I find that the standard class of a#ne models produces poor forecasts of future changes in Treasury yields. Better forecasts are generated by assuming that yields follow random walks. The failure of these models is driven by one of their key features: The compensation that investors receive for facing risk is a multiple of the variance of the risk. This means that risk compensation cannot vary independently of interest rate volatility. I also describe and empirically estimate a class of models that is broader than the standard a#ne class. These "essentially a#ne" models retain the tractability of the usual models, but allow the compensation for interest rate risk to vary independently of interest rate volatility. This additional flexibility proves useful in forming accurate forecasts of future yields. Address correspondence to the University of California, Haas School of Business, 545 Student Services Building #1900, Berkeley, CA 94720. Phone: 510-642-1435. Email address: du#ee@haas.b...

An estimated DSGE model: explaining variation in term premia

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—forecasting regressions and joint dynamic models of the term structure and macroeconomic variables—do not use this null. Their null is that excess returns are serially uncorrelated. This paper presents a dynamic model that satisfies the appropriate null. Simulation results show that finite-sample distributions

of Treasury repos. The intuition is that Treasury securities already function as a safe asset, thus in terms of safe asset creation, private Treasury repos are neutral. In the model, Treasury repos are beneficial because they shift risk (i.e. term premia) from relatively risk averse households to a more risk

Using data for U.S. and Canada, we find evidence of the time-varying nature of risk premia, which are obtained as difference between long term interest rates and their expected values. We then apply Kalman filtering to extract the conditional variance of term premia prediction errors; our results

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the future level of interest rates, is not entirely in line with rational behavior. There is strong evidence of time-variation in term premia. Furthermore, while this variation in term premia can be captured adequately by low-order members of the ARMA class models, there is clear evidence that conditional

of interest rates, is not entirely in line with what rational behaviour would suggest. We also find that there is strong evidence of time-variation in the term structure of interest rates. Furthermore, while this variation in term premia can be very well explained by low-order variations of the ARMA class

are modeled as a dampened power law process that nevertheless guarantees finiteness of moments of all orders. This renders model-implied mean equilibrium rates of return and equity and term premia finite. Comparison with a benchmark Gaussian process reveals that accounting for fat tails lowers the model