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

Former investment bank FX trader: Risk management part 3/3
Welcome to the third and final part of this chapter.
Thank you all for the 100s of comments and upvotes - maybe this post will take us above 1,000 for this topic!
Keep any feedback or questions coming in the replies below.
Before you read this note, please start with Part I and then Part II so it hangs together and makes sense.
Part III
  • Squeezes and other risks
  • 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.


Economic releases can cause large short-term volatility. The most famous is Non Farm Payrolls, which is the most widely watched measure of US employment levels and affects the price of many instruments.On an NFP announcement currencies like EURUSD might jump (or drop) 100 pips no problem.
This is fine and there are trading strategies that one may employ around this but the key thing is to be aware of these releases.You can find economic calendars all over the internet - including on this site - and you need only check if there are any major releases each day or week.
For example, if you are trading off some intraday chart and scalping a few pips here and there it would be highly sensible to go into a known data release flat as it is pure coin-toss and not the reason for your trading. It only takes five minutes each day to plan for the day ahead so do not get caught out by this. Many retail traders get stopped out on such events when price volatility is at its peak.


Short squeezes bring a lot of danger and perhaps some opportunity.
The story of VW and Porsche is the best short squeeze ever. Throughout these articles we've used FX examples wherever possible but in this one instance the concept (which is also highly relevant in FX) is best illustrated with an historical lesson from a different asset class.
A short squeeze is when a participant ends up in a short position they are forced to cover. Especially when the rest of the market knows that this participant can be bullied into stopping out at terrible levels, provided the market can briefly drive the price into their pain zone.

There's a reason for the car, don't worry
Hedge funds had been shorting VW stock. However the amount of VW stock available to buy in the open market was actually quite limited. The local government owned a chunk and Porsche itself had bought and locked away around 30%. Neither of these would sell to the hedge-funds so a good amount of the stock was un-buyable at any price.
If you sell or short a stock you must be prepared to buy it back to go flat at some point.
To cut a long story short, Porsche bought a lot of call options on VW stock. These options gave them the right to purchase VW stock from banks at slightly above market price.
Eventually the banks who had sold these options realised there was no VW stock to go out and buy since the German government wouldn’t sell its allocation and Porsche wouldn’t either. If Porsche called in the options the banks were in trouble.
Porsche called in the options which forced the shorts to buy stock - at whatever price they could get it.
The price squeezed higher as those that were short got massively squeezed and stopped out. For one brief moment in 2008, VW was the world’s most valuable company. Shorts were burned hard.

Incredible event
Porsche apparently made $11.5 billion on the trade. The BBC described Porsche as “a hedge fund with a carmaker attached.”
If this all seems exotic then know that the same thing happens in FX all the time. If everyone in the market is talking about a key level in EURUSD being 1.2050 then you can bet the market will try to push through 1.2050 just to take out any short stops at that level. Whether it then rallies higher or fails and trades back lower is a different matter entirely.
This brings us on to the matter of crowded trades. We will look at positioning in more detail in the next section. Crowded trades are dangerous for PNL. If everyone believes EURUSD is going down and has already sold EURUSD then you run the risk of a short squeeze.
For additional selling to take place you need a very good reason for people to add to their position whereas a move in the other direction could force mass buying to cover their shorts.
A trading mentor when I worked at the investment bank once advised me:
Always think about which move would cause the maximum people the maximum pain. That move is precisely what you should be watching out for at all times.

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.
submitted by getmrmarket to Forex [link] [comments]

Conflicting BTCUSDT historical Data from Pinned Post

Hi all. I followed the pinned instructions on how to download historical btc data, but I am seeing a discrepancy. I pulled minute data from August and compare recent ticks to binanance.com and the data is different as you can see in the screenshot below. Has anyone experience this before?

submitted by RobsRemarks to algotrading [link] [comments]

Where to get historical intraday stock data?

