Christophe Villa

The Predictive Power of the French Market Volatility Index: A Multi Horizons Study

The main purpose of this paper is to examine empirically the time series properties of the French Market Volatility Index (VX1). We also examine the VX1s ability to forecast future realized market volatility and finds a strong relationship. More importantly, we show how the index can be used to generate volatility forecasts over different horizons and that these forecasts are reasonably accurate predictors of future realized volatility. JEL classification codes: G14, C53, C13.

How common are common return factors across the NYSE and Nasdaq

We entertain the possibility of pervasive factors that are not common across two (or more) groups of securities. We propose and implement a general procedure to estimate the space spanned by common and group-specific pervasive factors. In our empirical analysis, we study the factor structure of excess returns on stocks traded on the NYSE and Nasdaq using our methodology. We find that there are only two common pervasive factors that govern the returns for both NYSE and Nasdaq. At the same time, the NYSE and Nasdaq each have one more group-specific factor that is not the same across the two exchanges. Our results point to the absence of complete similarity between the factors driving the returns on these exchanges.

Sources of Time Variation in the Covariance Matrix of Interest Rates

The main objective of this paper is to study the sources of time variation in the covariance matrix of interest rates. We depart from the traditional standard deviation–correlation decomposition of covariances and investigate whether time variation in the covariance matrix of bond yield changes is caused by time-varying eigenvalues and/or eigenvectors. On the basis of a formal testing procedure, we find that common factors display a clear time-varying volatility over the past three decades. Most notably, we observe that the switches in monetary policy that take place with the appointment of a new Federal Reserve chairman play an important role in characterizing the time variation in the loadings on the common factors that drive interest rates.

The information content of implied volatility, skewness and kurtosis: empirical evidence from long‐term CAC 40 options

The implied standard deviation is widely believed to be the best available forecast of the volatility of the returns over the remaining contract life (Jorion 1995). In this paper, we generalize this result to the higher moments of the distribution (Skewness and Kurtosis) based on a Gram-Charlier series expansion of the normal distribution (Corrado and Su 1996) using long term CAC 40 option prices contract, named PXL. First, we find that implied first moments contain a substantial amount of information for realized future moments of CAC 40 returns although this amount is decreasing with respect to the moments order. Second, we find that different shapes of the volatility smile are consistent with different distributions of the underlying returns. Based on these results, we also observe that including other implied moments significantly improve the out-of-sample pricing performance of the Black-Scholes (1973) model.

Recent Advances in Lending to the Poor with Asymmetric Information

Abstract  Microfinance institutions have successfully extended unsecured small loans to poor and opaque borrowers at the bottom of the economic pyramid. This success is largely due to innovative financial contracts that impose joint liability and create dynamic incentives to mitigate the effects of asymmetric information. Given recent advances in microfinance contracts, there is a need to map the theoretical developments. This article aims to accomplish that by performing a critical literature survey of microlending contracts, focussing on joint liability and dynamic incentives, bringing out some of the deficiencies of contract-theoretic propositions that cannot effectively account for the social mission of microfinance.

The dynamics of the term structure of interest rates: an Independent Component Analysis

The movements of a term structure of interest rates are commonly assumed to be driven by a small number of uncorrelated factors. Identified to the level, the slope, and the curvature, these factors are routinely obtained by a Principal Component Analysis (PCA) of historical bond prices (interest rates). In this paper, we focus on the Independent Component Analysis (ICA). The central assumption here is that observed multivariate time series reflect the reaction of a system to some (few) statistically independent time series. The ICA seeks to extract out independent components (ICs) as well as the mixing process. Both ICA and PCA are linear transform of the observed series. But, whereas a PCA obtains uncorrelated (principal) components, ICA provides statistically independent components. In contrast to PCA algorithms that use only second order statistical information, ICA algorithms (like JADE) exploit higher order statistical information for separating the signals. This approach is required when financial data are suspected to be not gaussian.