We develop a new empirical approach to term structure analysis that allows testing for time-varying risk premiums and arbitrage opportunities in models with both unobservable factors and factors identified as the innovations to observed macroeconomic variables. Factors can play double roles as both covariance-generating common shocks driving yields and determinants of market prices of risk in cross-sectional pricing. The evidence favors time-varying risk prices significantly related to the second Stock–Watson principal component of macroeconomic variables and to changes in the industrial production index. Our preferred specification includes these two observable and two unobservable factors, with the no-arbitrage condition imposed.

Using high-frequency intraday futures prices to measure yield volatility at selected maturities, we find that daily yield curves carry incremental information about future interest rate risk at the long end, relative to that contained in the time series of historical volatilities. Some of the information in the yield curves is not captured by standard affine models. Our results point to the existence of an unspanned volatility factor. Both time series and yield curve based forecasts provide utility to a risk averse investor, relative to a random walk. Information from the two sources can be combined to enhance yield volatility forecasting performance.