My Forex Secret: How to trade Forex to get rich and make others jealous!
Think of war or massive financial crisis. The one problem with the Swiss Franc as a safe haven currency is that the central bank takes an active role in deterring people from buying its currency. The Swiss national bank has no issue with manipulating the price of their currency at any time without warning to the market. Another Interesting point, at the time of this writing the SNB actually have a negative rate of interest which means that investors have to pay to own Swiss Francs.
However, in times of mass panic investors have shown that they would pay a negative rate in order to keep their capital safe. When there is a financial crisis the U. This makes the U. The one problem facing the U. This has the potential to cause the U. Because of this the USD is generally the least attractive safe haven currency in the markets for shorter term safe haven flows. However, in major global recessions, such as the financial crisis of , the USD has shown that it will appreciate over longer term safe haven flows.
For shorter term immediate safe haven flows the market will buy up the Japanese Yen. For longer term fears and panics the market will look to buy the Swiss Franc and the U. Buy the rumor sell the fact is one of the more common types of sentiment that you may have heard about before. Buy the rumor sell the fact occurs when the market has a strong expectation of a certain outcome and then trades in line with that expectation before the particular risk event. A risk event is any piece of economic data or news that is scheduled to come out and is considered to have potentially high impact on prices of currencies in the Forex market.
How long the market will buy the rumor before the factual piece of data is released will all depend on how high impact the data is. The market will then trade with its expectations ahead of the expected event, and if it is what the market expected, the market will abandon the trade and the price action reverses as traders start taking profits from the nice profitable run up into the risk event. Imagine that the market is anticipating that the Bank of Canada BOC , the central bank of Canada, will increase its main benchmark interest rate at its next rate decision announcement.
Speculation started about 2 weeks before the rate statement and there have been various leaks to the press about the fact that the hike is going to happen. In fact, the bank of Canada themselves have come out with some strong wording that a hike is potentially coming soon. What will happen in this type of scenario is that the price of the Canadian dollar will rally as speculators start piling into the Canadian dollar well ahead of the actual rate decision.
As the rate statement approaches the market has done a good job of fully pricing in the rate hike. When the actual event happens, and the BOC does indeed hike interest rates as expected, what you will likely see is instead of the market buying up Canadian dollars the market begins selling them off. News traders get squeezed out of their long positions that they entered just after the announcement and end up losing money as the price goes opposite to what they thought it should or expect it to be doing based on everything they have learned about the Forex market.
Higher interest rates are supposed to be positive for a currency. So what happened in this example? The market had been so confident that the rate hike would happen that they started positioning themselves long before the interest rate hike had been confirmed by the Bank of Canada. When the time came for the hike the market was already in profit and decided to book those profits rather than risk getting into a new position.
When done in enough volume, this profit taking can actually move the price of a currency significantly. This is often seen at the end of large moves or at key support and resistance points in the trading session. As the rest of the market catches on to the fact that this has become a buy the rumor sell the fact type move they now start selling the Canadian Dollar to try and take advantage of this fact which of course pushes the currency even lower. This can be a very frustrating for many traders because the price action goes the opposite way that it should based on the information that was just released.
But what the trader fails to realize was the large move that took place for a couple weeks going into the risk event. This is buying the rumor and selling the fact. It defies logic at the time but when you go back to the past it makes a lot of sense. The market is a discounting mechanism after all. Value trading happens when value traders enter the market looking to position themselves in line with the long term fundamental trend.
They look to do so when the shorter term sentiment has moved price in the opposite direction of the actual fundamental trend. There will be many traders watching these developments to try and use the pullback as an opportunity to get back into the market at better price. Everybody loves a good discount! The only reason they can do this is because the sentiment has taken price to an attractive point where it makes sense to get back in the trade in the direction of the big picture fundamentals. But, the big question is when would they want to do this? However, 1 bad piece of economic data in a long series of very strong data points does not change the overall trend; it merely will cause a short term pullback.
This is a great value trading situation because the fundamental trend is still intact but you now have a discount to get in at better prices. Value traders can be classed as some of the largest hedge funds, banks, and financial investment houses in the world. Many funds are so large that they must become value traders because they need to have a longer term outlook. They need to have this longer term outlook because they have a huge amount of financial assets that are too large for shorter term trading.
These value traders look to get into a trade with the expectation of the fundamental trend resuming at some point. In some situations it could be that they are simply adding to an existing position at a more attractive price. A good bargain is hard to resist! When there is enough money behind this type of trading activity it effectively ends any type of short term sentiment against the fundamental trend that may have been in control up to that point.
