the reported consensuses varied by up to 1M! In other words, there was essentially no consensus.
The Unemployment Insurance Weekly Claims Report is released each Thursday morning at exactly 8:30 AM ET. (On Thanksgiving the Report is released on Wednesday instead.) Media representatives gather at the Frances Perkins Building in Washington DC and are admitted to the "lockup" at 8:00 AM ET. In order to be admitted to the lockup you have to be a credentialed member of a media organization that has signed the DOL lockup agreement. The lockup room is small so there is a limited number of spots.
No phones are allowed. Reporters bring their laptops and connect to a local network; there is a master switch on the wall that prevents/enables Internet connectivity on this network. Once the doors are closed the Unemployment Insurance Weekly Claims Report is distributed, with a heading that announces it is "embargoed" (not to be released) prior to 8:30 AM. Reporters type up their analyses of the report, including extracting key figures like Initial Jobless Claims. They load their write-ups into their companies' software, which prepares to send it out as soon as Internet is enabled. At 8:30 AM the DOL representative in the room flips the wall switch and all of the laptops are connected to the Internet, releasing their write-ups to their companies and on to their companies' partners.
Many of those media companies have externally accessible APIs for distributing news. Media aggregators and squawk services (like RanSquawk and TradeTheNews) subscribe to all of these different APIs and then redistribute the key economic figures from the Report to their own subscribers within one second after Internet is enabled in the DOL lockup.
Some squawk services are text-based while others are audio-based. FinancialJuice.com provides a free audio squawk service; internally they have a paid subscription to a professional squawk service and they simply read out the latest headlines to their own listeners, subsidized by ads on the site. I've been using it for 4 months now and have been pretty happy. It usually lags behind the official release times by 1-2 seconds and occasionally they verbally flub the numbers or stutter and have to repeat, but you can't beat the price!
Important - I’m not affiliated with FinancialJuice and I’m not advocating that you use them over any other squawk. If you use them and they misspeak a number and you lose all your money don’t blame me. If anybody has any other free alternatives please share them!

How the news affects forex markets

Institutional forex traders subscribe to these squawk services and use custom software to consume the emerging data programmatically and then automatically initiate trades based on the perceived change to the fundamentals that the figures represent.
It's important to note that every institution will have "priced in" their own forecasted figures well in advance of an actual news release. Forecasts and consensuses all come out at different times in the days leading up to a news release, so by the time the news drops everybody is really only looking for an unexpected result. You can't really know what any given institution expects the value to be, but unless someone has inside information you can pretty much assume that the market has collectively priced in the experts' consensus. When the news comes out, institutions will trade based on the difference between the actual and their forecast.
Sometimes the news reflects a real change to the fundamentals with an economic effect that will change the demand for a currency, like an interest rate decision. However, in the case of the Initial Jobless Claims figure, which is a backwards-looking metric, trading is really just self-fulfilling speculation that market participants will buy dollars when unemployment is low and sell dollars when unemployment is high. Generally speaking, news that reflects a real economic shift has a bigger effect than news that only matters to speculators.
Massive and extremely fast news-based trades happen within tenths of a second on the ECNs on which institutional traders are participants. Over the next few seconds the resulting price changes trickle down to retail traders. Some economic news, like Non Farm Payroll Employment, has an effect that can last minutes to hours as "slow money" follows behind on the trend created by the "fast money". Other news, like Initial Jobless Claims, has a short impact that trails off within a couple minutes and is subsequently dwarfed by the usual pseudorandom movements in the market.
The bigger the difference between actual and consensus, the bigger the effect on any given currency pair. Since economic news releases generally relate to a single currency, the biggest and most easily predicted effects are seen on pairs where one currency is directly effected and the other is not affected at all. Personally I trade USD/JPY because the time difference between the US and Japan ensures that no news will be coming out of Japan at the same time that economic news is being released in the US.
Before deciding to trade any particular news release you should measure the historical correlation between the release (specifically, the difference between actual and consensus) and the resulting short-term change in the currency pair. Historical data for various news releases (along with historical consensus data) is readily available. You can pay to get it exported into Excel or whatever, or you can scroll through it for free on websites like TradingEconomics.com.
Let's look at two examples: Initial Jobless Claims and Non Farm Payroll Employment (NFP). I collected historical consensuses and actuals for these releases from January 2018 through the present, measured the "surprise" difference for each, and then correlated that to short-term changes in USD/JPY at the time of release using 5 second candles.
I omitted any releases that occurred simultaneously as another major release. For example, occasionally the monthly Initial Jobless Claims comes out at the exact same time as the monthly Balance of Trade figure, which is a more significant economic indicator and can be expected to dwarf the effect of the Unemployment Insurance Weekly Claims Report.
USD/JPY correlation with Initial Jobless Claims (2018 - present)
USD/JPY correlation with Non Farm Payrolls (2018 - present)
The horizontal axes on these charts is the duration (in seconds) after the news release over which correlation was calculated. The vertical axis is the Pearson correlation coefficient: +1 means that the change in USD/JPY over that duration was perfectly linearly correlated to the "surprise" in the releases; -1 means that the change in USD/JPY was perfectly linearly correlated but in the opposite direction, and 0 means that there is no correlation at all.
For Initial Jobless Claims you can see that for the first 30 seconds USD/JPY is strongly negatively correlated with the difference between consensus and actual jobless claims. That is, fewer-than-forecast jobless claims (fewer newly unemployed people than expected) strengthens the dollar and greater-than-forecast jobless claims (more newly unemployed people than expected) weakens the dollar. Correlation then trails off and changes to a moderate/weak positive correlation. I interpret this as algorithms "buying the dip" and vice versa, but I don't know for sure. From this chart it appears that you could profit by opening a trade for 15 seconds (duration with strongest correlation) that is long USD/JPY when Initial Jobless Claims is lower than the consensus and short USD/JPY when Initial Jobless Claims is higher than expected.
The chart for Non Farm Payroll looks very different. Correlation is positive (higher-than-expected payrolls strengthen the dollar and lower-than-expected payrolls weaken the dollar) and peaks at around 45 seconds, then slowly decreases as time goes on. This implies that price changes due to NFP are quite significant relative to background noise and "stick" even as normal fluctuations pick back up.
I wanted to show an example of what the USD/JPY S5 chart looks like when an "uncontested" (no other major simultaneously news release) Initial Jobless Claims and NFP drops, but unfortunately my broker's charts only go back a week. (I can pull historical data going back years through the API but to make it into a pretty chart would be a bit of work.) If anybody can get a 5-second chart of USD/JPY at March 19, 2020, UTC 12:30 and/or at February 7, 2020, UTC 13:30 let me know and I'll add it here.

