Mungo Wilson’s research is concerned with asset pricing.
A recent paper on credit ratings co-written with Jens Hilscher, challenges ratings’ position as the most widely used measure of corporate credit quality and demonstrates that ratings are not optimal estimates of raw default probability.
‘Our research shows that ratings are not an optimal predictor of default. They explain little of the variation in default probability across firms and they fail to capture the considerable variation in default probabilities and empirical failure rate over the business cycle’ says Wilson.
The researchers conclude that, given the nature of credit risk, a narrow focus on only one measure of credit quality reduces the accuracy of default prediction and, therefore, cannot be an optimal measure of credit quality. Instead, a more accurate and useful measure would be to separate default prediction from the measurement of systematic risk. Default prediction data could update frequently and rapidly and respond to firm-specific news, while measures of systematic risk could be a combination of current credit ratings and aggregate credit conditions.
Hilscher, J. and Wilson, M., Credit Ratings and Credit Risk, working paper, January 2012
Macroeconomic conditions and asset prices
In recent years, Wilson has published two important papers which discuss the role of macroeconomic risk in determining asset prices.
One major finding of Wilson’s work came out of research into the effects on stock markets of important macroeconomic announcements, such as inflation, unemployment or interest rates. His research has shown that 60 percent of the cumulative annual US equity risk premium was earned on these announcement days in the past half-century. The resulting insights may help to characterise the trade-off between macroeconomic risk and asset returns.
Wilson, M. and Savor, P., How much do investors care about systematic risk? Evidence from scheduled economic announcements, Journal of Financial and Quantitative Analysis (Forthcoming)
Elsewhere in his research, Wilson has offered a new method of measuring aggregate risk. He has demonstrated that the average correlation between pairs of stocks can be used to predict future market excess returns far more successfully than previously used measures – such as estimates of the variance of stock market returns.
Pollet, J. and Wilson, M., Average Correlation and Stock Market Returns, Journal of Financial Economics, June 2010.
A further, unpublished, paper on earnings announcements shows how to explain the puzzling phenomenon that the returns on stocks of firms announcing their earnings outperform other stocks by a large margin.
Savor, P. and Wilson, M., Earnings Announcements and Systematic Risk, AFA 2012 Chicago Meetings Paper, December 2011.
Wilson’s research also explores mutual funds. A recent paper demonstrates that large mutual funds alter their investment behaviour in ways previously often ignored.
Wilson, M. and Pollet, J., How Does Size Affect Mutual Fund Behavior? Journal of Finance, December 2008.
Information transmission across markets
Wilson’s recent research looks at the patterns of serial dependence in returns in the equity and CDS (Credit Default Swap) markets. The research establishes that CDS markets almost always respond sluggishly to news first revealed in equity market returns, suggesting that informed traders are not primarily active in CDS markets.
Hilscher, J., Pollet, J., and Wilson, M., Are Credit Default Swaps a Sideshow? Evidence that Information Flows from Equity to CDS Markets, working paper, September 2011.