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An intraday trading model based on Artificial Immune Systems

This paper introduces a trading system where decisions are driven by an algorithm belonging to the class of Artificial Immune Systems (AIS). In practice, the system we have built operates according to a two-steps procedure, where, in the first stage, the Negative Selection Algorithm (NSA) runs on historical values of the financial timeseries, while in the second phase, at each time t the outcomes of the NSA are merged into a decision support system that uses them to suggest an active trading position (long, short or standby, i.e.: buy, sell, or doing nothing) at time t + 1. The effectiveness of the procedure is examined using intraday data from the FOReign EXchange market (FOREX), and the results are evaluated mainly under the financial profile by means of typical indicators of financial performances. At the present time, the results suggest that the procedure can be proficiently used especially during downward periods of the market (descending prices), to hedge investors from the probability of higher drawdown.