Using Macro Forecast Surprises for Tactical Asset Allocation

Summary

This report studies whether gaps between consensus forecasts for macroeconomic indicators and their released values help explain subsequent returns across asset classes. It places the signal in an allocation framework that combines long-term strategic weights with short-term tactical adjustments. It defines two surprise events: actual data beating or missing expectations, and the actual and expected values moving in opposite directions. Each event is assigned a measure of its magnitude, then selected events with stronger historical hit rates guide portfolio changes, with irregular adjustments and periodic rebalancing.

The report describes tests on broad asset allocations, ETF portfolios, and relative long-short positions. It reports annualized excess return of 3.44% for an asset allocation strategy versus its benchmark and annualized absolute return of 9.62% for a relative-return long-short strategy; the ETF result is mentioned without a figure in the supplied text. These findings are historical estimates, not forecasts. The authors caution that the model abstracts from reality and relies on historical data, so its assumptions and results may not represent future market conditions.

Key ideas

• Consensus forecast errors can be studied as potential signals for future cross-asset returns.
• The analysis defines surprises by whether actual data beat or missed forecasts and whether actual and expected changes had opposite signs.
• Selected historical surprise events guide tactical allocation, with periodic portfolio rebalancing.
• Reported strategy results are based on historical data and depend on simplifying model assumptions.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.