Mathematical models of bond pricing are used by both academics and Wall Street practitioners, with practitioners introducing time-dependent parameters to fit 'arbitrage-free' models to selected asset prices. The authors show, in a simple one-factor setting, that the ability of such models to...

Mathematical models of bond pricing are used by both academics and Wall Street practitioners, with practitioners introducing time-dependent parameters to fit arbitrage-free models to selected asset prices. We show, in a simple one-factor setting, that the ability of such models to reproduce a...

We use asset returns to characterize the properties of the pricing kernel, including its volatility (measured by entropy) and time-dependence. Then we explore similar properties of a number of popular representative agent models: long-run risk, time-varying volatility and risk, several versions...

We inject aggregate uncertainty — risk and ambiguity — into an otherwise standard business cycle model and describe its consequences. We find that increases in uncertainty generally reduce consumption, but they do not account, in this model, for either the magnitude or the persistence of the...

type="main" <title type="main">ABSTRACT</title> <p>We propose two data-based performance measures for asset pricing models and apply them to models with recursive utility and habits. Excess returns on risky securities are reflected in the pricing kernel's dispersion and riskless bond yields are reflected in its dynamics. We...</p>

Asset pricing implications for business cycle analysis David Backus, Bryan Routledge, and Stanley Zin Although the stochastic growth model has become the benchmark for business cycle analysis, many of its implications for asset prices and returns are grossly counterfactual. For example, the...