The further the short term sentiment has taken price away from the fundamental trend direction the more likely it is that value traders will look to get back into the market and hunt for a good bargain. Value traders will typically be on the hunt if price has moved significantly beyond the average daily range. They will be even more likely to hunt for a spot to get in if the pair has moved significantly over more than a single session. This can sometimes lead to sharp reversals back in the trend direction. You identify this type of sentiment at times when you can see price has pulled back against the overall fundamental trend because of some short term sentiment that the market has over focussed on.
Many of the largest funds in the world use value trading to one degree or another in their investment mandate so you know that they do definitely have the power to move the market if enough of these traders decide that something has value at its current prices. Every trading day we have many different types of option contracts expiring at many different times against many different currency pairs. But how do they move the price of the currencies? In simple terms, the option price can act like a magnet at times. There are indeed many variations of how options are structured but for the sake of simplicity we will stick to plain vanilla options because they are the most widely used and tracked by the Forex market.
What we are looking out for is the price action leading up to the If there is an expiry of a big option of, say million or larger, then this will bring the markets attention to the price of the option. If the expiry price is close to where the market is currently trading, say 30 to 50 pips, then the price may be drawn to that option expiry level. There are a few things that may happen when there is a large option expiry leading into The price may head towards the price level. This could be because the buyer of the option contracts wants to cash in on their bet. The only way they can do that is if they push price to the price level.
If it is a big enough payoff then it makes sense to use some more money and push price to the level. Price may reject strongly off the price level. This could be because the seller of the option contract does not want to payout the money so they defend the price level by pushing price away from that level. When price gets to the level it may not move too far beyond it as the buyers and sellers fight it out.
This means that the battle between the winning and losing party is over and price is free to move without any intervention from either of those parties. The impact of an option expiry will largely depend how big it is. However, if price is nowhere near the expiry level then the prevailing market sentiment will likely be the main driver of price action. You can see these expiry levels posted in the news feed at Forex Live. Once you note where the large levels are you can mark them on your chart and spend a little bit of time watching how price reacts to help you learn how you might possibly take advantage of these events.
At some point price is going to need to take a breather and retrace some of the previous move. Traders love to ring the register and there is no better time than when the market has given them a nice extended move. As the market continues to move in one direction for a long enough period of time, more and more traders are going to start getting itchy fingers. The more price rallies beyond the average daily range, the more likely it is that traders will start taking profits. In order for the trader to take a profit they must sell what they already own.
When enough traders start selling their long positions then this can cause the price to retrace. This is profit taking in its most basic form. However, if you do get a profit taking retracement, and the sentiment has not changed from the original move, then this is a new buying opportunity to get back into the trade at better prices once traders finish taking profits.
Profit taking is interesting because it is a sentiment created from a previous sentiment. It is a sentiment created from the previous sentiment that moved prices far enough to create the need to take profits…. The very best sentiment trades happen when the current sentiment of the current trading session is in line with the big picture fundamentals.
Said another way; the mood of the market today compliments the long term fundamental economic direction. These are great trades because you have the power of the longer term investors who are using the fundamentals and the shorter term hedge fund traders using the sentiment to get into or out of their trades. Together they are all happily pushing the price in the same direction which can make for some great price action to take advantage of.
This is a time when you can make a lot of pips very quickly with trades that might not try to go against you very much if you have picked a good entry point. This is where you might want to use some well thought out technical analysis to time your entry. Again, technical analysis will help you time your entries. These are the type of trades that tend to last longer and move more in terms of pips because most of the market participants are thinking of trading in the same way. There is another situation where the sentiment and the fundamentals are actually opposite each other.
These are counter-sentiment trading opportunities because they are kind of like saying counter trend to the fundamentals. Allow the negative sentiment to bring price back to where it makes fundamental sense to start buying again in line with the big picture think buy the dip value traders. Trade the negative sentiment short against the positive fundamentals. This is where knowing how strong the sentiment is will help you make some profitable trades against the big picture fundamentals.
These tend to be shorter term trades with higher risk. Trade the positive sentiment long against the negative fundamentals. The sentiment trades that are against the fundamentals tend to be the trickiest. These are the trades you might want to stay away from until you are comfortable that you have a high level of skill when it comes to trading and understanding the sentiment situation that is active in a live market. There are no mechanical rules regarding how to trade sentiment. Trading sentiment is more of skill that is honed and perfected by spending time with the market and getting to know its moods and behaviours that it has when certain events that happen.