Backtesting

So without too much effort we determined that (1) USD/JPY is strongly negatively correlated with the Initial Jobless Claims figure for the first 15 seconds after the release of the Unemployment Insurance Weekly Claims Report (when no other major news is being released) and also that (2) USD/JPY is strongly positively correlated with the Non Farms Payroll figure for the first 45 seconds after the release of the Employment Situation report.
Before you can assume you can profit off the news you have to backtest and consider three important parameters.
Entry speed: How quickly can you realistically enter the trade? The correlation performed above was measured from the exact moment the news was released, but realistically if you've got your finger on the trigger and your ear to the squawk it will take a few seconds to hit "Buy" or "Sell" and confirm. If 90% of the price move happens in the first second you're SOL. For back-testing purposes I assume a 5 second delay. In practice I use custom software that opens a trade with one click, and I can reliably enter a trade within 2-3 seconds after the news drops, using the FinancialJuice free squawk.
Minimum surprise: Should you trade every release or can you do better by only trading those with a big enough "surprise" factor? Backtesting will tell you whether being more selective is better long-term or not.
Hold time: The optimal time to hold the trade is not necessarily the same as the time of maximum correlation. That's a good starting point but it's not necessarily the best number. Backtesting each possible hold time will let you find the best one.
The spread: When you're only holding a position open for 30 seconds, the spread will kill you. The correlations performed above used the midpoint price, but in reality you have to buy at the ask and sell at the bid. Brokers aren't stupid and the moment volume on the ECN jumps they will widen the spread for their retail customers. The only way to determine if the news-driven price movements reliably overcome the spread is to backtest.
Stops: Personally I don't use stops, neither take-profit nor stop-loss, since I'm automatically closing the trade after a fixed (and very short) amount of time. Additionally, brokers have a minimum stop distance; the profits from scalping the news are so slim that even the nearest stops they allow will generally not get triggered.
I backtested trading these two news releases (since 2018), using a 5 second entry delay, real historical spreads, and no stops, cycling through different "surprise" thresholds and hold times to find the combination that returns the highest net profit. It's important to maximize net profit, not expected value per trade, so you don't over-optimize and reduce the total number of trades taken to one single profitable trade. If you want to get fancy you can set up a custom metric that combines number of trades, expected value, and drawdown into a single score to be maximized.
For the Initial Jobless Claims figure I found that the best combination is to hold trades open for 25 seconds (that is, open at 5 seconds elapsed and hold until 30 seconds elapsed) and only trade when the difference between consensus and actual is 7k or higher. That leads to 30 trades taken since 2018 and an expected return of... drumroll please... -0.0093 yen per unit per trade.
Yep, that's a loss of approx. $8.63 per lot.
Disappointing right? That's the spread and that's why you have to backtest. Even though the release of the Unemployment Insurance Weekly Claims Report has a strong correlation with movement in USD/JPY, it's simply not something that a retail trader can profit from.
Let's turn to the NFP. There I found that the best combination is to hold trades open for 75 seconds (that is, open at 5 seconds elapsed and hold until 80 seconds elapsed) and trade every single NFP (no minimum "surprise" threshold). That leads to 20 trades taken since 2018 and an expected return of... drumroll please... +0.1306 yen per unit per trade.
That's a profit of approx. $121.25 per lot. Not bad for 75 seconds of work! That's a +6% ROI at 50x leverage.

