My priority during the past few years has always been the development of profitable trading strategies with a high probability of delivering profitable results under future market conditions. I have read as many books as I have been able to, run as many tests as my computer power has allowed and have stress tested, “banged against the wall” and tested my ideas as hard as I could. From this I have reached many interesting conclusion but perhaps one of the strongest is the one I will be sharing within this blog post. Within the next few paragraphs I will talk to you about the market’s randomness and why the statistics behind price movement suggest that the “best way” to get a robust long term profitable system is to take advantage of “everything”. A global view, is your ultimate Forex weapon.
An interesting discussion arises whenever you consider the development of trading systems. The first question that arises is generally simple : Is this possible ? Is it possible to develop a system which gets profit from the market under very varied past and future market conditions ? The answer depends on a very important subject which relates to the efficiency of the market. If the market is efficient – it follows a random walk – then this is not possible, if it doesn’t then there is a given set of rules which may generate a profitable trading strategy that “works” independently of what the market does. If there is no random walk then – by definition – there is at least some hidden pattern in the market which is exploitable.
When you analyze the EUR/USD data for the past ten or twenty years (DEM/USD before EUR/USD) and you evaluate it against the random market hypothesis you find some pretty interesting results with most of them telling you that the market does NOT follow a random walk . For example see this article and this article for research papers talking about Forex pairs and the random market hypothesis. Inevitably the conclusion amongst all studies I have found – and my own personal research – is that the market is, at the very least, weak-form efficient.
On a weak-form efficient market there is no way in which a long term profitable strategy can be derived from single series data (from developing a system for that pair) as this would inevitably yield – in the best of cases – a curve fitted result in the past with a randomly profitable outcome on an out of sample test but it is perfectly possible to derive a profitable strategy for one pair if information from “many sources” is taken into account. This doesn’t mean that the market may not be more inefficient than this but it means that a multi-series system would have the highest chance at future survival since the market analysis shows that the market is at least “this inefficient”.
What this tells us is pretty interesting since it forecasts that our best chances of developing a system that works under both past and future market conditions is to use other instruments and other financial data to derive our entries and exits. For example many people have advocated for the use of Libor interest rate data in the development of trading models for automated Forex trading strategies as this data yields a high correlation with the way in which instruments trade because it controls a large portion of capital flows (it determines the “natural direction” of money flow). So using such fundamental data for the taking of decision is bound to be a very important step forward.
One of my goals for this year – as I said in December – was to learn more about and start using neural networks for automated trading system development and I believe that their usage has the most potential when considering multi-series data. Neural networks have shown to simply deliver curve-fitted solutions when attempting to predict the outcomes of single instruments but their potential for the construction of a “global model” which takes into account “all available information” is much clearer since they would be able to find patterns under very complex variable changes, something which other methodologies might find difficult or impossible to achieve. Under these conditions the possibility of curve fitting would also be much lower since we know that weak-form efficient markets are prone to exploitation if multi series data (a.k.a fundamentals and other pairs) is taken into consideration.
Although the development of single series system using genetic and other tehcniques is not demonstrated to be “doomed to fail” and in several cases quite the contrary, it is true that to further advance our abilities to exploit market inefficiencies we need to look “beyond our noses” and use all the data available to us to make trading decisions. If Libor rates and another myriad of pairs and fundamental releases are available then why not use this data to develop a robust trading system model? Why not use everything we know for the development of profitable trading strategies?
Certainly a project to develop such a model would be very complex and difficult and it falls beyond the capabilities of our current testing implementations. One of the main reasons why I want to implement C++ or FreePascal testers (and why we are in fact developing them) is mainly to allow us to exploit all of these new possibilities in the best possible way. I certainly believe that by using independent testers we will be able to exploit much more elaborate and “deep” inefficiencies and to arrive at systems which are much more robust and view the market through a much more macro economical perspective.
In the end I believe that the natural way to progress in system development is to have a “global view” and to develop systems which make trading decisions not only based on single series of data but based on information coming from many different sources. If you would like to learn more about my projects and work in automated trading and how you too can develop likely long term profitable systems 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 towards automated trading in general . I hope you enjoyed this article ! :o)