After 9 months of obsession, here is my open source Node.js framework for backtesting forex trading strategies
TL;DR There's lots more to the story. But the code is all open source now. Have at it. I'm too exhausted to continue with this. If you'd like more details, feel free to message me. If you happen to carry on with this project or use any ideas from it, I would greatly appreciate it if you could keep in touch on your findings. If anyone has any insights, please feel free to comment or message me. I've spent the last nine months working furiously on this. I started a project for backtesting strategies against data I exported from MetaTrader. I had a very powerful computer crunching numbers constantly, trying to find the most optimal configuration of strategy indicator inputs that would results in the highest win rate and profit possible. Eventually, after talking with a data scientist, I realized my backtesting optimizer was suffering from something called overfitting. He then recommend using the k-fold cross-validation technique. So, I modified things (in the "k-fold" forex-backtesting branch), and in fact it provided very optimistic results when backtested against MetaTrader data (60 - 70% win rate for 3 years). However, I had collected 3 months of data from a trading site (by intercepting their Web Socket data), and when I performed validation tests against that data using the k-fold results created from the MetaTrader data, I only got a ~57% win rate or so. In order to break even with Binary Options trading, you need at least a 58% win rate. So in short, the k-fold optimization results produce a good result when validation tested against data exported from MetaTrader, but they do not produce a good result when validation tested against the trading site's data. I have two theories on why this ended up not working with the trading site's data:
The trading site I collected data from uses Reuters data. The prices in the MetaTrader data I used are different from the prices in the the trading site's data. Basically the the trading site's data is offset and is slightly higher than the MetaTrader data (and there may be other differences). I suspect that the k-fold optimization may have produced a predictor that is tailored to the data exported from MetaTrader (data available here), but it does not work as well on the the trading site's data.
The script I used to collect data from the trading site disconnects from the trading site periodically for maybe 10 minutes every, and so when it does, the strategy indicator calculations used when validating against the collected data have to start all over due to gaps, and so potential trades are lost.
For the strategy I use the following indicators: SMA (Simple Moving Average), EMA (Exponential Moving Average), RSI (Relative Strength Index), Stochastic Oscillator, and Polynomial Regression Channel. forex-backtesting has an optimizer which tries hundreds of thousands of combinations of values for each of these indicators, combined, and saves the results to a MongoDB database. It can take days to run depending on how many configurations there are. Basically the strategy tries to detect price reversals and trade with those. So if it "thinks" the price is going to go down within the next five minutes, it places a 5 minutes PUT trade. The Polynomial Regression Channel indicator is the most important indicator; if the price deviates outside the upper or lower value for this indicator (and other indicators meet their criteria for the strategy), then a trade is initiated. The optimizer tries to find the best values for the upper and lower values (standard deviations from the middle regression line). Additionally, I think it might be best to enter trades at the 59th or 00th second of each minute. So I have used minute tick data for backtesting. Also, I apologize that some of the code is messy. I tried to keep it clean but ended up hacking some of it in desperation toward the end :) gulpfile.js is a good place to start as far as figuring out how to use the tools available. Look through the available tasks, and see how various "classes" are used ("classes" in quotes because ES5 doesn't have real class support). The best branches to look at are "k-fold" and "master", and "validation". One word of advice: never, ever create an account with Tradorax. They will call you every other day, provide very bad customer support, hang up the phone on you, and they will make it almost impossible to withdraw your money.
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