By Mark Kritzman, Cel Kulasekaran, and David Turkington.
We introduce a more flexible way to forecast risk and return based on the most relevant historical periods.
As economic regimes shift, investors who choose to adapt must build portfolios that match their evolving view of the future. Forecasts of asset risk and return should account for regime-specific trends. The question is how to implement this idea in practice. Typically, an analyst will find every time an economic indicator like inflation or growth was above (or below) a fixed threshold, and she will pay equal attention to every data point that qualifies. While this approach seems sensible, it also has dramatic limitations. Ideally, we should recognize that the regime labels of past events are not simple yes/no answers; they are ambiguous. We should pay more attention to some past events than others, based on their relevance. We should weigh the impact of many variables rather than just one. And we should accept that some events are relevant to more than one regime. A statistical measure of relevance, based on the Mahalanobis distance, empowers investors to analyze these nuances of regimes with rigor. We show how to estimate expected risk and return as weighted averages of the relevant past, and how these forecasts of asset performance lead to intuitive portfolios optimized for a range of possible regimes.