Sentiment can last for an hour, a day, or even months depending on what is causing it and how relevant the market believes the cause for the sentiment is to the current economic situation. Once the news is out the market will then create a new sentiment based on what actually happened with news event. An interesting thing about sentiment is that sometimes the market reaction to a certain event will be quite strong but then a few weeks later the exact same scenario will occur and the market will hardly produce the slightest move.
The Forex market tends to become desensitized to information the more that it hears it. This can cause a lot of frustration for traders that are not staying properly tuned into what is currently driving prices in the Forex market. A lot of what will cause things to change with sentiment is what the expectations from the market are.
As we know, the market will always react more to information that is not known or is unexpected. Once the information is known to the markets then the price swings will become far less because the market has attempted to price in the information already. Old news is old news and the market continually wants to be given new information to drive prices.
Sometimes the market will be focussed on one thing but then something else happens and the original thing the market was focussed on is instantly forgotten. On other occasions the sentiment will last for weeks as the market becomes more and more obsessed with a certain piece of information as it continually tries to price that information in. One way to try and understand the Forex market is to think of the market as a living breathing person because it will often display human emotions of fear, greed, and irrational behaviour.
Hopefully this article has done its job to provide you some useful information on what sentiment trading is and some of the way sentiment works in the Forex market. Yes this is the point I was going to write myself. The way I structured my bankroll made it actually impossible to go broke as well. Stop-losses are not as effective or nearly as simple as they are described in typical financial media. I don't get that. It would be true if he just made a few trades, but the author claimed to be making trades a day. Over a period of months winning that wouldn't qualify as blind luck.
Definitely not blind luck; but boosted by the fact that SPY was on a massive bull run at that time. This is really cool, any way you cut it. DanBC on Nov 6, He doesn't say what his daily volatility was, but let's assume 2k which squares pretty well with his claim that his worst day was a 2k loss. I'll use a t-distribution with 3 degrees of freedom, which allows big up and down swings again, accentuating the effect of luck. And remember that this simulation is overestimating the effect of luck.
By that definition you could start claiming everything as blind luck. Why bother doing anything at all, let luck do the work. I don't have much experience with finance or working experience with machine learning, but I've always wondered how much room there was for a clever amateur to profit in this space, even as it's crowded with much more sophisticated professionals with much more sophisticated algorithms and machines. He talks about a chess tournament in which it was "anything goes" The expected outcome was that a grandmaster using a Deep Blue-like computer would win, but the winners ended up being a couple of amateurs with three computers: The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time.
So in HFT, how much room is there for an amateur to profit over professionals by having a sophisticated process? Good point, I also wonder about the potential to exploit the algorithms used by the "professionals. Its hard to be optimistic about these two ideas because while the chess example is a good story, its not analogous for many reasons, ranging from disparity in available information to players to a difference of several magnitudes in saturation. Not to mention HFT just isn't chess. So 'theoretically', they've already done what is being suggested here. If someone comes along and develops a winning strategy, it really shouldn't be considered as having anything to do with 'professional strategy vs novice strategies'.
It would just be about one person either getting really lucky or coming up with something that is genius in its own right. Theoretically, there should be no other possible strategies. Inevitably someone will come up with one though, and the 'sample space' will grow. But its extremely unlikely that additional unique strategies are successful just because they 'counter' the strategies in the sample space. But then again, this is real life and these things aren't impossible. There is an air of either incredibility or sheer jealousy in these comments.
Nevertheless, I just wanted to tell the OP that he did a great job. I work in the finance industry as a quantitative software developer, and it certainly is not an easy job for one person to do. In fact, I tried independent of my professional work doing this myself, and I ended up losing a lot of money. If people are trying to do this, please please be careful. Big companies, like ones I have worked at, have technical and human resources that are vastly more powerful.
Great work, very interesting to me. Counter to what we're constantly told through the media this stuff can be done. Doing it year after year seems to be the elusive part. I developed a fully-automated low-frequency stat arb system that I ran in based on a perhaps even simpler algorithm. It traded various equities equally to the long and short side regardless of market conditions so widespread rally or collapse was irrelevant. Month-to-month the results were very consistent until the uptick rule was nixed in July August was a record winner for me, but Sept-Dec fell flat, not losing, but with greatly diminished profits and the same variation and more frequently getting slammed all-long or all-short instead of a mix that was often near-neutral.
