During this past week I have written several posts about trading robustness and the use of minor currency pairs in forex trading. I talked about how – in order to have accurate simulations on minors in Metatrader 4 – we needed to develop daily systems which were able to arrive at accurate control point simulations in which the accurate well known daily charts could be used and the lower time frames (less accurate for these spreads due to historical spread variations) could be avoided. On today’st post I will be sharing with you my efforts to develop systems with minors using my genetic programming framework (you can read more about it here, here and here) and what preliminary results I have been able to achieve. I will talk about the different pairs I used, the profitability of the results I achieved and why these results are bound to be robust, non-curve-fitted and a good startup point for the development of a minor-based portfolio.
Minors constitute an important part of forex trading because they constitute the majority of instruments we can trade. Aside from the 6-8 major highly-liquid currency pairs, minors form the rest of the foreign exchange over-the-counter market. It is therefore important for us to consider the trading of minor currency pairs if we want to achieve a higher degree of diversification and less exposure to the USD than with the main major currency pairs (which are almost entirely based on the USD).
This leads us to find minor based strategies which are profitable on each one of the different instruments available. When I was confronted with this problem, I immediately thought that my genetic framework might be the best way to develop sound and reliable systems to trade the minors, obtaining reliable simulations and generating transparent systems we could analyze to determine what sort of inefficiencies are bound to work on the different less liquid pairs. The systems developed worked on the daily charts and provided accurate control point simulations. The building of the systems was performed from 2003 to 2009 while 2010 was left as an out-of-sample year to further avoid any curve fitting that might have happened due to the inclusion of the whole trading period. It is also worth remembering that the framework is very restricted to only build systems with simple entry and exit criteria that are symmetrical in short/long entries/exits.
Perhaps the most interesting part of this was to analyze the results obtained for the different minors and what the “framework” came up with as a solution to achieve long term profitability on these pairs. Interestingly enough the solution depended on how much each different currency pair “trended” and how volatile its movements were. On the more volatile pairs the system opted to use only range-trading or trend-following-on-retracement techniques (buying low, selling high) while on more trendy pairs the system decided to use trend following techniques. It is interesting to note however that the system found an “equilibrium” on each pair, using a combination of both of these techniques depending on the actual character of the pair being traded. On pairs like the GBP/CAD – shown above – the system decided to use both techniques, following the trend using long term indicators (only very established trends) while fading trends that are just “weak” in nature.
This way of developing systems allows us to easily develop sound trading tactics for a whole portfolio of minors in an almost automated fashion. By following this procedure on most minors I was able to obtain a trading portfolio which contains a lot “new instruments” we have never traded in Asirikuy. With an average compounded yearly profit of 38% and a maximum draw down of 28%, the portfolio achieves a good average compounded yearly profit to maximum draw down ratio of 1.38, in line with many good portfolios obtained using current Asirikuy systems on majors. The fact that the portfolio also relies on a wide variety of non USD pairs also makes it a perfect diversification against this currency and a good portfolio to trade under non-USD denominated accounts. Of course, we can make portfolios using all JPY, EUR, or CAD pairs (for example), something I will talk about within a future post.
As you see, this genetic framework is an extremely powerful tool for the development of trading strategies, allowing us to obtain results for any instrument we want with the certainty that the trading system obtained will be transparent (easy to understand) and the possibility of curve fitting will be minimal. Most importantly, the systems have adequate worst case draw down values that would allow us to stop trading them shall their statistical characteristics deviate from the long term values determined in testing. I am currently continuing my work on this genetic programming mechanism, expecting to release it in January 2011.
If you would like to learn more about automated trading and how you too can develop your own likely long term profitable mechanical trading strategies based on sound trading tactics please consider joining Asirikuy.com, a website filled with educational videos, trading systems, development and a sound, honest and transparent approach to automated trading in general . I hope you enjoyed this article ! :o)