Asset Allocation with a High Dimensional Latent Factor Stochastic Volatility Model
提出一个高维动态因子多元随机波动率模型，允许大量资产的收益均值和波动率随时间变化，并基于36只股票检验了该模型在动态资产配置中的经济价值，发现其显著优于多种基准策略。
We investigate the implications of time-varying expected return and volatility on asset allocation in a high dimensional setting. We propose a dynamic factor multivariate stochastic volatility (DFMSV) model that allows the first two moments of returns to vary over time for a large number of assets. We then evaluate the economic significance of the DFMSV model by examining the performance of various dynamic portfolio strategies chosen by mean-variance investors in a universe of 36 stocks. We find that the DFMSV dynamic strategies significantly outperform various benchmark strategies out of sample. This outperformance is robust to different performance measures, investor's objective functions, time periods, and assets. Copyright 2006, Oxford University Press.