Risk Premia Forecasts: Major Asset Classes – Thursday, July 6

The expected risk premium for the Global Market Index (GMI) continued to rise in June. GMI, an unmanaged market-value weighted portfolio of the major asset classes, is projected to earn an annualized 5.6% (over the “risk-free” rate) in the long run – 20 basis points above last month’s estimate.

Adjusting for short-term momentum and longer-term mean-reversion factors (defined below) pares GMI’s ex ante risk premium to an annualized 5.2%.

Meanwhile, the trend for GMI’s risk-premium performance in recent history ticked lower in June. The benchmark’s risk premium slipped to an annualized 4.0% for the three years through last month, down from 4.3% in the previous month.


Here’s a recap of how GMI’s risk premium estimates have evolved over the last three years:


Next, let’s turn to actual performance in recent history: here’s a chart of rolling three-year annualized risk premia for GMI, US stocks (Russell 3000) and US Bonds (Bloomberg Barclays Aggregate Bond Index) through last month.


Finally, here’s a summary of the methodology and rationale for the estimates above. The basic idea is to reverse engineer expected return based on assumptions about risk. Rather than trying to predict return directly, this approach relies on the somewhat more reliable model of using risk metrics to estimate performance of asset classes. The process is relatively robust in the sense that forecasting risk is slightly easier than projecting return. With the necessary data in hand, we can estimate the implied risk premia using the following inputs:

● an estimate of GMI’s expected market price of risk, defined as the Sharpe ratio, which is the ratio of risk premia to volatility (standard deviation).
● the expected volatility (standard deviation) of each asset
● the expected correlation for each asset with the overall portfolio (GMI)

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Author: Travis Esquivel

Travis Esquivel is an engineer, passionate soccer player and full-time dad. He enjoys writing about innovation and technology from time to time.

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