We examine the effects of estimation risk and Bayesian learning on equilibrium asset prices when there is uncertainty about both the first and second moments of consumption and dividend growth rates. For the 1891-2007 period, our model generates a sizable average annual equity premium,...

Using a Bayesian time‐varying beta model, we explore how the systematic risk exposures of hedge funds vary over time conditional on some exogenous variables that managers are assumed to use in changing their trading strategies. In such a setting, we impose a structure on fund returns, betas...

In this paper, I build a Dynamic Stochastic General Equilibrium (DSGE) model and estimate it using Bayesian Markov Chain Monte Carlo (MCMC) methods. I use the results in order to examine how asset prices and macroeconomic quantities respond to the di erent shocks in the economy. Fluctuations in...

In this paper we reviewed two findings pertinent for using asset market data to make inferences about the intangible capital stock. We presented evidence familiar from the empirical finance literature that returns are heterogeneous when firms are grouped according to their ratio of market equity...

This internet appendix provides simulation results that compare the Bayesian model averaging approach (BMA) with alternative proxy selection approaches. For more information, refer to the main paper.The paper "Model Uncertainty and Expected Return Proxies'" to which these Appendices apply is...

We examine the effects of parameter uncertainty and Bayesian learning on equilibrium asset prices when all the structural parameters of the aggregate consumption and dividend growth rate processes are unknown. With realistic calibration of a parsimonious set of prior parameters, the model...

Long-run risk models, a cornerstone in the macro-finance literature for their ability to capture key asset price phenomena, are known to entail implausibly high levels of timing and risk premia. Our paper resolves this puzzle by considering consumption of durable goods in addition to that of...

The Intertemporal Capital Asset Pricing Model (ICAPM) predicts that an unobservable factor capturing changes in expected market returns should be priced in the cross section. My Bayesian framework accounts for uncertainty in the intertemporal risk factor and gauges the effects of prior...

Over the last two decades, alternative expected return proxies have been proposed with substantially lower variation than realized returns. This helped to reduce parameter uncertainty and to identify many seemingly robust relations between expected returns and variables of interest, which would...

A representative consumer uses Bayes' law to learn about parameters of several models and to construct probabilities with which to perform ongoing model averaging. The arrival of signals induces the consumer to alter his posterior distribution over models and parameters. The consumer's...