The calibration of financial models has become rather important topic in recent years mainly because of the need to price increasingly complex options in a consistent way. The choice of the underlying model is crucial for the good performance of any calibration procedure. Recent empirical...

We study the estimation, the dynamics, and the predictability of option-implied risk-neutral moments (variance, skewness, and kurtosis) for individual stocks from various perspectives. We first show that it is in the estimation of the higher moments essential to use an interpolation with a...

This paper studies the factor structure of the cross-section of delta-hedged equity option returns. We find that a four-factor model explains the cross-section and time-series of equity option returns. Out of the four factors, three are characteristic based factors from the long-short option...

This report provides an overview of the utility of single stock and custom basket options in fund management. It is shown that managers of active equity funds can limit possible negative return contributions of their over - and underweight positions via single stock options and thus help to...

This paper evaluates the underperformance of individual equity options relative to their replicating portfolios. Considering a high-dimensional set of variables, we use a machine learning approach to identify the characteristics of options and their underlying stocks that provide incremental...

Financial models are largely used in option pricing. These physical models capture several salient features of asset price dynamics. The pricing performance can be significantly enhanced when they are combined with nonparametric learning approaches, that empirically learn and correct pricing...

This paper studies polar sets of anisotropic Gaussian random elds, i.e. sets which a Gaussian random eld does not hit almost surely. The main assumptions are that the eigenvalues of the covariance matrix are bounded from below and that the canonical metric associated with the Gaussian random eld...

State price density (SPD) contains important information concerning market expectations. In existing literature, a constrained estimator of the SPD is found by nonlinear least squares in a suitable Sobolev space. We improve the behavior of this estimator by implementing a covariance structure...

This paper presents a set of probability density functions for Euribor outturns in three months’ time, estimated from the prices of options on Euribor futures. It is the first official and freely available dataset to span the complete history of Euribor futures options, thus comprising over...

We introduce a novel semi-parametric estimator of the price of American options in a discrete time, Markovian framework. The estimator is based on a parametric specification of the stochasticdiscount factor and is non-parametric w.r.t. the historical dynamics of the state variables. The...