Title: Individual stock variance premia properties
Authors: Jeroen Rombouts - ESSEC Business School (France) [presenting]
Francesco Violante - ENSAE ParisTech (France)
Lars Stentoft - University of Western Ontario (Canada)
Abstract: For the individuals stock of the S\&P 500 index, the aim is to estimate the Variance Risk Premium, defined as the difference between risk neutral and physical expectations of an asset's total return variation which has market return predictability and is of fundamental importance for validation and development of new asset pricing models. Variance swap payoffs are highly volatile time series, with time varying variance levels and extreme payoffs during volatile market conditions, and to extract the VRP we use signal extraction techniques based on a state-space representation of the model and the Kalman-Hamilton filter. Our proposed approach provides measurement error free estimates of the part of the VRP related to normal market conditions, and allows constructing variables indicating agents' expectations under extreme market conditions. The framework only requires option implied volatility, e.g. the VIX index for the S\&P 500, data and daily returns for the underlying, the sources of which are free and readily available for many assets.