Mitigating Estimation Risk in Asset Allocation: Diagonal Models Versus 1/N Diversification
研究发现，使用波动率等有限信息的对角策略在缓解估计风险与利用信息之间取得良好平衡，在1926-2012年的数据中，这些策略通常优于1/N分散化。
Abstract Recent literature suggests that optimal asset‐allocation models struggle to consistently outperform the 1/ N naïve diversification strategy, which highlights estimation‐risk concerns. We propose a dichotomous classification of asset‐allocation models based on which elements of the inverse covariance matrix that a model uses: diagonal only versus full matrix. We argue that parsimonious diagonal‐only strategies, which use limited information such as volatility or idiosyncratic volatility, are likely to offer a good tradeoff between incorporating limited information while mitigating estimation risk. Evaluating five sets of portfolios over 1926–2012, we find that 1/ N is generally not optimal when compared with these diagonal strategies.