I hate to ask questions that have been asked before. But I am afraid that this is one of them. I have searched the web for days now, read so many forum posts. But I can't find an answer. Most answers about historical intraday data were about sites that offer historical futures and options, but I don't need those (btw. why would you want to use options data, which is derived from the stock data, instead of the actual stock data?).
What I need is historical intraday stock data: At least S&P 500 stocks, dating back 5 years, 30 minute interval (or smaller), a weekly update, OHLC would be nice, but only one of them (close for example) would be sufficient. I need to be able to download the raw data, that means that I can't use something like Quantopian. So the data either needs to be downloadable (like a ZIP folder) or have a python API, so I can download it with the API.
I know, something like this is not free, I would be able to spent up to about $50 a month. I am still a student, so I can't afford much more than that. What I found so far is Kibot and QuantQuote.
Kibot: They seem to have a bad reputation. It seems that their stock data is either inaccurate, or incomplete. I just don't know if this still applies to the last 5 years. Since their data dates back to 1998, I could imagine that they had issues in the beginning but fixed them since they have been in business for more than 20 years. Their Standard subscription costs $49/month and includes 1 minute intraday data for all their symbols (6500 stocks, + ETFs, Futures and Forex) with a weekly update dating back 1 year. So I would also need to purchase once their historical S&P 500 data with a 30 minute interval, dating back to 1998 (I would need 2015 and up) for $150.
I can handle slightly inaccurate data (for example if the pricing is off by 0.5% or something like that), but missing data or inconsistent data (for example if instead of a constant 1min interval, it sometimes jumps multiple minutes) is a problem.
QuantQuote: They are expensive, too expensive. I would need to purchase once their S&P 500 package for $895 and then $50/month for a weekly update. They seem to offer the same as Kibot, but for a much higher price and with a higher quality (I assume).
It would help a lot, if you could say something about Kibot or Quantqote, or just about buying historical intraday data. Maybe you know better sites? Or do you know where to look or ask?
Any comment is appreciated!
submitted by rndmnewguy to Trading [link] [comments]

How to derive historical financial data for forex instrument backtesting

If you believe backtesting strategies for forex major currency pairs is unhopeful please leave a comment with an explanation.
I'm a CS major at Columbia with internships in back office global bank infrastructure positions here in NY and have great interest in trading algorithmically because I can't trust my behavior to enter trades, among other obvious reasons.
I would like to know what the best sources are for obtaining historical data (OHLCV, etc) for (forex) backtesting purposes. Is a large excel file used in practice, or are historical prices derived via API's? It seems that I need to pay after some research online, but I know you redditors can deliver.

I found a free source here for EURUSD. There are other pairs available too.
submitted by Reciprocates to algotrading [link] [comments]

You can use TD Ameritrade's real-time equity data for free, for paper trading without the 20-minute delay.

In case people didn't know, if you use a platform which "contains" a paper trading acccount, rather than relying on the TOS platform entirely, you can take advantage of the free real-time US equity data for paper trading. So to keep this simple you can get NinjaTrader for free here, it's generally considered a free platform for those who didn't know. https://ninjatrader.com/FreeLiveData When you get NT through this method, you can pick Futures or Forex data. You can go back and fill out each one if you'd like say, do Futures first (that'll be through CQG and give you a lot of data for 7 days or 14, I can't recall) and the Forex through FXCM. Regardless, you don't have to use either one if you don't want. After that you'll be able to download NT installer, I always go with NinjaTrader 8, it works well. Rather than 7, that is.
Simply click "connections" in the main panel once it's open, and add a TD Ameritrade connection with the same login/pass you'd use to login to TOS or your TD/AT online account.
One important thing to note: If you want tick data, at the least NinjaTrader will say give you 10 tick, 2, 1 tick or even intervals like 1s (literally type 1s or 10s or 1t 3t 10t etc and hit enter when you have a chart open) but I believe it's derived from the bar data, if that makes sense. Also if you're viewing anything less than the 1 minute bar timeframe, itll just start off at the time you've opened the chart with such tick/second/range/interval data, and no historical on the chart. So if I'm doing that I like to open a second chart in another tab of the same instrument to show the historical data.
So the paper trading account is within the NT platform, and so long as you make sure you have set up your default account to be say Sim101, the usual name of the default paper trading account, you won't be actually executing trades through the TD Ameritrade broker, but you get to trade on real-time data.
Between this being free data, the possibility of using Rithmic, CQG and FXCM trials for futures and forex, you can get basically all free data. For a paper trader like me, that's nice because I have no skin the game... I think that's the saying.
Keep in mind I'm not promoting NinjaTrader in any commercial capacity and have no affiliation with them whatsoever as a company or in any manner I can conceive. There's one other platform I use which isn't free that's compatible with TD Ameritrade's data and that's called MotiveWave. It also does support simulated trading very very well. I suggest checking it out and I'll just say Google MotiveWaveTM 4.2.8 Ultimate Edition ;) Hope this isn't just old news everyone here has known. If so, let me know. Happy trading and hope this coming trading week is a good one.
Edit: Some other resources which at least have free trials available without necessarily needing any payment info I find useful are: 1) www.livesquawk.com (Especially Steve K's market signals... I've only heard of McAffe's signals but never tried them, however Steve K is a good guy and seems to really know what he's doing. Tl;dr, they work for me in paper trading).
2) https://www.tradethenews.com - you need a linkedin with 5 or more connections to get the free trial but they have a great squawk service with a guy from NYC who seems to be on literally almost 24 hours a day 5 days a week.
3) https://pro.benzinga.com - a Bloomberg Terminal alternative basically, but not as fancy... for more fancy see:
4) http://www.metastock.com/fundsoft4 This one isn't really explained the best on their own site, in my opinion but I've been using the free 30 day trial and what it is, is Metastock's own way of selling Reuters Eikon service. Eikon is about the best Bloomberg Terminal alternative I've found yet in many years of searching. I'm more into looking at data and figuring out how plats work than the actual trading in some ways. Important note on this one: Once you do have a trial, and they take a little while to rubber stamp it so be patient with the emails they send, you can login through the regular Reuters Eikon web login if you wish rather than using the Windows standalone program. They're the same one's just web-baed.
5) Lastly for now, https://www.money.net - definitely worth checking out. Has it's own live squawk for news during trading hours and definitely no payment info needed for a trial. You can login once trial acquired via login.money.net or the now 'legacy' installable platform. They're both good but I'm not crazy about the iOS/Android versions at all.
submitted by FraterThelemaSucks to stocks [link] [comments]