Make it real

If you want to do this for realsies, you need to run these numbers for all of the major economic news releases. Markit Manufacturing PMI, Factory Orders MoM, Trade Balance, PPI MoM, Export and Import Prices, Michigan Consumer Sentiment, Retail Sales MoM, Industrial Production MoM, you get the idea. You keep a list of all of the releases you want to trade, when they are released, and the ideal hold time and "surprise" threshold. A few minutes before the prescribed release time you open up your broker's software, turn on your squawk, maybe jot a few notes about consensuses and model forecasts, and get your finger on the button. At the moment you hear the release you open the trade in the correct direction, hold it (without looking at the chart!) for the required amount of time, then close it and go on with your day.
Some benefits of trading this way: * Most major economic releases come out at either 8:30 AM ET or 10:00 AM ET, and then you're done for the day. * It's easily backtestable. You can look back at the numbers and see exactly what to expect your return to be. * It's fun! Packing your trading into 30 seconds and knowing that institutions are moving billions of dollars around as fast as they can based on the exact same news you just read is thrilling. * You can wow your friends by saying things like "The St. Louis Fed had some interesting remarks on consumer spending in the latest Beige Book." * No crayons involved.
Some downsides: * It's tricky to be fast enough without writing custom software. Some broker software is very slow and requires multiple dialog boxes before a position is opened, which won't cut it. * The profits are very slim, you're not going to impress your instagram followers to join your expensive trade copying service with your 30-second twice-weekly trades. * Any friends you might wow with your boring-ass economic talking points are themselves the most boring people in the world.
I hope you enjoyed this long as fuck post and you give trading economic news a try!

Key Factors that Affect Foreign Exchange Rates

I like my numbers how I like my men

Hard.
Following up on my post about trading economic news, here are some hard numbers about news releases. If you can't be bothered to read any further, just know that a high S value means there is money to be made by trading the release of that economic metric.
I collected historical data (consensus and actual) for each of these economic metrics from January 2018 to the present. These are mostly monthly metrics; one is quarterly, one is biweekly, and one is weekly. I did this manually from an economic news aggregation website because I'm too cheap to pay for exported data. I also noted whether each release was the primary (or only) news being released at that precise moment or whether there were other important economic metrics being released at the same time.
Then I wrote software to fetch 2 minutes of USD/JPY price data (in 5 second candles) starting at the time of each release and correlated each candle to the "surprise" in the metric (the difference between the consensus and the actual). That produced data for each metric that looks like this and give you an idea how reliably the news predicts the short-term price move.
Next the software went back through the price history and measured the "coordinated movement" of the currency pair during each candle. By that I mean it measured the size of each candle in pips and then set the sign to be positive if its moving in the same direction as the first candle or negative otherwise, and averaged all those numbers together. These charts look like this and give you an idea how dramatically the price moves in response to the news.
Then, for each candle, the absolute value of the correlation is multiplied against the coordinated movement, creating a "tradeability" score. The idea is that a strong (positive or negative) correlation and a strong coordinated movement yields a high score, and either a weak correlation or a small price movement yields a low score. These charts look like this.
Finally, for each news release I measured the maximum value of the correlation (R) and the maximum value of the tradeability score (S). Since I don't have access to anything with finer granularity than 5 seconds, it's no surprise that candle 0 had the maximum correlation and maximum tradeability for each metric.
I did this process twice for every metric: first over all releases and second over only those releases that were the primary or only release happening at that moment. I kept the results from the one that returned the better net maximum tradeability score. The net maximum tradeability score is just the product of the maximum tradeability score and the number of releases being considered, either all of them or some smaller number. (This helps avoid bias in the results for metrics that are often released at the same time as other metrics.)
In the results linked at the top of this post, the metrics are ordered by decreasing maximum tradeability score (S) with maximum correlation (R) also shown. Remember, R = +1 means perfect positive linear correlation, R = -1 means perfect negative linear correlation, and R = 0 means no correlation. S values less than 3 are essentially untradeable due to the spread.
A couple notes:

