I am an Assistant Professor in the Finance Group at the Warwick Business School, University of Warwick (that I joined in the Fall of 2014). I was awarded a Ph.D. by the Department of Finance at Bocconi University in Spring 2014. My research interests span empirical asset pricing, financial econometrics, and commodity markets.
My research has been presented at conferences organized by the American Economic Association (AEA), the National Bureau of Economic Research (NBER), the Econometric Society, the European Finance Association (EFA), the Royal Economic Society (RES), the European Economic Association (EEA), the Society for Economic Dynamics (SED), and the Society for Financial Studies (SFS).
Warwick Business School
Scarman Road, CV4 7AL, Coventry, UK
+44 (0) 24 765 22701
Empirical asset pricing
My work on empirical asset pricing mostly relates to the time-series predictability of stock returns and the origins of their cross-sectional heterogeneity. This is not limited to equity returns but span alternative asset classes such as real estate, e.g. REIT, commodity and both treasury and corporate bonds. In a related line of research I am interested in understanding the frequency-specific properties of expected returns and the corresponding link with both returns predictability and portfolio allocations.
My research is primarily based on Bayesian econometric methods, in particular non-linear non-Gaussian state-space models, e.g. change-point dynamics and dynamic Poisson regressions. A recent part of my pipeline relates to developing multi-scale time-series models to characterise the frequency-specific information content of alternative economic predictors in modeling expected returns.
My research on commodity markets mainly relates to the modeling of investors' expectations and the corresponding dynamics of the risk premia implied by a typical expectations hypothesis. I recently started to investigate the linkages between the unexpected growth rate of the economy and time-series momentum in returns on commodity futures across products.