This study investigates if changes in risk-neutral systematic volatility, skewness, and kurtosis, are priced, either symmetrically or asymmetrically, as systematic risk factors in the cross-section of stock returns. The moments are constructed using options on the S&P 500, and represent...

High idiosyncratic volatility (IV) stocks follow predictable return pattern after exhibiting large ex ante returns: a period of underreaction and low returns is superseded by persistent high returns. This pattern is robust and economically significant: it may be interpreted as informationally...

We develop a novel machine learning method to estimate large dimensional time-varying GMM models via our newly designed ridge fusion regularization scheme. Our method is a one-step procedure and allows for abrupt, smooth and dual type time variation with a fast rate of convergence. It...

This chapter presents an empirical application of Bayesian MCMC estimation to the three main asset pricing models in use in the financial econometrics literature, namely, the Capital Asset Pricing Model (CAPM), the Fama-French (1992) three-factor model, and the Carhart (1997) four-factor model...

Households face earnings risk which is non-normal and varies by age and over the income distribution. We show that allowing for these rich features of earnings dynamics, in the context of a structurally estimated life-cycle portfolio choice model, helps to rationalize the limited participation...

The evaluation of quantiles (or VaR, Value at Risk) and that of CVaR, Conditional Value at Risk in risk management (or mean excess in actuarial sciences) is a very crucial point in the decision processes. Indeed, there are often great difficulties (or impossibilities) in finding the kind of...

This paper examines the profitability of investing according to environmental, social and governance (ESG) criteria in the U.S. and Europe. Based on data from 2003 to 2017, we show that a portfolio long in stocks with the highest ESG scores and short in those with the lowest scores yields a...

Value-at-Risk (VaR) forecasting generally relies on a parametric density function of portfolio returns that ignores higher moments or assumes them constant. In this paper, we propose a new simple approach to estimation of a portfolio VaR. We employ the Gram-Charlier expansion (GCE) augmenting...

We explore the issue of estimating a simple agent-based model of price formation in an asset market using the approach of Alfarano et al. (2008) as an example. Since we are able to derive various moment conditions for this model, we can apply generalized method of moments (GMM) estimation. We...

We study the well-known multiplicative Lognormal cascade process in which the multiplication of Gaussian and Lognormally distributed random variables yields time series with intermittent bursts of activity. Due to the non-stationarity of this process and the combinatorial nature of such a...