Return Predictability and Intertemporal Asset Allocation: Evidence from a Bias-Adjusted VAR Model

Tom Engsted, Thomas Q. Pedersen
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引用次数: 25

Abstract

Within a VAR based intertemporal asset allocation model we explore the effects on return predictability and optimal asset allocation of adjusting VAR parameter estimates for small-sample bias. We apply a simple and easy-to-use analytical bias formula instead of bootstrap or Monte Carlo bias-adjustment. Regarding return predictability we show that bias-adjustment in the multivariate setup can yield very different results than in the univariate case. Furthermore, bias-correcting the VAR parameters has both quantitatively and qualitatively important effects on the optimal portfolio choice. For intermediate values of risk-aversion, the intertemporal hedging demand for bonds and stocks is heavily affected by the bias-correction. Utility calculations also show large effects of bias-adjustment, both in-sample and out-of-sample.
收益可预测性与跨期资产配置:来自偏差调整VAR模型的证据
在基于VAR的跨期资产配置模型中,我们探讨了在小样本偏差下调整VAR参数估计对收益可预测性和最优资产配置的影响。我们采用一个简单易用的分析偏差公式,而不是自举或蒙特卡罗偏差调整。关于回报的可预测性,我们表明,多变量设置中的偏差调整可以产生与单变量情况下非常不同的结果。此外,偏差校正VAR参数对最优投资组合选择具有定量和定性的重要影响。对于风险厌恶的中间值,债券和股票的跨期套期保值需求受到偏差修正的严重影响。效用计算也显示了样本内和样本外偏差调整的巨大影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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