Expectation Puzzles, Time-varying Risk Premia, and Dynamic Models of the Term Structure

Though linear projections of returns on the slope of the yield curve have contradicted the implications of the traditional expectations theory,' we show that these findings are not puzzling relative to a large class of richer dynamic term structure models. Specifically, we are able to match all of the key empirical findings reported by Fama and Bliss and Campbell and Shiller, among others, within large subclasses of affine and quadratic-Gaussian term structure models. Additionally, we show that certain risk-premium adjusted' projections of changes in yields on the slope of the yield curve recover the coefficients of unity predicted by the models. Key to this matching are parameterizations of the market prices of risk that let the risk factors affect the market prices of risk directly, and not only through the factor volatilities. The risk premiums have a simple form consistent with Fama's findings on the predictability of forward rates, and are shown to also be consistent with interest rate, feedback rules used by a monetary authority in setting monetary policy.

Interpreting Recent Changes in the Credit Spreads of Japanese Banks

This paper examines the recent period of relatively low credit spreads in Japan, with particular emphasis on the marketfs assessments of the credit risks of large Japanese banks implicit in the prices of credit derivatives. We extract the market-price implied likelihood of a credit event in the future, and explore the nature of the default risk premiums underlying recent changes in bank bond and credit derivatives prices. We document substantial increases in the gjump-at- defaulth default risk premiums for the large Japanese banks examined during the early part of 2006. These patterns in risk premiums are related to the recent patterns in market indicators of global event risk, local equity market volatility, and an estimate of the duration of the Bank of Japanfs zero interest rate policy.Default risk premium; Credit default swap; Japanese banks; Zero interest rate policy; Event risk

Transform Analysis and Asset Pricing for Affine Jump-Diffusions

In the setting of affine' jump-diffusion state processes, this paper provides an analytical treatment of a class of transforms, including various Laplace and Fourier transforms as special cases, that allow an analytical treatment of a range of valuation and econometric problems. Example applications include fixed-income pricing models, with a role for intensityy-based models of default, as well as a wide range of option-pricing applications. An illustrative example examines the implications of stochastic volatility and jumps for option valuation. This example highlights the impact on option 'smirks' of the joint distribution of jumps in volatility and jumps in the underlying asset price, through both amplitude as well as jump timing.

Efficient Estimation of Linear Asset Pricing Models with Moving-Average Errors

This paper explores in depth the nature of the conditional moment restrictions implied by log-linear intertemporal capital asset pricing models (ICAPMs) and shows that the generalized instrumental variables (GMM) estimators of these models (as typically implemented in practice) are inefficient. The moment conditions in the presence of temporally aggregated consumption are derived for two log-linear ICAPMs. The first is a continuous time model in which agents maximize expected utility. In the context of this model, we show that there are important asymmetries between the implied moment conditions for infinitely and finitely-lived securities. The second model assumes that agents maximize non-expected utility, and leads to a very similar econometric relation for the return on the wealth portfolio. Then we describe the efficiency bound (greatest lower bound for the asymptotic variances) of the CNN estimators of the preference parameters in these models. In addition, we calculate the efficient CNN estimators that attain this bound. Finally, we assess the gains in precision from using this optimal CNN estimator relative to the commonly used inefficient CMN estimators.

Schedule network node time distributions and arrow criticalities

This research develops exact methods to calculate project duration distributions and to calculate Van Slyke\u27s (1963) criticality for arrows, the probability that an arrow is on a critical path, assuming nonnegative integer duration distributions. These calculations for project duration distributions correct estimates made by the Program Evaluation and Review Technique (PERT), and the Van Slyke criticality calculations extend the arrow criticality analysis by the Critical Path Method (CPM) into the probabilistic realm;Exact methods for calculating project duration distributions and Van Slyke\u27s criticality are demonstrated on series networks, parallel networks, parallel-series networks, and the Wheatstone network. The Van Slyke criticality equation for parallel networks is in a form that appears to improve upon one proposed by Dodin & Elmaghraby (1985). The present form is generalized to, in principle, include all networks;The exact methods are enhanced by developing a procedure to limit the number of calculations needed to analyze large networks. The procedure identifies paths through a large network, calculates the minimum and maximum path durations, and ranks the paths by duration. A smaller skeletal network is constructed from the arrows of the longest paths and is analyzed by exact methods. The procedure emphasizes accuracy for the longer project durations, of greatest concern to project managers and schedulers, while limiting the number of necessary calculations;The procedure for large networks is illustrated on the 40-arrow Kleindorfer (1971) network. Of the 51 Kleindorfer paths, the procedure selected 6 paths to construct a skeletal network. Analysis of the skeletal network yields a project duration distribution that is correct in its range and in the duration probabilities for the upper 5% of the distribution. Analysis results are compared with SLAM II and FORTRAN simulations. No arrow criticality appears to be seriously miscalculated. The project duration distribution is calculated to be bimodal, in keeping with the simulation;Conditions under which the just mentioned bimodality can occur are determined for parallel, normally-distributed paths. The large-network procedure warns when these oddly shaped distributions are possible

Term Structure Dynamics in Theory and Reality

This paper is a critical survey of models designed for pricing fixed income securities and their associated term structures of market yields. Our primary focus is on the interplay between the theoretical specification of dynamic term structure models and their empirical fit to historical changes in the shapes of yield curves. We begin by overviewing the dynamic term structure models that have been fit to treasury or swap yield curves and in which the risk factors follow diffusions, jump-diffusion, or have \switching regimes." Then the goodness-of- ts of these models are assessed relative to their abilities to: (i) match linear projections of changes in yields onto the slope of the yield curve; (ii) match the persistence of conditional volatilities, and the shapes of term structures of unconditional volatilities, of yields; and (iii) to reliably price caps, swaptions, and other fixed-income derivatives. For the case of defaultable securities we explore the relative fits to historical yield spreads

Term Structure Dynamics in Theory and Reality

This paper is a critical survey of models designed for pricing fixed income securities and their associated term structures of market yields. Our primary focus is on the interplay between the theoretical specification of dynamic term structure models and their empirical fit to historical changes in the shapes of yield curves. We begin by over viewing the dynamic term structure models that have been fit to treasury or swap yield curves and in which the risk factors follow diffusions, jump-diffusion, or have \switching regimes." Then the goodness-of- ts of these models are assessed relative to their abilities to: (i) match linear projections of changes in yields onto the slope of the yield curve; (ii) match the persistence of conditional volatilities, and the shapes of term structures of unconditional volatilities, of yields; and (iii) to reliably price caps, swaptions, and other fixed-income derivatives. For the case of defaultable securities we explore the relative ts to historical yield spreads