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Article

Application of the Belief Function Theory to the Development of Trading Strategies

Procedia Computer Science. 2019. Vol. 162. P. 235-242.
Lepskiy A., Suevalov A.

The possibility of using the belief function theory for developing of trading strategies is considered in this paper. An analysis of this approach is given on the data of the Russian stock market. The belief and plausibility functions (and their corresponding bodies of evidence) to the system’s recommendations (buy, sell or hold) are calculated using fuzzy inference methods for technical indicators. Further, these bodies of evidence are aggregated using the combining rules (Dempster’s rule, Yager’s rule and others). The discount coefficients of the bodies of evidence are calculated at the stage of the learning under the condition of maximizing the profitability of the trading strategy. The intervals for the buying or selling of assets are determined on the results of such combination. The decision about the corresponding action is taken after comparing these intervals. The study showed that the proposed approach provides an interesting result.