We construct an affine model that incorporates bond risk premia. By understanding risk premia, we are able to use a lot of information from well-measured risk-neutral dyanmics to characterize real expectations. We use the model to decompose the yield curve into expected interest rate and risk premium components. We characterize the interesting term structure of risk premia — a forward rate reflects expected excess returns many years into the future, and current slope and curvature factors forecast future expected returns even though they do not forecast current returns.

This paper quantifies how variation in real economic activity and inflation in the U.S. influenced the market prices of level, slope, and curvature risks in U.S. Treasury markets. To accomplish this we develop a novel arbitrage-free DT SM in which macroeconomic risks – in particular, real output and inflation risks – impact bond investment decisions separately from information about the shape of the yield curve. Estimates of our preferred macro-DT SM over the twenty-three year period from 1985 through 2007 reveal that unspanned macro risks explained a substantial proportion of the variation in forward terms premiums. Unspanned macro risks accounted for nearly 90 % of the conditional variation in short-dated forward term premiums, with unspanned real economic growth being the key driving factor. Over horizons beyond three years, these effects were entirely attributable to unspanned inflation. Using our model, we also reassess some of Chairman Bernanke’s remarks on the interplay between term premiums, the shape of the yield curve, and macroeconomic activity.

We analyze financial risk premiums and real economic dynamics in a DSGE model with three types of agents- shareholders, bondholders and workers- that differ in participation in the capital market and in attitude towards risk and intertemporal substitution. Aggregate productivity and distribution risks are transferred across these agents via the bond market and via an efficient labor contract. The result is a combination of volatile returns to capital and a highly cyclical consumption process for the shareholders, which are two important ingredients for generating high and countercyclical risk premiums. These risk premiums are consistent with a strong propagation mechanism through an elastic supply of labor, rigid real wages and a countercyclical labor share. Based on the empirical estimates for the two sources of real macroeconomic risk, the model generates signi…cant and plausible time variation in both bond and equity risk premiums. Interestingly, the single largest jump in both the risk premium and the price of risk is observed during the current recession.

We provide an axiomatic model of preferences over atemporal risks that generalizes Gul’s disappointment aversion model by allowing risk aversion to be “first order ” at locations in the state space that do not correspond to certainty. Since the lotteries being valued by an agent in an asset-pricing context are not typically local to certainty, our generalization, when embedded in a dynamic recursive utility model, has important quantitative implications for financial markets. We show that the state-price process, or asset-pricing kernel, in a Lucas-tree economy in which the representative agent has generalized disappointment aversion preferences is consistent with the pricing kernel that resolves the equity-premium puzzle. In addition, we show that risk aversion in our model can be both state-dependent and counter-cyclical, which empirical research has demonstrated is necessary for explaining observed asset-pricing behavior.

andUniversityofMinnesota We present a pricing kernel that summarizes well the main features of the dynamics of interest rates and risk in postwar U.S. data and use it to uncover how the pricing kernel has moved with the short rate. Our findings imply that standard monetary models miss an essential link between the central bank instrument and the economic activity that monetary policy is intended to affect, and thus we call for a new approach to monetary policy analysis. We sketch a new approach using an economic model based on our pricing kernel. The model incorporates the key relationships between policy and risk movements in an unconventional way: the central bank’s policy changes are viewed as primarily intended to compensate for exogenous business cycle fluctuations in risk that threaten to push inflation off target. This model, while an improvement over standard models, is considered just a starting point for their revision. The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System. Modern models of monetary policy start from the assumption that the central bank controls an asset price, namely, the short rate, as its policy instrument. In these models, this

Stock market returns are signi…cantly higher on days when important macroeco-nomic news, such as that about ination, unemployment, or interest rates, is scheduled for announcement. The average announcement day excess return from 1958 to 2008 is 10.6 basis points versus 1.0 basis points for all the other days, suggesting that over 60 % of the cumulative annual equity risk premium is earned on announcement days. In contrast, the risk-free rate is detectably lower on announcement days, consistent with a precautionary saving motive. Our results demonstrate the required trade-o ¤ be-tween macroeconomic risk and asset returns, and provide an estimate of the premium investors demand to bear this risk. JEL Classi…cation: G12

We propose two performance measures for asset pricing models and apply them to representative agent models with recursive preferences, habits, and jumps. The measures describe the pricing kernel’s dispersion (the entropy of the title) and dynamics (horizon dependence, a measure of how entropy varies over different time horizons). We show how each model generates entropy and horizon dependence, and compare their magnitudes to estimates derived from asset returns. This exercise — and transparent loglinear approximations — clarify the mechanisms underlying these models. It also reveals, in some cases, tension between entropy, which should be large enough to account for observed excess returns, and horizon dependence, which should be small enough to account for mean yield spreads.

High interest rate currencies tend to appreciate. This is the uncovered interest rate parity (UIP) puzzle. It is primarily a statement about short-term interest rates and how they are related to exchange rates. Short-term interest rates are strongly affected by monetary policy. The UIP puzzle, therefore, can be restated in terms of monetary policy. When one country has a high interest rate policy relative to another, why does its currency tend to appreciate? We represent monetary policy as foreign and domestic Taylor rules. Foreign and domestic pricing kernels determine the relationship between these Taylor rules and exchange rates. We examine different specifications for the Taylor rule and ask which can resolve the UIP puzzle. We find evidence in favor of asymmetries. A foreign Taylor rule that is more procyclical than its domestic counterpart, generates a positive excess expected return on foreign currency. If foreign policy reacts relatively passively to inflation, the same is true. The combination of a weak inflation policy and a strong employment policy makes for a risky currency. This is broadly consistent with empirical evidence on ‘carry trade ’ funding and recipient currencies. When we calibrate our model to a particular currency pair — the United States and Australia — we find that our model is consistent with many empirical characteristics of real and nominal exchange rates, including the negative correlation between interest rate differentials and currency depreciation rates.

We provide a structural Bayesian equilibrium learning model that captures the interaction of the uncertainty about fundamentals of investors and the central bank. In our model central bank policy is able to affect fundamental state transitions and investors can learn about future fundamental states from observing policy variables. We show that investors ’ fear measures — implied volatility (ATMIV) and put-call implied volatility ratios (P/C) — lead industrial capacity utilization, which the central bank reacts to so the fear measures can be used to predict interest rates. The model endogenously generates several of the time series properties of option prices including the counter (pro) cyclicality of ATMIV (P/C), the V-shape (inverse V-shape) relation between ATMIV (P/C) and monetary policy variables, the positive relation between the level and absolute changes in ATMIV, the negative beta of volatility as a priced systematic risk factor, and an economically significant amount of time variation in the volatility premium.

We develop a class of dynamic term structure models that accommodates arbitrarily many interest-rate factors with very few parameters. The model builds on a cascade interest-rate dynamics that naturally ranks the factors by their rates of mean reversion, with each revolving around the next lower-frequency factor. The model further achieves dimension invariance by parameterizing the distributions of coefficients of the different frequency components. The net result is a class of term structure models with merely five parameters regardless of the number of factors. Using a panel of 15 LIBOR and swap rates, we estimate 15 models with one to 15 factors. The extensive estimation exercise shows that the 15-factor model significantly outperforms the other lower-dimensional specifications. The high-dimensional specification generates root mean squared pricing errors less than one basis point, thus making it an ideal candidate as a basis for forward rate curve stripping. The model also overcomes several known limitations of low-dimensional specifications by matching the observed low cross-correlations between changes in different interest rate series and by