How can I get this code to work, I want to have a closure function return an object to access private functions?

Ok so I am pretty new to Go since I have been learning for about 2 days, so I apologize for the super basic question.
So anyways right now I am trying to build a micro service that streams fake simulated stock data via web sockets to a client. The data used is essentially a months worth of historical m1(minute bar data) i got here. The data is stored in redis as a JSON object that is an Array of floats [1081.8, 1101.2, 1060.1, 1090.2] which is the exchange rate of EUUSD (multiplied by 1000) of that current minutes Open value, Highest value, Lowest value, Closing Value, but I stream these points 10 times a second from a Node.js service I spun up, the timestamps are created on the client side since it's a simulation.
Here Is what I do with the data Fake early build of sample trading platform
For the Go Service here is what I have:
This is the Main package on github
This is the closure object thing I am trying to make SymbolSock I uploaded it in github so that comments are easier to read, since it explains what each function/struct does.
symbolHandler explained:
When a client sends in a request to subscribe to a Feed such as GBP/JPY a new struct instance is created called symbolPush
type symbolPush struct{ symbol string clients int feed string lastV float32 atIndex int } 
a SymbolPush instance stores an index atIndex which is the index of the shared dataset, it's symbol (which is like it's namespace/websocket channel) and the last closing price.
Also I have a scale-like case class: Which is used by a function I append to the symbolPush struct to send out an instance to be eventually stringified like this conn.WriteJSON(the return value)
 type seriesPoint struct { Symbol string `json:"symb"` LastValue float32 `json:"lastVal"` MinValue float32 `json:"min"` PointData OHLC `json:"data"` } func (s *symbolPush) GetPoint() seriesPoint { s.atIndex++ lastVV := s.lastV if(s.atIndex == (len(dataPoints) -1)){ s.atIndex = 0 } //index 3 is the close value s.lastV = dataPoints[s.atIndex][3] minVal := dataPoints[s.atIndex][2] return seriesPoint{ Symbol: s.symbol, LastValue: lastVV, MinValue: minVal, PointData: dataPoints[s.atIndex], } } 
Now right now it's obvious I am not returning anything that can be used from symbolsock since last night I deleted my old code since it wasn't working and just left it incomplete since I feel I would like to hear some input before I do a sloppy solution.
What I want to have returned from symbolsock is essentially an object that can do this:
call the closure function with the JSONblob and return an object like seriesSockets := symbolsock.SymbolStream(theData)
Use this object to seriesSockets.joinStream("APPL") which will call newStream function in symbol sockets, either creating a new struct or incrementing the clients field.
signal when a user has unsubscribed to a feed, which will delete the feed if clients == 0
get a point from these structs to be broadcasted to subscribed clients like seriesSockets.getSeriesPoint("APPL")
So my main question is how can I return an object like seriesSockets that accomplishes these things?
Oh here are the Go Playgrounds: main symbolSock
Also for readability here are is the github repo
Also I should mention I asked a question earlier which I will get back to once I have more information, but they're related.
submitted by TheBeardofGilgamesh to golang [link] [comments]

What is the best source of minute historical data?

I am thinking from minute to minute, many years back.
currency rates
I found this and seems to average about 2 values per minute
What do you guys think?
submitted by Oddstrider to Forex [link] [comments]

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