Also getting fills better than my orders then completely disappeared, as this was the beginning of the HFT middlemen - including your own brokerage. I shut it down at the start of , keeping the profits intact and moving on to other priorities. I continued to monitor the theoretical results for a couple of years but the conditions didn't return so I eventually cancelled my data feed. Being pedantic, trades a day isn't HFT.
This is stil algo trading, of which HFT is a subset. I consider HFT to be any strategy where speed itself is the what gives the edge. Colocation is usually a prerequisite, though not sufficient. It's a shame HFT gets all the attention, when it's really a tiny portion of trading activity. Also limiting trades isn't really adequate risk management. The tech exists to very accurately model your exposures. This is something I see underdeveloped a lot, and what separates the top trading firms from the rest. Still I commend you creating a model, working out how to test and execute it automatically and actually trading your own money.
I really think more hackers should be actively managing their money, in general, not like in the article. In the US, HFT is mostly synonymous with "all out tech war, flooding the order queue so your less-equipped peers get lags". Nanex publishes analysis on these events, which are not occuring several times a month and keep accelerating.
That's basically what AIG did with copulas. Unfortunately, the assumptions in these models tend to break during crisis, when correlations go to one. And AIG went bankrupt. With more assumptions, you can have "more efficient" risk management in terms of leverage e. Some US venues impose fees for having low fill rate. As far as I know, most US HFT firms' strategies are not based on creating latency by rapidly submitting and canceling orders, but the bad behavior of some players is much more visible than the orderly behavior of others.
When I say limiting trades, I mean naively saying 'I will have at most x positions outstanding'. Each trade has an associated risk variance , that interacts in complicated ways in a portfolio, which I'm sure you know. You need to have a risk budget, account for each trade, and work out the risk for the composite portfolio. Obviously this is not fool proof, but it's a way better approximation of the real world.
And assumptions about this are bound to break at the most inopportune moment, see e. AIG, which I already referred to. Read about the "copula model" disaster, as your statement indicates you are unaware of its details. Otherwise, you have counterparty risk. However, since this is in different exchanges, it might happen that during a flash crash, your SPY position will be liquidated for insufficient margin at a low price, but then the price bounces back, and you've lost money on a perfectly hedged position.
OP's model limiting exposure and assuming the worst, if I understand correctly is not statistically efficient use of margin, but it's way better at actually managing risk than any statistical model. I don't know the exact definition of HFT but I did run my algorithm from a server collocated with my broker close to the exchange. I modelled lag time in simulation and not having it collocated certainly would have hurt.
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Take a look at the VIX from until today and you'll understand why you stopped making money. Without a ton of volatility, any homebrew HFT is going to lose to commissions and spread. Basically, he was trading in one of the few periods where is was possible to make money. I've been considering trying HFT myself for a while. I'm competent with Machine Learning and am a Software Developer by day, so I can program and can sysadmin well enough to get something up and running without any trouble at all. But, every time I've tried to actually get started, I've always found the amount of research required before being able to begin is just staggering.
It seems like the logical course of single-programmer HFT trading being: However, the first step and the third step seem like the ones which require the most research. Is there somewhere which has a straightforward dump of timestamped market data available to download free or not , in order to actually develop a working program?
Likewise, figuring out what to actually trade with, and which service to use is also pretty taxing. Nothing in HFT is free. People doing this for a living use precision time protocol in a colocated data center to build their own timestamps. There are a couple of brokers out there specializing in the space. If the easy part was building a working model either you got incredibly lucky or the model is wrong. Quality sample data and historical data to backtest is hard. Symbols change, stocks split, dividends are announced etc. I run a 12 person HFT group in Denver.
This is an excellent description of how an individual can bootstrap themselves into success. Great story, and nicely presented. The one interesting point that he glossed over is what his indicators were. He wrote, "The indicators that were most useful were all relatively simple and were based on recent events in the market I was trading as well as the markets of correlated securities.
I'm looking back through my code and there are really a lot of indicators. It would get pretty technical to explain them. They are all explainable it's just that each one corresponds to slightly different market conditions and I just didn't want to get into it.
Most people considering trying this probably have a few ideas for indicators. But for anyone coming to HFT from a coding background instead of a trading background, an explanation of one of your indicators would have been fascinating. Yes, I would find this very interesting. Doesn't matter if the indicator is now defunct. Thanks for an excellent post. I would like to see any one indicator explained in detail as well. I am sure it would be of interest to a lot of people.