Non Farms Payroll, one of the most closely watched economic indicators, is the most tradeable by far. Although not shown here, the correlation is even higher (0.8xx) if you omit those releases that occur simultaneously as other news, but because of the strong correlation and high pip movement it's better overall to consider all NFP releases.
Retail Sales is tradeable, but Personal Income and Personal Spending is not. This was a surprise to me, I haven't traded any of these metrics before. I'll have to look into what is exactly in each one to understand why this is.
With the exception of Michigan Consumer Sentiment, all of these releases are correlated with the price movement, but many of them aren't practical to trade because the movement is too small.
The negative sign and weak correlation on Inflation Rate MoM is a bug, I think. I got a different (positive) number when I ran it earlier, but then I was on a conference call while reformatting the data and I may have done something dumb. I'll go back and review it.

It takes me about 15 minutes to scrape 2 years of monthly data by hand and type it up, and then the software takes about 10 seconds to run per metric. If there are regular forecasted economic releases that you'd like to see correlated and scored, let me know! I can do other currency pairs and other country's economic news as well, it's just a matter of data collection.

some helphul common terms for forex traders

Common terms:

ADX – Average Directional Index (technical indicator)
ATR – Average True Range (technical indicator)
BB – Bollinger Bands (technical indicator)
BE – Breakeven
BoC – Bank of Canada
BoE – Bank of England
BoJ – Bank of Japan
BP – Basis Point
CBOT – Chicago Board of Trade
CCI – Commodity Channel Index (technical indicator); also Consumer Confidence Index (economic indicator)
CFA – Chartered Financial Analyst
CFTC – Commodity Futures Trading Commission (regulatory)
CME – Chicago Mercantile Exchange
COT – Commitments of Traders (market report)
CPI – Consumer Price Index (economic indicator
CSI – Commodity Selection Index (technical indicator)
CTA – Commodity Trading Advisor
DD – Drawdown, also Due Diligence, also Dealing Desk (see NDD)
EA – Expert Advisor
ECB – European Central Bank
ECN – Electronic Communication Network, also Electronic Currency Network
EMA – Exponential Moving Average (technical indicator)
ETF – Exchange Traded Fund
EW – Elliott Wave (theory)
FA – Fundamental Analysis
FCM – Futures Commission Merchant
FDM – Forex Dealer Member
Fed – Federal Reserve System
FF – Forex Factory
FIFO – First In, First Out
FOMC – Federal Open Market Committee
FX – Foreign Exchange
GDP – Gross Domestic Product (economic indicator)
GMT – Greenwich Mean Time
HH – Higher High (chart)
HL – Higher Low (chart)
IB – Introducing Broker, also Interbank, also Interactive Brokers, also Inside Bar
IMF – International Monetary Fund
ISO – International Organization for Standardization
LONG – A position purchasing a particular currency against another currency
LH – Lower High (chart)
LL – Lower Low (chart)
LWMA – Linearly Weighted Moving Average (technical indicator)
MT4 – MetaTrader Version 4.00 (trading platform)
MA – Moving Average (technical indicator)
MACD – Moving Average Convergence Divergence (technical indicator)
MM – Market Maker, also Money Management
MTF – Multiple Time Frame
NDA – Non-Disclosure Agreement
NDD – Non-Dealing Desk
NFA – National Futures Association (regulatory)
NFP – Nonfarm Payroll (economic indicator)
OCO – One-Cancels-the-Other (order type)
OHLC – Open, High, Low, Close (chart)
OTC– Over-the-Counter
P&F – Point and Figure (chart)
PA – Price Action
PB – Pin Bar abbreviation of Pinocchio Bar (chart)
PIP – Price Interest Point, also Performance Index Paper
PP – Pivot Point
PPI – Producer Price Index (economic indicator)
PPZ Price Pivot Zone
PSAR – Parabolic Stop and Reversal (technical indicator)
Quant – Quantitative Analysis
R – Risk/Reward (ratio)
RSI – Relative Strength Index (technical indicator)
RVI – Relative Vigor Index (technical indicator)
SAR – Stop and Reversal
SEC – Securities and Exchange Commission (regulatory)
SHORT – To sell a currency
SL – Stop-Loss (order)
SMA – Simple Moving Average (technical indicator)
SMMA – Smoothed Moving Average (technical indicator)
S&P – Standard & Poor's
S/R – Support/Resistance
Stoch – Stochastic Oscillator (technical indicator)
STP – Straight Through Processing
TA – Technical Analysis
TF Time Frame
TL – Trend Line
TP – Take Profit (order)
TS – Trailing Stop (order)
TSI – True Strength Index (technical indicator)
UTC – Universal Time, Coordinated
WB – World Bank

