Identifying Economic Regimes:Reducing DownsideRisks for University Endowments and Foundations
研究发现市场崩盘时相关性上升，传统分散化失效；用趋势过滤算法识别不同经济状态，多体制模拟比静态模型更准，帮助捐赠基金等非营利机构评估降低最差情景的策略。
One of the most durable patterns in market behavior involves contagion—increases in correlation and volatility—during crash periods such as 2008. This condition can cause major problems for an investor when markets severely contract and anticipated diversification benefits vanish. To address contagion, the authors implement a machine-learning algorithm, <i>trend filtering</i>, to capture distinctive economic conditions. Over long horizons, they find that a multiregime simulation provides more accurate estimates of downside risk compared with traditional static portfolio models and can help in evaluating strategies for reducing the worst-case outcomes. The approach readily applies to nonprofit institutions that depend upon their endowment capital to fund liabilities and meet goals. <b>TOPICS:</b>Exchanges/markets/clearinghouses, risk management