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Journal of the Operational Research Society

, Volume 66, Issue 7, pp 1115–1131 | Cite as

An adaptively managed dynamic portfolio selection model using a time-varying investment target according to the market forecast

  • Jongbin Jung
  • Seongmoon Kim
General Paper

Abstract

In this paper, we propose an adaptive investment strategy (AIS) based on a dynamic portfolio selection model (DPSM) that uses a time-varying investment target according to the market forecast. The DPSM allows for flexible investments, setting relatively aggressive investment targets when market growth is expected and relatively conservative targets when the market is expected to be less attractive. The model further allows investments to be liquidated into risk-free assets when the market forecast is pessimistic. By dynamically determining the investment target, the DPSM allows construction of portfolios that are more responsive to market changes, while eliminating the possibility of the model becoming infeasible under certain market conditions. When the proposed DPSM is implemented in real-life investment scenarios using the AIS, the portfolio is rebalanced according to a predefined rebalancing cycle and the model’s input parameters are estimated on each rebalancing date using an exponentially weighted moving average (EWMA) estimator. To evaluate the performance of the proposed approach, a 7-year investment experiment was conducted using historical stock returns data from 10 different stock markets around the world. Performance was assessed and compared using diverse measures. Superior performance was achieved using the AIS proposed herein compared with various benchmark approaches for all performance measures. In addition, we identified a converse relationship between the average trading volume of a market and the value of the weighting parameter prescribed to the EWMA estimator, which maximizes cumulative returns in each market.

Keywords

adaptive investment strategy dynamic portfolio selection model portfolio rebalancing mean-variance portfolio selection non-linear programming 

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Copyright information

© Operational Research Society Ltd. 2014

Authors and Affiliations

  1. 1.School of Business, Yonsei UniversitySeoulKorea

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