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Jeudi 26 Janvier

16H15 : Laurent E. CALVET (EDHEC) "The Cross-Section of Household Preferences"

17H30 : Denisa BANULESCU (University of Orléans) "Volatility During the Financial Crisis Through the Lens of Higf Frequency Data : A Realized Garch Approach"  

 

 

 

16h15 : Laurent E. CALVET  (EDHEC)

THECROSS-SECTION OF HOUSEHOLD PREFERENCES

 

This paper estimates the cross-sectional distribution of preferences in a large administrative panel of Swedish households. We consider a life-cycle portfolio choice model, which incorporates risky labor income and risky financial, real estate, and retirement investments, and study middle-aged households grouped by education, industry of employment, and birth cohort. We estimate the model using the Method of Simulated Moments to match the evolution of wealth and the risky portfolio share over time. The model allows for heterogeneity in risk aversion, the elasticity of intertemporal substitution (EIS), and the rate of time preference. When all three parameters are unrestricted, they are weakly identified and we consider alternative parameter restrictions to address this problem. We obtain moderate estimates of risk aversion and values of the EIS that are always greater than the reciprocal of risk aversion, always less than one, and weakly negatively correlated with risk aversion. We find that households with higher education have higher EIS, while households in risky occupations have lower risk aversion.

Papier joint avec :  John Y. Campbell, Francisco J. Gomes, and Paolo Sodini.

 

17H30 : Denisa BANULESCU (University of Orléans)

VOLATILITY DURING THE FINANCIAL CRISIS THROUGH THE LENS OF HIGH FREQUENCY DATA : A REALIZED GARCH APPROACH.

We study financial volatility during the global financial crisis and use the largest volatility shocks to identify major events during the crisis. Our analysis makes extensive use of high frequency (HF) financial data to model volatility and, importantly, to determine the timing within the day when the largest volatility shocks occurred. The latter helps us identify the events that can be associated with each of these shocks, and serves to illustrate the benefits of using high-frequency data. Some of the largest volatility shocks coincide, not surprisingly, with the bankruptcy of Lehman Brothers on September 15, 2008 and Congress’s failure to pass the Emergency Economic Stabilization Act on September 29, 2008. The day with the largest volatility shock was February 27, 2007 – the date when Freddie Mac announced a stricter policy for underwriting subprime loans and a date that was marked by a crash on the Chinese stock market. However, the intraday HF data shows that the main culprit was a computer glitch in the trading system. The days with the largest drops in volatility can in most cases be related to interventions by governments and central banks.

Papier joint avec Peter Reinhard Hansen, and Zhuo Huang.