Predicting fixed income credit spread movements March 1, 2001 Mary Murphy Luisa Rubino Steve Smigie Gigi Widham

Summary Prediction of direction and magnitude of credit spread movements for: 10-year US Swap Spread spread between US corporate AAA 7-10 year and 10-year Treasury Bond spread between US corporate BBB 7-10 year and the 10-year Treasury Bond Prediction was most successful for the spread between AAA and 10-year T-Bond Trading strategy produces an annualized alpha of 1.01% Predictive power can be used to test other trading strategies

Why Credit spreads? Increase in significance of corporate debt in fixed income portfolio management Decrease in supply of Treasury bonds Reduction in number of fixed income asset classes in Europe Relevance of credit risk for fixed income investors

Historical trends Swap spreads Corporate spreads

Methodology Reviewed existing research Focused on financial variables Used in-sample data from January 1990 to December 1999 Tested models out of sample from January 2000 to December 2000

Variables Lag of the change in S&P 500 P/E Lag of the S&P 500 P/E Lag of the change in the VIX Lag of the change 30-year Treasury Bond future volatility Lag of the change in the 10 year on/off spread Lag of the change in the yield of 10-year Treasury bonds Lag of the spread btwn BBB and the AAA yields (7-10yr maturities) Lag of the change in spread between the 10 year T-bond and 3 Month T-bill Lag of change of each credit spread Lag of each credit spread

Models AAA Spread t = AAA Spread t Swap Spread t S&P500 P/E t-1 BBB Spread t = – AAA Spread t Swap Spread t yr T-bond t S&P500 P/E t BBB - AAA t-1 Swap Spread t = S&P500 PE t Swap Spread t-1 – S&P500 P/E t BBB Spread t-1

Interpretation of models

Trading strategy Long position in BBB corporate bonds and short equal amount in 10 year Treasury bond when model predicts that credit spreads tighten Results: (vs. benchmark of 30 day Euro$)

Conclusions/future paths of study Credit spread movements are predictable Models include valuable information to predict business cycle Future research could test trading strategies that capitalize on the predictive power

Q & A