How well are you guys doing? How much money did you make? There is a coursera course called "Computational Investing, Part I" that I am taking that aims to build a market trading simulator to test a trading model. It just started so it's not too late to join. A lot of people are stating that this is like gambling - it is - but not in the sense that you think. Firstly he doesn't use his entire bankroll on each trade, secondly he goes long-short consistently over very short periods of time, thirdly he's too tiny to actually move markets, and fourthly he is in and out within a day - where his max var.
Worst case he runs out of capital over a period of weeks. He can't blow up in the way that you think - but he can have large drawdowns over a period of weeks. Markets are eventually consistent scalable systems - and that is why we prefer them over central planning. In the short term however sub-decade - they can't price jack. Oh - wait - protein folding is actually harder than that. There are 2 major ways to make money in the markets. Value-Growth and statistical arb often high frequency. And will continue to do so as long as markets exist.
Judson on Nov 6, This reminds me of an AMA from a few years ago.
Types Of Sentiment
Really interesting if you are into stuff like this: Relax with the vitriol. The guy is sharing an interesting personal story, not providing a step-by-step HOWTO or recommending people follow his suit. In fact, the article is really an ad for his startup Courseware. You are right kind of: But I've made a decision to start reaching out generally so I can attract cool people to work with on whatever projects I may be interested in in the future. By the way, no offense meant by the advertising thing. I enjoyed the article.
Although, as a technical person, would've enjoyed more details on the code and algorithms. This article is missing a crucial piece of data: This is a different style of trading than what investors do. He said that he was never more than a few contracts in. I was extremely low risk so they weren't concerned. Need to know what the starting capital was to be able to figure out if his return beat the market.
The charts show he was trading between Jun and Oct How much of his gains could be attributed to the market recovery in general? The Dow went from about to , the Russell from about to Well, in the article he said tat he did not care about direction, he would simple buy when his expected price was up, and sell when down. However, there could have easily been a bias in his model that "preferred" and performed better during upward movements. If so, he got lucky. High volatility and high volume was what it liked. I guess the real question is: I'm probably showing my ignorance here but what do you mean by alpha?
And how is it quantified? Alpha is how much excess return you had over the market or risk free return E. That is why everyone in the investment community is 'seeking alpha'. You don't need a bias to accidentally make money when the market is overall moving up, do you? Picking stocks by throwing darts while blindfolded will, on average, make you money in a market that's moving up.
The problem is he was also selling short. If you pick stocks randomly and randomly pick to buy or sell you shouldn't make money, ever.
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You're right, if you're randomly and without bias including short selling then you'd expect to neither make nor lose money, aside from transaction fees. Great point, here is a chart of the Russel , incredible growth during that period. Trade fees alone would eat a huge chunk of money.
He was trading futures. In general, futures have 1: He must make that much just to break even. You should look more deeply into how these things work. Let's take the DAX Futures for example which he was trading. All numbers are in EUR. One "tick" minimal movement is worth At volume you pay 0.
This is the cost of business. If you bought, and sold after a favorable 1 tick movement, e. If you bought and sold after an unfavorable one tick movement e. He was very smart, but you're looking at it wrong - the fees are the cost of doing business, much like salaries are the cost of producing software. You just roll the fees up-front into your choices when thinking about it, and it all makes much more sense. Not trying to take away from OPs very commendable achievement - just trying to give the common perspective on how to view this. Pls do not follow the advice of the OP. I started a hedgefund in doing HF platform arbitrage and ran it for 5yrs and i can honestly tell you that this is just survivorship bias.
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This is a very complex field and being off slightly, having a slight bias, a fraction of a point off your execution pricing and a slightly flawed money management system is recipe for disaster. The biggest issue is the confusion that you can apply machine learning to HF trading. HF trading sub 15min mark is more about playing the deal flow, and only the institutions have an edge on this.
This is why goldman had to separate the buy and sell sides in the early 's. Above 15mins you are able to find an edge using time series analyses since the market is scaling invariant according to Benoit Mandelbrot and this does not apply to dealflow. Also having access to dealflow allows you to predict volatilty seconds ahead which allows you decrease your risk and increase you reward as well as handle your costs since the volatility will impact your transaction costs even if transaction costs themselves stay the same.
There is just so much stuff to cover that a comment will not do justice in explaining what is wrong with this guys logic. There are plenty of shops making tons of money with HFT who do not have deal flow at all - it's got nothing to do with luck. Survivorship bias would mean I simply got lucky. Finally, machine learning has everything to do with my success. If you read the article you would know that I built an accurate model for backtesting that I used to optimize variables as well as confirm that I was going to make money before I even started live trading.
