Dynamic Asset Allocation for Stock Trading Optimized by Evolutionary Computation

Authors:
Jangmin O;Jongwoo Lee;Jae Won Lee;Byoung-Tak Zhang
Affiliations:
The authors are with Seoul National University, San 56--1, Shillim-dong, Kwanak-gu, Seoul, 151--742, Korea. E-mail: jmoh@bi.snu.ac.kr,;The author is with Sookmyung Women's University, 53--12, Chongpa-dong, Yongsan-gu, Seoul, 140--742, Korea.,;The author is with Sungshin Women's University, Dongsun-dong, Sungbuk-gu, Seoul, 136--742, Korea.;The authors are with Seoul National University, San 56--1, Shillim-dong, Kwanak-gu, Seoul, 151--742, Korea. E-mail: jmoh@bi.snu.ac.kr,
Venue:
IEICE - Transactions on Information and Systems
Year:
2005

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Abstract

Effective trading with given pattern-based multi-predictors of stock price needs an intelligent asset allocation strategy. In this paper, we study a method of dynamic asset allocation, called the meta policy, which decides how much the proportion of asset should be allocated to each recommendation for trade. The meta policy makes a decision considering both the recommending information of multi-predictors and the current ratio of stock funds over the total asset. We adopt evolutionary computation to optimize the meta policy. The experimental results on the Korean stock market show that the trading system with the proposed meta policy outperforms other systems with fixed asset allocation methods.