Advancing Strategic Asset Allocation in aMulti-Factor World
提出一种基于多因子的战略资产配置新方法，解决传统方法在估计精度、组合优化、尾部风险建模和经济情景模拟上的不足，帮助投资者构建更稳健的分散化组合。
Strategic asset allocation is arguably one of the most important, yet least advanced, aspects of investing. The authors present a new approach to strategic asset allocation that leverages the idea that long-term investment returns derive from multiple distinct sources that they call “return-generating factors.” Their approach addresses four key shortcomings of traditional approaches: First, their multi-factor model helps better understand the important sources of return in today’s complex investment universe, generating a substantial increase in estimation precision across asset classes and providing investors with a new way to think about portfolio diversification. Second, their robust portfolio optimization methodology seeks to explicitly account for the uncertainties inherent in the estimates of expected returns, delivering well-diversified portfolios with superior risk?return characteristics. Third, the factor-based risk analytics better capture the true characteristics of asset returns, such as fat tails and increased correlations at times of crises, allowing the authors to more-accurately model the downside risks of portfolios. Finally, the factor-based simulation technique accounts for the impact of different economic conditions (e.g., low interest rates) on future portfolio returns, resulting in more-precise, forward-looking projections. <bold>TOPICS:</bold> <ext-link>Portfolio theory</ext-link>, <ext-link>tail risks</ext-link>, <ext-link>factor-based models</ext-link>