Methodological Advances in Estimating Non-Gaussian Consumption-Based Asset Pricing Models: We contribute to the literature of rare disaster events by constructing a robust methodol ...
Assistant Professor at NEOMA Business School (France)
Methodological Advances in Estimating Non-Gaussian Consumption-Based Asset Pricing Models: We contribute to the literature of rare disaster events by constructing a robust methodology for estimating non-Gaussian extensions of the standard CCAPM. We demonstrate theoretically that, in the presence of consumption rare disaster events, all cumulants of order strictly higher than two help solve the risk-free rate and the equity premium puzzles. We show empirically that when rare disaster events are truly pronounced, cumulants up to order twelve, impact asset prices signi cantly. By allowing dividends and consumption growth to be non-collinear, we are able, in the presence of disasters, to identify high order co-dependency risks that cannot be summarized by the covariance between consumption growth and asset returns. Using monthly US consumption data, we build a robust single country estimation procedure that reveals that non-durables and total consumption are subject to rare disaster events. For non-durables and services, however, we reject the rare disaster event hypothesis.
Housing Rare Disaster Events, Asset Prices and the Term Structure of Interest Rates: We introduce a housing consumption-based asset pricing model that incorporates rare disaster events into the dynamics of consumption. Using US aggregate consumption data in a robust maximum likelihood estimation approach, we show that rare disaster events in non-housing consumption contribute only marginally to explaining the low risk-free rate and the high equity premium observed in the data. Instead, it is the housing rare disaster events that are able to solve the risk-free rate, the equity premium and the volatility puzzles and this for moderate levels of risk aversion and intra-temporal elasticity of substitution. Additionally, we show that housing rare disaster events tend to produce steeper yield curves.To obtain our results, we develop a novel analytical framework that hinges on two key ideas. The rst one extends the Cumulant Generating Function-based pricing formulas of Martin (2013) to a two goods economy. The second idea uses exponential affine approximations for the price-dividend ratio. These techniques enable us to derive compact and intuitive closed form solutions for the risk-free rate, risk premia and discount bond yields.
|Thesis Committee :||
Supervisor: Abraham Lioui, EDHEC Business School
External reviewer: Harjoat Bhamra, Imperial College
Other committee members: René Garcia and Raman Uppal, EDHEC Business School