Dynamic Asset Allocation for Stock Trading Optimized by Evolutionary Computation
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Information Vol.E88-D No.6 pp.1217-1223
- Publication Date
- 2005/06/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietisy/e88-d.6.1217
- Type of Manuscript
- PAPER
- Category
- e-Business Modeling
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Jangmin O, Jongwoo LEE, Jae Won LEE, Byoung-Tak ZHANG, "Dynamic Asset Allocation for Stock Trading Optimized by Evolutionary Computation" in IEICE TRANSACTIONS on Information,
vol. E88-D, no. 6, pp. 1217-1223, June 2005, doi: 10.1093/ietisy/e88-d.6.1217.
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.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.6.1217/_p
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@ARTICLE{e88-d_6_1217,
author={Jangmin O, Jongwoo LEE, Jae Won LEE, Byoung-Tak ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Dynamic Asset Allocation for Stock Trading Optimized by Evolutionary Computation},
year={2005},
volume={E88-D},
number={6},
pages={1217-1223},
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.},
keywords={},
doi={10.1093/ietisy/e88-d.6.1217},
ISSN={},
month={June},}
Copy
TY - JOUR
TI - Dynamic Asset Allocation for Stock Trading Optimized by Evolutionary Computation
T2 - IEICE TRANSACTIONS on Information
SP - 1217
EP - 1223
AU - Jangmin O
AU - Jongwoo LEE
AU - Jae Won LEE
AU - Byoung-Tak ZHANG
PY - 2005
DO - 10.1093/ietisy/e88-d.6.1217
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2005
AB - 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.
ER -
English
