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Full-Text Articles in Social and Behavioral Sciences

On The Robustness Of The Positive Relation Between Expected Idiosyncratic Volatility And Expected Return, Fangjian Fu Dec 2010

On The Robustness Of The Positive Relation Between Expected Idiosyncratic Volatility And Expected Return, Fangjian Fu

Research Collection Lee Kong Chian School Of Business

My 2009 JFE paper ["Idiosyncratic Risk and the Cross-Section of Expected Stock Returns', Journal of Financial Economics, Vol. 91, pp. 24-37] documents a positive and statistically significant cross-sectional relation between expected idiosyncratic volatility (E(IVOL)) and expected stock return. A recent working paper titled "On the Relation between EGARCH Idiosyncratic Volatility and Expected Stock Returns" by Guo, Ferguson, and Kassa of University of Cincinnati suggests that the positive relation is driven by an in-sample approach to estimate E(IVOL). They fail to find a significant relation between return and their E(IVOL) estimated out of sample. I find that two estimation settings in …


Bayesian Analysis Of Structural Credit Risk Models With Microstructure Noises, Shirley J. Huang, Jun Yu Nov 2010

Bayesian Analysis Of Structural Credit Risk Models With Microstructure Noises, Shirley J. Huang, Jun Yu

Research Collection Lee Kong Chian School Of Business

In this paper a Markov chain Monte Carlo (MCMC) technique is developed for the Bayesian analysis of structural credit risk models with microstructure noises. The technique is based on the general Bayesian approach with posterior computations performed by Gibbs sampling. Simulations from the Markov chain, whose stationary distribution converges to the posterior distribution, enable exact finite sample inferences of model parameters. The exact inferences can easily be extended to latent state variables and any nonlinear transformation of state variables and parameters, facilitating practical credit risk applications. In addition, the comparison of alternative models can be based on devian information criterion …