论文标题
波动率可以解决幼稚的投资组合难题吗？
Can Volatility Solve the Naive Portfolio Puzzle?
论文作者
论文摘要
我们调查了复杂的波动率估计是否改善了相对于NAIVE 1/N策略的均值变化投资组合策略的截面性能。投资组合策略仅依赖于第二时刻。在多个数据集中，使用各种计量经济学和投资组合模型，大多数模型达到了较高的SHARPE比率和较低的投资组合波动率，这些模型在统计学和经济上相对于天真规则，即使在控制周转成本之后，它们在经济上具有重要意义。我们的结果表明，与样本协方差矩阵相比，采用更复杂的计量经济学模型的好处，而均值变化策略通常在多个数据集和评估标准上表现优于天真的投资组合。
We investigate whether sophisticated volatility estimation improves the out-of-sample performance of mean-variance portfolio strategies relative to the naive 1/N strategy. The portfolio strategies rely solely upon second moments. Using a diverse group of econometric and portfolio models across multiple datasets, most models achieve higher Sharpe ratios and lower portfolio volatility that are statistically and economically significant relative to the naive rule, even after controlling for turnover costs. Our results suggest benefits to employing more sophisticated econometric models than the sample covariance matrix, and that mean-variance strategies often outperform the naive portfolio across multiple datasets and assessment criteria.
