Yield Forecasts and Stochastic Volatility in Affine Models with Macro Factors

Affine term structure models (ATSMs) are known to have a trade-off in predicting future Treasury yields and fitting the time-varying volatility of interest rates. This paper empirically studies the role of macroeconomic variables in simultaneously achieving these two goals under affine models. To this end, we incorporate a liquidity demand theory via a measure of the velocity of money into affine models. We find that this considerably reduces the statistical tension between matching the first and second moments of interest rates. In terms of forecasting yields, the models with the velocity of money outperform among the ATSMs examined, including those with inflation and real activity. Our result is robust across maturities, forecasting horizons, risk price specifications, and the number of latent factors