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Abstract In any canonical Gaussian dynamic term structure model (GDTSM), the conditional forecasts of the pricing factors are invariant to the imposition of no-arbitrage restrictions. This invariance is maintained even in the presence of a variety of restrictions on the factor structure of bond yields. To establish these results, we develop a novel canonical GDTSM in which the pricing factors are observable portfolios of yields. For our normalization, standard maximum likelihood algorithms converge to the global optimum almost instantaneously. We present empirical estimates and out-of-sample forecasts for several GDTSMs using data on U.S. Treasury bond yields.

When Japanese short-term bond yields were near their zero bound, yields on longterm bonds showed substantial fluctuation, and there was a strong positive relationship between the level of interest rates and yield volatilities/risk premia. We explore whether several families of dynamic term structure models that enforce a zero lower bound on short rates imply conditional distributions of Japanese bond yields consistent with these patterns. Multi-factor “shadow-rate ” and quadratic-Gaussian models, evaluated at their maximum likelihood estimates, capture many features of the data. Furthermore, model-implied risk premiums track realized excess returns during extended periods of near-zero short rates. In contrast, the conditional distributions implied by non-negative affine models do not match their sample counterparts, and standard Gaussian affine models generate implausibly large negative risk premiums.

Abstract We propose an arbitrage-free stochastic discount factor (SDF) model that jointly prices the cross-section of returns on portfolios of stocks sorted on book-to-market dimension, the cross-section of government bonds sorted by maturity, the dynamics of bond yields, and time series variation in expected stock and bond returns. Its pricing factors are motivated by a decomposition of the pricing kernel into a permanent and a transitory component. Shocks to the transitory component govern the level of the term structure of interest rates and price the cross-section of bond returns. Shocks to the permanent component govern the dividend yield and price the average equity returns. Third, shocks to the relative contribution of the transitory component to the conditional variance of the SDF govern the Cochrane-Piazzesi (2005, CP) factor, a strong predictor of future bond returns. These shocks price the crosssection of book-to-market sorted stock portfolios. Because the CP factor is a strong predictor of economic activity one-to two-years ahead, shocks to the importance of the transitory component signal improving economic conditions. Value stocks are riskier and carry a return premium because they are more exposed to such shocks.

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ABSTRACT This article develops a new family of Gaussian macro-dynamic term structure models (MTSMs) in which bond yields follow a lowdimensional factor structure and the historical distribution of bond yields and macroeconomic variables is characterized by a vectorautoregression with order p > 1. Most formulations of MTSMs with p > 1 are shown to imply a much higher dimensional factor structure for yields than what is called for by historical data. In contrast, our "asymmetric" arbitrage-free MTSM gives modelers the flexibility to match historical lag distributions with p > 1 while maintaining a parsimonious factor representation of yields. Using our canonical family of MTSMs we revisit: (i) the impact of no-arbitrage restrictions on the joint distribution of bond yields and macro risks, comparing models with and without the restriction that macro risks are spanned by yield-curve information; and (ii) the identification of the policy parameters in Taylor-style monetary policy rules within MTSMs with macro risk factors and lags. ( JEL: G12,E43, C58, E58) KEYWORDS: Macro-finance term structure model, Lags, Taylor Rule Identification Dynamic term structure models in which a subset of the pricing factors are macroeconomic variables (MTSMs) often have bond yields depending on lags of these factors. 1 As typically parameterized, such MTSMs imply that the cross-section

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In fixed income markets, volatility is unspanned if volatility risk cannot be hedged with bonds. We first show that all affine term structure models with state space RM+ ×RN−M can be drift normalized and show when the standard variance normalization can be obtained. Using this normalization, we find conditions for a wide class of affine term structure models to exhibit unspanned stochastic volatility (USV). We show that the USV conditions restrict both the mean reversions of risk factors and the cross section of conditional yield volatilities. The restrictions imply that previously studied affine USV models are unlikely to be able to generate the observed cross section of yield volatilities. However, more general USV models can match the cross section of bond volatilities. 1.

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Abstract We reconsider the role of financial intermediaries in monetary economics. We explore the hypothesis that financial intermediaries drive the business cycle by way of their role in determining the price of risk. In this framework, balance sheet quantities emerge as a key indicator of risk appetite and hence of the "risk-taking channel" of monetary policy. We document evidence that the balance sheets of financial intermediaries reflect the transmission of monetary policy through capital market conditions. Our findings suggest that the traditional focus on the money stock for the conduct of monetary policy may have more modern counterparts, and we suggest the importance of tracking balance sheet quantities for the conduct of monetary policy.