We present a simple new explanation for the diversification discount in the valuation of firms. We demonstrate that, ceteris paribus, limited liability of equity holders is sufficient to explain a diversification discount. To derive this result, we use a credit risk model based on the value of...

"We use Markov Chain Monte Carlo (MCMC) methods for the parameter estimation and the testing of conditional asset pricing models. In contrast to traditional approaches, it is truly conditional because the assumption that time variation in betas is driven by a set of conditioning variables is not...

We use Bayesian model averaging to analyze industry return predictability in the presence of model uncertainty. The posterior analysis shows the importance of inflation and earnings yield in predicting industry returns. The out-of-sample performance of the Bayesian approach is, in general,...

We analyze whether newspaper content can predict aggregate future stock returns. Our study is based on articles published in the Handelsblatt, a leading German financial newspaper, from July 1989 to March 2011. We summarize newspaper content in a systematic way by constructing word-count indices...

Using a complete sample of US equity options, we analyze patterns of implied volatility in the cross-section of equity options with respect to stock characteristics. We find that high-beta stocks, small stocks, stocks with a low-market-to-book ratio, and non-momentum stocks trade at higher...

Markov Chain Monte Carlo (MCMC) methods have become very popular in financial econometrics during the last years. MCMC methods are applicable where classical methods fail. In this paper, we give an introduction to MCMC and present recent empirical evidence. Finally, we apply MCMC methods to...