Roméo Tedongap

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Staff working papers

The Term Structures of Loss and Gain Uncertainty

We investigate the uncertainty around stock returns at different investment horizons. Since a return is either a loss or a gain, we categorize return uncertainty into two components—loss uncertainty and gain uncertainty. We then use these components to evaluate investment.

Which Parametric Model for Conditional Skewness?

Staff Working Paper 2013-32 Bruno Feunou, Mohammad R. Jahan-Parvar, Roméo Tedongap
This paper addresses an existing gap in the developing literature on conditional skewness. We develop a simple procedure to evaluate parametric conditional skewness models. This procedure is based on regressing the realized skewness measures on model-implied conditional skewness values.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C2, C22, C5, C51, G, G1, G12, G15

Risk Premium, Variance Premium and the Maturity Structure of Uncertainty

Expected returns vary when investors face time-varying investment opportunities. Long-run risk models (Bansal and Yaron 2004) and no-arbitrage affine models (Duffie, Pan, and Singleton 2000) emphasize sources of risk that are not observable to the econometrician.
Content Type(s): Staff research, Staff working papers Topic(s): Asset pricing, Financial services JEL Code(s): G, G1, G12, G13

The Equity Premium and the Volatility Spread: The Role of Risk-Neutral Skewness

Staff Working Paper 2009-20 Bruno Feunou, Jean-Sébastien Fontaine, Roméo Tedongap
We introduce the Homoscedastic Gamma [HG] model where the distribution of returns is characterized by its mean, variance and an independent skewness parameter under both measures. The model predicts that the spread between historical and risk-neutral volatilities is a function of the risk premium and of skewness.
Content Type(s): Staff research, Staff working papers Topic(s): Financial markets JEL Code(s): G, G1, G12, G13

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