Avoiding The News

Auto-trading fun with Bollinger bands [Novice level].

Whilst we have a fair few 'novice' posts about TA and Global Macro (aka "Fundamentals"), there aren't too many involving auto-trading. Seeing as I'm in the middle of teaching myself MQL4, I thought I'd throw this out there as discussion prompter.
By "novice", I mean someone who has moved beyond complete beginner ("what's a FOMC and a NFP?") but still not deploying robust and market ready strategies ("how does market structure affect news event response?"), so constructive criticism, informed commentary or taking the ideas and developing them further are very much the point of sharing in the first place. It's not meant to be a showcase of code, because the code is a mess!
This post got me thinking about how relatively trivial it would be to implement a Bollinger Band mean reversion autotrader.
Project Goals
My interest in the project was as a way to begin development of a skeleton EA that would use a custom indicator to implement trade signals. The point of this would be to allow for faster prototyping of visually based autotrading before taking it to the testing environment. The key advantage of this is that you can see on your charts which entries are being missed, something that is much more laborious to do via visual mode in the strategy tester.
Concept Development
So to begin the project, I sketched out the concept.
One way to trade Bollinger Bands is to trade the reversion to the mean. Intuitively, we expect that wider deviations from the mean will result in more reliable reversions to the mean. To explore this we could enter when price breaches the second SD band and then returns back inside it.
Here's the default Bollinger Band on default settings in MT4, demonstrating this sort of behaviour:
http://i.imgur.com/dK2oDO7.png
Prototyping
I want to use the indicator, and not the EA, to generate trade signals, as this is the point of the project for me. Because I'm lazy and grew up coding in basements, I opt to fiddle with the default indicator code rather than build up from scratch.
My first goal is to add two things.
Firstly, I want to add another layer of bands, because I saw a set up like that a while ago and liked it. (This is not a very good reason, and I think it costs me down the track).
Secondly, I want to add in a way to visually indicate the trade signals before we pass them to the EA.
Adding another set of bands is just a copy and paste of the existing bands. My learning point here is that I need to adjust the amount of buffers to match the number of bands I want. This comes into play for adding the trade signal arrows, as they need to go in the same sort of structure as the second lot of bands.
[I know from reading about the project goals in advance that EAs access custom indicators via iCustom(). This function can only receive the contents of one of the first 8 indicator buffers. Thus the idea will be that the buffer that marks out the trade entries on the indicator will later be used by the EA to mark out where entries should be. It's possible this is not the best way for EAs to access custom indicators , so input from more experienced coders is welcome!]

