Market Cycle Varying Multifactor Strategies Cyclical Analysts Noah Harris Juliet Xu JJ Haines

Goal To determine whether or not different factors behave better or worse during different stages of the economic cycle. To develop a time-varying multifactor strategy to take advantage of these differences in factor behavior.

Agenda Overview Factors Market Cycles Scoring Screens Results Conclusions

Overview Identify successful factors from Global Asset Allocation final projects Run in- and out-of-sample screens for all factors (monthly) Use historical data from a pre-determined four-stage cycle to segment factor returns Regress macroeconomic data to predict next month’s cycle stage

Factors We looked at the best factors used by the groups from Global Asset Allocation. Selected Factors:  Book to Price  Analyst Estimate Revision  Price Momentum  Free Cash Flow Yield (FCF/P)  NTM Forward Earnings to Price  Fundamental Debt Factor – eliminated due to poor in-sample performance

Market Cycles Defined by four liquidity regimes:  Calm = positive increasing  Speculation = positive decreasing  Turbulence/Crisis = negative decreasing  Rebound/Recovery= negative increasing (where positive/ negative refers to the liquidity environment)

Factor In-Sample Performance

Scoring Screens and Factor Weightings for Different Cycles Factors are scored from -5 to 5 by each teammate and averaged Long Weightings sum to 100%, Short Weightings sum to -100% “Total” represents weights for a non-varying multifactor scoring screen

Strategy Performance-Annual Cycle Varying- Scoring screens vary with market cycle Equal Wt Factors Varying- Scoring screens vary with market cycle & factors are equal weighted Stable-Scoring screen stays constant through all periods The stable screen had the best out-of-sample performance for both long only and long-short but the cycle varying screen beat the S & P more often in long only.

Overall Performance (Out-of-Sample)

Strategy Performance-Cycles Both the Cycle Varying and Stable Long Only strategies beat the S & P in all four market cycles. The Cycle Varying Long-Short beat the S & P in 3 out of 4 cycles.

Mistiming Question: What happens if we miss the turning point from one regime and the next? Check returns out-of-sample assuming that we miss the turning point by 1, 2 or 3 months The results show that there is little or no significant loss in Alpha!

Prediction for Next Period: Prediction: Next Period will be CALM Procedure: Use Logistic Regressions for each regime independently and compare results

Example of Predictive Process Use all monthly data for final prediction Use backward stepwise to optimize the number of variables (P-to-remove = 0.05) Results in different final list of variables for each regime Example: Test for Calm

Conclusions Using the cycle varying strategy adds positive alpha The stable investment strategy outperforms the cycle varying strategy out-of-sample While both our stable and cycle varying strategies performed well, the stable strategy performed better for long-short and long only and had higher alphas  Our cycle varying strategy had more consistent performance, beating the market in 7 out of 8 years, but was not clearly able to add alpha or returns over a stable strategy Best Strategy (highest alpha): Buy the long-short stable investment portfolio Regimes are based on regressions, and therefore highly predictable Missing a regime change by up to 2 months is does not seriously impact portfolio performance

Recommendations for Further Study Determine which factors specifically failed out of sample Select less correlated factors Try to identify better performing regime definitions of the economic cycle Determine whether varying weights and factors in different regimes adds significant costs  Does it cost more to vary the weights or the factors?