You want to overweight equities ahead of the period when they outperform other asset classes, and to reduce allocation when equities are expected to underperform. Sounds easy? It isn’t, of course. The key is forecasting returns for the asset classes under consideration.
At Performance Analytics, we apply our proprietary dynamic multi-factor regression model – the PAR model™ – to forecast equity market returns over a six-month period. We offer the results of the model as part of our monthly research subscription service. This helps investment managers achieve better portfolio risk-return performance.
For example, in back-testing, the PAR model’s™ 6-month return forecast for the S&P 500 would have been a negative 12% on Dec. 31, 2007, and a negative 28% on June 30, 2008. Based on such expectation, you would want to significantly reduce your exposure to stocks. Of course, the market cashed in 2008, proving that the model would have been very accurate well ahead of the move. However, on November 30, 2008 the model would have turned positive, and predicted a 4% return, and the forecast rose to 21% on January 31, 2009 – you would want to maximize your equity exposure based on these expectations.
We offer subscription to our PAR Model™ reports to asset management clients. The reports contains the following information:
- The PAR Model’s™ six-month return forecast for the S&P 500
- Factor contribution to the current return forecast, and historical analysis
- Attribution of the change in return forecast from the previous month
- Our commentary and interpretation of these results
- Performance of active asset allocation strategies based on the model