I'm pretty confident that whatever you were doing in has nothing to do with what I was doing. If anyone has questions for me happy to answer as best I can. I have one question: Why doesn't every hacker do this to make extra money? Is it within the grasp of anybody who can program to automate trading like this?
Sounds like it's not really for everybody. You have to own or rent a server with access to direct lines to the exchanges, or else your lag will be such that profiting from HFT is impossible. How much do these cost? I tried at one point to do it with Ninjatrader. The programming skills for the trading software is not complicated. What is complicated is tweaking it so it will make money, there are tons of indicators out there and many people have tried this with neural networks and the like.
A lot of effort is put into it. I personally thought there were smarter people than me who barely had an edge. I honestly didn't think it was within the grasp of a single programmer nowadays, but this author has proved me wrong. He of course has much more sophisticated algorithms than what I was attempting. A profitable predictor is a much, much harder problem.
At a place like Goldman Sachs, a quant with a working predictor gets paid 5 times as much as the IT guy who makes that predictor talk to the market quickly enough. Because, as your question implies, it is relatively easy to do the IT work or hire someone to do it. Not so for the predictors. At a place like Goldman Sachs, you don't need quants or predictors. You call up the CEO of a company you want to post record profits, and you tell them if they don't do absolutely desperate, self-destructive things screwing employees and customers for immediate gains , you will crash their stock and destroy their entire company.
That CEO then has a choice. Be the one who killed the company, or be the one who kept it running for a few more weeks and delivered a record quarter that made Goldman Sachs happy. Once you have the assets and capacity to actively manipulate the price of any stock at will, the market is a VERY different animal and no longer need to be understood at all. You simply force its hand. I wondered the same thing and tried to answer it for myself not that long ago. In short, it's hard, time-consuming, stressful and costly. Coming up with something that works in backtesting is easy, doing it moving forward while staying within your risk envelope and considering all the associated costs is hard.
Whatever you put together is surely going to need plenty adaptation and oversight. It's a very fluid problem, you're just one player among countless others. How much time do you have in the day? Where is your capital coming from? For most people, the source of capital is a job that they probably can't ignore while fiddling with a trading program that would have to be remarkably successful to replace that income. You need a certain amount of capital to start with and there are all sorts of running costs.
From the basic costs of execution, to market data and eventually co-location if you get that far. The fact that the OP kicked off with an amount that's essentially the barest minimum for any kind active trading is exceptional. How many people struggle to simply get up on time, control their desire to check a particular website or to get over and move on from some frustration? Even if there's automation involved, trading will test your mental fortitude. On top of that, there are quite a few risks and potential to lose a lot of money. Getting a server close to the exchange 2. Finding a good predictor.
Predicting up or down is easy on paper. Finding a predictor that a. What works a few months ago isn't guaranteed to work now. Some are better gamblers than others, but no individual can consistently have more ups than downs over a period of years. Making a living by gambling pretty much sucks, which is why most hackers don't do it. You'd think that something as complex as markets would attract hackers trying to "figure it out".
The problem is that due to the changing nature of the other participants, all hacks are temporary. Makes for great blog posts, but not a long term strategy. You are correct that no individual can. Its not heading down to the roulette wheel. If someone puts on millions of trades and wins a statistically significant portion of them you would have to say its not gambling. Its trading with a statistical edge. You have to have the capital for the server and access to the data feeds, as well as time to burn.
Also, you need to find finance interesting enough to spend time with it. Wouldn't the term "Statistical Arbitrage" be a more apt description of what you were doing?
If you are relying on a broker-supplied pricefeed over the internet you are far outside the real of what is traditionally understood as "High Frequency Trading". It wasn't anything over the internet. I had a server rented at my broker who were situated close to the exchanges in Chicago and had direct lines. For sure I was not the fastest but only behind by a couple milliseconds perhaps. Ok, that wasn't clear to me. You talked about programming hotkeys and then automating the hotkeys so I assumed this was running on your desktop.
How much does that cost? Thanks for the post. Is this the software you used? Yes, however, I forgot to mention that pretty early on I converted my program to use an API from https: It's odd, but I can't remember exactly why. I think it was simply because I found a broker who could offer me a lower commission rate and they only supported TT. With regard to posting code yes I may do that. Is that the simpler one? I used the simpler one. What does it depend on? I was only a developer so I'm not sure what licensing costs are for gateways, but those are the servers you connect to in order to place orders on the exchanges.
