基于时变隐马尔可夫机制转换模型的多资产配置研究

股票收益率预测和基于此的资产配置一直是金融研究的核心问题。过去许多 文献提出的方法在样本内有效，但在样本外往往表现不佳，甚至不如历史平均值 的预测表现。这是由金融市场状态变化引发的模型不确定、参数不稳定问题导致 的。金融市场不同状态之间的转换是突然的，但转换后的状态又具有持续性，这些 线性模型难以刻画的特征却可以被隐马尔可夫模型描述。本文在时变隐马尔可夫 机制转换模型的基础上加入经济变量，构成单因子和双因子预测模型，对美国市 场上的行业股票组合超额收益率进行样本外预测，并参考了组合预测的方法，结 合了各个预测因子的信息。基于隐马尔可夫机制转换模型的组合预测在日常消费 品、日常服务和其他行业 (诸如，矿业、娱乐、金融等) 股票组合上有很好的预测 表现，样本外𝑅 ²显著为正。单因子和双因子时变模型在多数行业上的预测能力都 显著超越了历史平均值的预测。资产配置结果表明，基于隐马尔可夫机制转换模 型的组合配置有良好的表现，在样本外夏普率和确定性等价收益率上超过了基于 历史均值预测的 Markowitz 方法、普通单因子预测的组合配置。其中，双因子时变 模型得到的结果表现最佳，甚至在确定性等价收益率这一指标上显著优于1/N策 略。资产收益率和经济变量之间的关系会随经济周期发生变化。隐马尔可夫机制 转换模型可以识别经济周期的变化，从而可以更稳定地预测资产收益率，进而更 有效地进行资产配置。

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