#property indicator_chart_window #property indicator_buffers 8 // <---- have to set this to match your copy and pasted buffer amount #property indicator_color1 LightSeaGreen #property indicator_color2 LightSeaGreen #property indicator_color3 LightSeaGreen // hack in (make 'em colourful. Turns out I didn't understand how the numbering worked, and indictator_color4 is never visualised) #property indicator_color4 clrWhite #property indicator_color5 clrWhite #property indicator_color6 clrRed #property indicator_color7 clrGreen #property indicator_color8 clrRed //--- indicator parameters input int InpBandsPeriod=50; // Bands Period input int InpBandsShift=0; // Bands Shift input double InpBandsInnerDeviations=1.0; // Add in for our other Band input double InpBandsOuterDeviations=2.0; // Bands Deviations //--- buffers double ExtMovingBuffer[]; double ExtUpperBuffer[]; double ExtLowerBuffer[]; double ExtStdDevBuffer[]; // hack in buffers (these buffers will store our trade signals) double SellSignalBuffer[]; double BuySignalBuffer[]; // these buffers will hold the additional bands. apologies for the naming, I didn't originally intend to share this double ExtUpperUpperBuffer[]; double ExtLowerLowerBuffer[]; //+------------------------------------------------------------------+ //| Custom indicator initialization function | //+------------------------------------------------------------------+ int OnInit(void) { //--- 1 additional buffer used for counting. IndicatorBuffers(8); // don't forget to adjust this to account for the new buffers IndicatorDigits(Digits); //--- middle line SetIndexStyle(0,DRAW_LINE); SetIndexBuffer(0,ExtMovingBuffer); SetIndexShift(0,InpBandsShift); SetIndexLabel(0,"Bands SMA"); //--- upper band SetIndexStyle(1,DRAW_LINE); SetIndexBuffer(1,ExtUpperBuffer); SetIndexShift(1,InpBandsShift); SetIndexLabel(1,"Bands Upper"); //--- lower band SetIndexStyle(2,DRAW_LINE); SetIndexBuffer(2,ExtLowerBuffer); SetIndexShift(2,InpBandsShift); SetIndexLabel(2,"Bands Lower"); SetIndexBuffer(3,ExtStdDevBuffer); //--- Copy and paste from above, and just change the number! Upper outer band is INDEX 4 SetIndexStyle(4,DRAW_LINE); SetIndexBuffer(4,ExtUpperUpperBuffer); SetIndexShift(4,InpBandsShift); SetIndexLabel(4,"Bands Outer Upper"); //--- Copy& paste, lower outer band is INDEX 5 SetIndexStyle(5,DRAW_LINE); SetIndexBuffer(5,ExtLowerLowerBuffer); SetIndexShift(5,InpBandsShift); SetIndexLabel(5,"Bands Outer Lower"); //--- remind myself which is which so I don't forget later: sell signal is INDEX 6!!!! SetIndexStyle(6,DRAW_ARROW); SetIndexArrow(6,218); SetIndexBuffer(6,SellSignalBuffer); SetIndexShift(6,InpBandsShift); SetIndexLabel(6,"Sell Signal"); //--- buy signal is INDEX 7 !!! SetIndexStyle(7,DRAW_ARROW); SetIndexArrow(7,217); SetIndexBuffer(7,BuySignalBuffer); SetIndexShift(7,InpBandsShift); SetIndexLabel(7,"Buy Signal"); //--- check for input parameter if(InpBandsPeriod<=0) { Print("Wrong input parameter Bands Period=",InpBandsPeriod); return(INIT_FAILED); } //--- SetIndexDrawBegin(0,InpBandsPeriod+InpBandsShift); SetIndexDrawBegin(1,InpBandsPeriod+InpBandsShift); SetIndexDrawBegin(2,InpBandsPeriod+InpBandsShift); // hack in our additional buffers, so they also start at the corect point SetIndexDrawBegin(4,InpBandsPeriod+InpBandsShift); SetIndexDrawBegin(5,InpBandsPeriod+InpBandsShift); SetIndexDrawBegin(6,InpBandsPeriod+InpBandsShift); SetIndexDrawBegin(7,InpBandsPeriod+InpBandsShift); //--- initialization done return(INIT_SUCCEEDED); } //+------------------------------------------------------------------+ //| Bollinger Bands | //+------------------------------------------------------------------+ // all of this code is from the default indicator int OnCalculate(const int rates_total, const int prev_calculated, const datetime &time[], const double &open[], const double &high[], const double &low[], const double &close[], const long &tick_volume[], const long &volume[], const int &spread[]) { int i,pos; //--- if(rates_total<=InpBandsPeriod || InpBandsPeriod<=0) { return(0); } //--- counting from 0 to rates_total ArraySetAsSeries(ExtMovingBuffer,false); ArraySetAsSeries(ExtUpperBuffer,false); ArraySetAsSeries(ExtLowerBuffer,false); ArraySetAsSeries(ExtStdDevBuffer,false); // hack in to make sure our custom buffers run in the same direction ArraySetAsSeries(SellSignalBuffer,false); ArraySetAsSeries(ExtUpperUpperBuffer,false); ArraySetAsSeries(ExtLowerLowerBuffer,false); ArraySetAsSeries(BuySignalBuffer,false); ArraySetAsSeries(close,false); ArraySetAsSeries(high,false); ArraySetAsSeries(low,false); //--- initial zero if(prev_calculated<1) { for(i=0; i1) pos=prev_calculated-1; else pos=0; //--- main cycle for(i=pos; i After a bit of tweaking typos, the indicator now displays two sets of bands, one at 1x SD and one at 2xSD from the mean (moving average). It also has two buffers that will use the DRAW_ARROW style to mark out potential trades.
 Adding trade logic
 I still can't decide if it's better to isolate the logic code in the Custom Indicator or the EA, in the long run. There seem to be performative, stylistic and redundancy issues, but for the moment the project is to put the logic in the Indicator, so that's what I did.
 The fastest way to prototype this idea seems to be identifying when price closes outside of the far band. 
 This is trivial to achieve. We compare the close to the two outer bands, and if it's outside them, then we set the relevant trade signal buffer.
 //
  double tempclose = close[i]; if(tempclose>(ExtUpperUpperBuffer[i]+10*Point)) { SellSignalBuffer[i] = high[i]+(20* Point); } else { SellSignalBuffer[i] = 0; } if(tempclose<(ExtLowerLowerBuffer[i]-10*Point)) { BuySignalBuffer[i] = low[i]-(20*Point); } else { BuySignalBuffer[i]=0; } } 
 It works!
 http://i.imgur.com/Ak3UkkK.png
 Green arrows successfully mark out possible sell entries where price closes above the top band, and red arrows mark out possible buy entries when price closes below the lower band. 
 The logic can be a lot more complicated than this obviously, but the point of my project is to develop the iCustom technique, rather than make a good autotrader.
 Now it's time to switch to the EA.
 part two to follow