If he posts the code, you're a long way from running it. Do you think you got lucky or that your skill as a trader made you this money? Or rather, which of these do you think mattered most? How do did you cope with increased stress level? Trading futures, especially in a an automated way, can easily drain your margin unless the algorithm is really well tested for edge cases. My automated program was much less stressful than trading manually. The best was going to Hawaii, waking up, and having the entire day done.
I was making like 6k every day on that vacation. I wonder if running your program nowadays can have same successful results as two years ago.. Don't do this with your own money. Found a startup building HFT tools, and then raise money for it, and use other people's money to test your tools. If the tools work, sell them. If they don't, tweak them, try it again, and sell them until they do. This is risk management. I started the infrastructure for this kind of thing a while ago. It provides structure, communications, auditing and alerting for autonomous systems. Part of it is base code for dealing with stocks and options, treating securities positions as autonomous systems that have the scaffolding for running simulations on themselves.
It's in Smalltalk and runs under Squeak and Pharo. It can be found at: This is not HFT. There's a huge difference between automated and high frequency trading. What he does is only automated scalping at best or at the fastest. Automated trading is more on strategy, while HFT has more to do with volume and speed. With automated trading, you predict price movements. HFT involves being a liquidity provider. You don't use market technical indicators in HFT, you wait for some really huge orders. HFT firms won't bother him. Those are dealing with an entirely different set of algorithms.
He should have contacted brokers instead. Is there a way to do this with Python or Ruby? I could just as well program this in C , but I have a friend who can code a little, but doesn't really need everything in C to do what he wants. Combine this with a web based code editor and easy hosting, and I think this would be a viable product. Nope, there is absolutely no way to do this with python or ruby. Seriously though, there are some existing frameworks and products that you could check out.
I haven't used this myself, it's just in my bookmarks: Sorry a bit new to this field. Yep, almost any of them have an API these days. Your software would make the list of trades which is uploaded and executed Oh, I forgot about another backtesting framework for python. It has a built in IDE as well. I work at quantopian. We are working on broker integration, so you will be able to trade algos you develop live. Our backtesting engine, Zipline, is opensource - https: Sure, his program could easily have been done in almost any language. He wasn't competing on speed, which might have excluded languages like Python.
Looking at your first chart there, is there a reason other than market conditions you were making significantly more at the end of '09 than mid '10? To be honest I don't know exactly what happened. My theory is that over time more and more market participants started integrating the types of analysis I was doing which rendered my program ineffectual. It's a pretty normal pattern that there is some inefficiency in the market and over time it disappears.
Being a machine learning program, how much of it did you tell it to forget? Were you compounding the data always, or telling it to forget what was going on several months ago? Or somewhere in between? I'm pretty unfamiliar with machine learning, apologies if this is obvious or something. If the model worked well, did you try letting your algorithm to 'forget' the data and see if the model worked better?
It's possible that your algorithm is sensitive to market volatility. Could you comment on how your "curve fitting" algorithm worked? Did you end up with an equation for each curve? Im working on something that requires curve fitting and any kind of tip would be helpful. I basically just brute forced it. I came up with a cost function which would measure the difference between a possible curve and each data point. I think you're supposed to do the squared difference but I can't remember if I did that.
With a cost function in place it's just a matter of zooming in on variables that minimize the cost function. The article doesn't seem to expound on that unless I missed something. Is this a result of bots on the other side adapting in some way to what you were doing? I would have thought you would be too small a player for them to notice. I don't think anyone was adapting to what I was doing in particular but rather simply adapting to the opportunities in the market.
I guess those opportunities tend to get ironed out rather fast then. From March through much of , the market was strongly bullish - if his algorithm showed a positive market bias then his returns would primarily be a function of timing read luck: Not exactly shocked Jim Simons didn't return his email. But completely shocking that he walked away from a successful automated trading strategy Author graphed his daily returns which should give you a handle on his volatility.
His montlhy returns went to nearly zero so he stopped. Edited to fix numbers. I cannot get even a remote sense for the nature of his risk exposure from looking at his daily returns. The point here is that a systematic bias in his algorithm will expose his trading strategy to the good graces of market fortune luck regardless of whether he trades a million, billion or once a day. The source of the bias is irrelevant. ChuckMcM on Nov 6, The high point of my trading was October when I made almost k. After this I continued to spend the next four months trying to improve my program despite decreased profit each month.
