Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with non-parametric estimation of the pricing kernel (Empirical Pricing Kernel) given by the ratio of the risk-neutral density estimator and the subjective density estimator. The...

Pricing kernels implicit in option prices play a key role in assessing the risk aversion over equity returns. We deal with nonparametric estimation of the pricing kernel (Empirical Pricing Kernel) given by the ratio of the risk-neutral density estimator and the subjective density estimator. The...

The goal of this article is an exact Bayesian analysis of the Heston (1993) stochastic volatility model. We carefully study the effect different parameterizations of the latent volatility process and the parameters of the volatility process have on the convergence and the mixing behavior of the...

Derivatives on the Chicago Board Options Exchange volatility index (VIX) have gained significant popularity over the last decade. The pricing of VIX derivatives involves evaluating the square root of the expected realised variance which cannot be computed by direct Monte Carlo methods. Least...

Least squares Monte Carlo (LSM) is an approximate dynamic programming (ADP) technique commonly used for the valuation of high dimensional financial and real options, but has broader applicability. It is known that the regress-later version of this method is an approximate linear programming...

Recently, simulation methods combined with regression techniques have gained importance when it comes to American option pricing. In this paper we consider such methods and we examine numerically their convergence properties. We first consider the Least Squares Monte-Carlo (LSM) method of...

This paper presents a practical volatility estimation method for cash flow simulation based real option valuation with changing volatility. During cash flow simulation, present value of the future cash flows and their corresponding cash flow state variable values are recorded for all time...

We present a non-parametric Monte-Carlo method for computing the price of an option in an uncertain volatility model. We use the link between second-order BSDE and non-linear second order parabolic PDEs to derive a numerical scheme that gives a fast and accurate estimation of the optimal...

The parametric estimation of stochastic differential equations (SDEs) has been the subject of intense studies already for several decades. The Heston model, for instance, is based on two coupled SDEs and is often used in financial mathematics for the dynamics of asset prices and their...