A Forensic Approach to Trading: Examining the FOMC release.

It's a truism in trading that your strategies are worthless unless they pass the test of the market. They either make money in the long run, or they don't. We have a hard, factual standard we can hold matters to.
When it comes to theories about what is happening in the market, it's much harder to apply similar standards because many things don't appear on the charts. However, this often means we fail to even try.
This is bad practice. We should be willing to challenge our own, and other's theories about the market, as well as investigate out-of-the-box theories, by comparing them to available chart evidence.
Edit: squitstoomuch has drawn my attention to the fact that my analysis and understanding of the situation has some serious, if not fatal flaws. Rather than delete the post, I'll leave it up because looking at other people's mistakes is often useful, and it's still a good idea to compare your ideas to the charts and see if the market validates them. Grossly incorrect stuff has strike throughs, the rest still stands.
For example, a very common analysis you will hear after the combination of rate decision and Governor press conference is that the overall direction of movement can be accounted for by what was said in the conference.
~~This is something you can assess by looking at the charts.~~
Proposition 1: The USD fell largely due to Yellen's comments implying future rate trajectories
Consider:
M1 EURUSD http://i.imgur.com/MS7ceQf.png
M1 USDJPY http://i.imgur.com/JeHI8qw.png
You can see that the majority of the price movement against the USD happens within the first ten minutes after the rate release, and within that, the majority of the move happened within the first minute.
~~Logic dictates that NONE of this movement was related to the content of the speech, simply because the speech had not been given yet.~~
You can also see that although there was movement throughout the speech, it managed to only depress the USD an additional third compared to the rate release.
~~How you choose to interpret this is up to you, but at least you can now frame the 'it was Yellen's speech that did it' theories in the context of some irrefutable evidence.~~
My personal interpretation is that whilst the speech content strongly influences price, and did further depress the USD, it was not the original motivator for the drop. Nor was it the main determinant of the magnitude of the drop in the value of the USD, because both of those happened before she ever opened her mouth. ~~
Let's look at some more propositions.
Proposition 2: You should trade what happened last time
USDJPY H1 chart from 14th December 2016, the previous time rates were raised. FOMC raises Fed Fund Rate, USD goes:
http://i.imgur.com/qL7upT7.png
... up. So if you had simply looked at what happened last time, and then bought this time, you would have lost money. I'm going to strongly recommend that nobody short the USD for the next rate hike just because it went down this time!
Proposition 3: You could have just predicted the movement on technicals.
Well...
http://i.imgur.com/zYOlVmw.png
... as it turns out, one of the most basic, elementary technical strategies (trendline + horizontal resistance) would have gotten you in nicely this time, at least on USDJPY. The EURUSD set-up was a bit more advanced, but still straightforward in the context of the essentially guaranteed rate decision.
http://i.imgur.com/L8B7s1K.png
Interestingly, pivot points perfectly predicted the extent of the day's price movement this time round.
USDJPY (D)
http://i.imgur.com/emY42Nn.png
EURUSD (H1)
http://i.imgur.com/fD8UDss.png
(Note the different timeframes. This may just be a case of coincidence, but I will say that ever since I put them on my charts, they've been very useful for exactly this sort of thing: how far the market will go before a pause or a retrace).
Proposition 4: the market is irrational and unpredictable
I don't have any strong evidence to disprove this, but I will say that the NFP price action was a big red flag that something like this was going to happen on FOMC day, and that there are clear, strongly repeatable analytical approaches that predicted an outcome like this. Many people were not the least bit surprised.
^{^{^{^{^{^{^{^{^{^.}}}}}}}}}
Finally, I'd like to suggest that this is much more than just "pricing in". I don't have the time nor patience to go through my archives and dig out every "priced in" economic release that I've ever tried to trade, so I'll leave the evidence hunt for those more curious.
But in my experience, when the market has priced an event in, and that event happens, the usual result is ... nothing. This is what 'pricing in' means, that price is already correct in regards to that information.
If anything actually happens, it's usually counter-intuitive, and that means that the big banks are using the event to hustle price about.
As a footnote, that's not the only way they hustle price. One thing they also like to use talking heads to influence market sentiment: http://news.forexlive.com/!/goldman-sachs-see-a-second-fed-hike-in-june-20170310 (This bulletin is saying there will be faster rate hikes, ie investors should buy USD. You might wonder why Goldman would risk their reputation by putting their name behind directions they're not trading, and the easy answer is that nobody remembers these bulletins, but everyone remembers the end of year profits of the bank. Bank mouthpieces aren't there to help the clients, they're there to help the bank)