It is of course possible that once you made "real" money with your algorithm it was spotted by the other algorithms which then started working against it. Aka exploiting it Having talked with people in that space hft I was left with the impression that an insane amount of analysis was done on those trades. Would you be able to open source any of the code behind your trading system? Maybe not the "secret sauce", but it would be interesting to see how you processed the data feeds, modeled the data, entered orders, etc. I certainly could open source it. I may just wait a bit on the off chance that somebody wants to purchase it.
Relax, nobody is buying your program. I work in the industry, this happens all the time. Trading strategies have a shorter half life than you may think. Juuumanji on Nov 6, A lot of people in the business would pay e. If he claimed it still works but he wants to sell it, it is a completely different game -- because when these things work, they are cash cows. Yes i'm pretty sure it wouldn't work today. By buying the code I realistically mean hiring me to work for them based on what I achieved.
If you want to go back to trading, you'll probably have to actively try to get a job -- at the very least, let someone who's still in the business know that you are looking. In my experience in this field, word of mouth and friends-of-friends are infinitely more successful hiring strategies, for both sides. Evbn on Nov 6, Sharma on Nov 6, Trust me, you earned that much because of your luck. Otherwise Andrew Ng would have partnered with another finance professor and they would have been the richest people on earth!! Imagine trading with their expert systems on global markets.
I traded stocks and Forex for years and my experience says, it is not for everyone. What ever indicators,discipline or model you follow it is going to work only if you have the right intuition or luck! I like to trade Forex using mql4, any suggestion? Would it be more fair to say that your profitability turned to zero? To be honest I'd given up and moved on to other stuff well before I actually shut down the program.
Thanks for the post, it's very inspirational. Could you explain this part, specifically what do you mean by "bucket"? This produced unique predictions for each bucket that I was then able to graph in Excel. As you can see the expected price change increases as the indicator value increases. Could you explain this part, specifically what do you mean by "bucket". This is an activity that adds no value to our world. It is pretty clear from his own graph that this stopped working in october ' Cool article but I hope people don't start trying to follow this path.
Ask yourself -- why did he stop?
I don't understand trading enough to even understand many of the terms in the article, however I'm curious to one thing: Have you ever thought of making a trading system that would buy tons of stock when a flash crash happens? It is going to happen again. If your system is ready and you buy before they shut the market down or roll back orders you could make a hefty profit. The difficulty is in identifying what is a 'flash crash' i. If the market dives and you quickly get into a big long position, and then it dives some more - what do you do?
You can either close out your losing trade and take the loss, or hope that the market comes back up, all the while holding on to the risk of further losses. Also, there's no guarantee that trades in the middle of a flash crash will remain valid after the crash. The exchange could nullify all trades in a certain period of time, which would completely wipe out your upside potential.
This is the most important thing: In every single "flash crash", the exchanges have retroactively canceled trades, in a rather arbitrary manner e. There is some underlying justification, but it is also arbitrary e. XX" condition as well as the "between XX: Of course there is no guarantee that the same criteria will be used the next time around so caveat emptor.
How I made $k with machine learning and high frequency trading | Hacker News
MonteChristo on Nov 7, The prototypical example of why a tax on financial transactions is urgently needed. Excellent article on this posted here: Isn't profit meaningless without knowing initial investment? I read the first few paragraphs and got bored. Why not say upfront what the bankroll was to start?
I found what I was looking for in the comments. Built it up to 30k trading manually before my automated program went live. Can you create an online course and teach us all? FireBeyond on Nov 7, Hopefully not buried too deep, but any books recommended for getting into day-trading, either manual, or algorithmic? Kindle preferred, but definitely not the deciding factor. Might've been what it was a couple of years ago but this post, dated today, is the perfect advertisement for the author's current business.
I am skeptical for two reasons: You don't just stop using it. There should be more to this story. Can I recommend that you read the article and you will find therein the answers you seek! Hacker News new comments show ask jobs submit. DennisP on Nov 6, This is a bit off-topic, but it's actually quite feasible to get a real edge in Hold'em, and it's not just about spotting other people's patterns. AnIrishDuck on Nov 7, Exactly.
KingMob on Nov 6, While writing his own trading system is a decent accomplishment, due to things such as an overall rising market in the time period involved and survivorship bias, the original author is likely to be completely mistaken about the reason for his winnings. ScottBurson on Nov 6, There's a sentence in this article that is critical and yet very easy to overlook: