To your first point about our development strategy: we used genetic programming, and tried to apply novel strategies for which there wasn't much of a precedent in financial applications.
To your second point, re: our testing strategy:
I will concede that we only have 2 months of live trading data, but so far it corresponds well to the behavior we were seeing in our forward tests (what we call the data that the system was not trained on).
We trained our system on 10 years of data (2001 - 2011) with two years of forward tests (2012 and 2013) for evaluating its effectiveness (and to verify that our algorithms have not been overtrained to fit the testing data set). Our forward testing involved taking the same data we would have received from our financial institution and feeding it through the algorithm to see what trades it makes. Having proven our algorithm worked with forward tests, we hooked it up to live data to get real results. So far, so good!
To you third point--risk--we need to explain how our algorithm trades.
We've trained our system to recognize patterns such that it will open a trade with a stop-loss and a take-profit. Because the take-profit and stop-loss are preconfigured, our system doesn't need to monitor data feeds with a time resolution of “real time” to make decisions; the onus is on the brokerage to close winning and losing trades.
The lot size of the trade is calculated such that a losing trade (the price of the currency pair reaching the stop-loss) will incur a loss equal to the risk. So at a risk of 2%, a losing trade on a $1000 account will bring the account value down to $980. Winning trades earn double the risk, so a winning trade on an account of $1000 at 2% risk will increase the account value to $1040.
With all this in mind, we claim 40% annual profit because our live trading exhibits patterns similar to our forward tests, and while our forward tests exceed 40% annual profit, we're extrapolating our two months' worth of live testing performance out to the rest of 2014. There's a good chance that this number will change in the coming months. We will revise it up or down accordingly.
It's possible that our system will need to be used "in the wild" for more than just two months in order for people to take us seriously. If that's the case, I am happy to continue dogfooding FX Machine; so far, it’s been a profitable experience :)
Thanks again for your great questions. We’ll use questions like these to build an FAQ section on the site!
I am not purporting to claim that FX Machine will always return 40%+ annual profit forever. Rather, I'm presenting a technology we've developed (as a startup on a startup site!) that trades automatically and, so far, has yielded returns that average (across all currency pairs) in excess of 40% annually. This number was higher on our forward tests, but we have two years of historical data for those and only two months' worth of live testing.
As I said in my reply to ep25, there’s a good chance that our 40% claim will need to be revised either up or down as we continue to dogfood our product. Investing is never a sure bet, even (or especially) when computers are involved. For that reason, I will continue to invest only money that I already have. I'm dogfooding our product with my own hard-earned cash--not somebody else's. What greater measure of confidence is there than this?
The question is not about 40% or 100%, if you are beating the market by a good margin consistently, why would you share that secret with everyone else. You trade/invest for your own account and get rich.
If your system cannot beat the market consistently why bother then, just close your shop and invest in an index fund.
If, however, we find an institution who understands the potential of FX Machine and is willing to invest in it, we can amass our millions much sooner than we would on our own. The opportunity cost for us associated with selling FX Machine versus using it personally is not measured in dollars; it's measured in years.
We're trading on live data (not just making claims based on forward tests) without any human involvement, though human intervention and the ability to recognize trends could have saved some of the trades that ended up being losers. Still, we're looking at sizable gains with a hands-off approach (maybe you'll need to re-train the system every year, but even that can be automated).
We've now run into the problem of telling the world about it; you'd think that 40% annual returns would have large institutions knocking down the door to give us our millions. So it goes!