Optimal Trading Frequency for Multi-period Mean-Variance Portfolio Selection with Data Noise
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Abstract
This paper investigates a dynamic mean-variance (MV) portfolio optimization model with different investment frequencies and examines the in-sample performance of the frequency-adjusted MV portfolio strategy under data noise. The model can be considered a special case of a constrained linear-quadratic (LQ) optimal stochastic control problem, where the different investment frequencies are incorporated as linear constraints. By utilizing the state separation property and a piecewise description approach, this study employs multiple coupled Riccati equations to address relevant challenges, characterize the optimal control policy, and develop analytical strategies for asset allocation. The numerical examples illustrate that investors need to select an appropriate investment frequency to balance the potential risk of wealth loss and investment performance.
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