Some potential market movers coming up tomorrow

How Does Non-Farm Payroll (NFP) Affect Forex Trading By Daffa Zaky January 18, 2019, 5:07 pm • Posted in Education In the U.S., nonfarm payroll data is released every month on the first Friday. The NFP Trading Strategy . The NFP report generally affects all major currency pairs, but one of the favorites among traders is the GBP/USD. Because the forex market is open 24 hours a day, all ... NFP STRATEGY FOR TRADING FOREX. Now we are going to discuss what an NFP strategy for the Forex market could look like. Please be aware that it is crucial for every trader to do their own demo testing, backtesting, paper testing, etc before trading live. Past results do not guarantee similar outcomes in the future. The Nonfarm Payrolls (NFP) are among the biggest market movers in the Forex markets and probably the most-watched Forex news item, together with central bank events or interest rate decisions. Although their impact seems to be decreasing over the last few months. NFP and Forex Trading: MAIN TALKING POINTS. Non-Farm Payrolls (NFP) releases create volatility in the forex market. NFP measures net changes in employment jobs. Forex traders use an economic ...

Forex NFP Trading Strategy That Works - YouTube

Trading the Non-Farm Payrolls. by Steve Ruffley, day trader. You successfully trade off news releases such as the non-farm payrolls. People expect data to be black and white these days but this is ... Discover how to trade NFP like a pro without killed by the markets. Here’s the thing: Many traders are lured into trading the news because you can make profi... How to Trade NFP News [100% profit] The non-farm payroll (NFP) report is a key economic indicator for the United States. It is intended to represent the tota... LIVE Forex Trading - Non-Farm Employment (NFP) Day - December 6, 2019 ... (forex). Subscribe to the channel and join us. ... You will quickly learn once you are successful how meaning comes from ... Non Farm Payroll (NFP) is one of the biggest news that can move the Forex market. This video discusses 5 simple steps to trade the NFP report. The topics cov...

Time	Event	Forecast	Last
0830	Non-Farm Employment Change	227K	126K
0830	Unemployment Rate	5.4%	5.5%
0945	FOMC Member Dudley Speaks	.	.

Trading the Non-Farm Payroll Report

Former investment bank FX trader: Risk management part 3/3