Categorizing market action can be done in several different ways. A simple dimension is associated with concepts such as range and volatility. Another dimension is related to directionality. Using the various combinations you can build a bi-dimensional matrix of market behavior. (I am not sure whether they are the only two dimensions to take into account. You could have multi-dimensional environments more complex to categorize and study.) Considering a bi-dimensional matrix, market conditions are:

1. volatile - directional

2. non-volatile - non-directional

3. volatile - non-directional

4. non volatile - directional

The problem is how to efficiently and with limited lag identify the state the marketplace is currently in. An appropriate trading system would be chosen accordingly. In a non-volatile directional environment you could be quite profitable implementing a trend following system, which would not suffer so much from false signals. In a volatile non-directional environment you could implement a contrarian system which would profit from the high number of false breakouts. And so forth.

Many indicators can be used to define the areas, although borders/lines of contact between areas remain a problem together with the lag you would face during transition phases from one environment to the next. Overall, however, gray areas and lag could impact significantly on your performance.

Building a family of robust systems to cover the whole spectrum of situations is one solution to the problem. For example, you could have a system working well in low volatility conditions (directional or non directional) together with a system working well in high directional situations (volatile or non-volatile) and a system optimized to work in volatile non-directional environments. Combinations of systems could obviously be very different depending on systems' characteristics. Generally speaking, lag would not be an issue because as soon as market conditions change one of the system would overperform others. Definitions of market conditions through various indicators would be simplified as well as optimization of parameters which would lead otherwise to overoptimization. Robustness of systems during sub-optimal phases for their performance is the key to profitability.

Systems not fully satisfactory when traded alone could become interesting when traded in parallel with other systems as the equity lines would be smoother and risk would be reduced although at the expense of the overall profitability.


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