Prediction of Interday Stock Prices Using Developmental and Linear Genetic Programming
نویسندگان
چکیده
A developmental co-evolutionary genetic programming approach (PAM DGP) is compared to a standard linear genetic programming (LGP) implementation for trading of stocks across market sectors. Both implementations were found to be impressively robust to market fluctuations while reacting efficiently to opportunities for profit, where PAM DGP proved slightly more reactive to market changes than LGP. PAM DGP outperformed, or was competitive with, LGP for all stocks tested. Both implementations had very impressive accuracy in choosing both profitable buy trades and sells that prevented losses, where this occurred in the context of moderately active trading for all stocks. The algorithms also appropriately maintained maximal investment in order to profit from sustained market upswings.
منابع مشابه
Interday and Intraday Stock Trading Using Probabilistic Adaptive Mapping Developmental Genetic Programming and Linear Genetic Programming
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