This paper studies the relation between the uncertainty of volatility, measured as the volatility of volatility, and future delta-hedged equity option returns. We find that delta-hedged option returns consistently decrease in uncertainty of volatility. Our results hold for different measures of...

In the existing literature on barrier options, much effort has been exerted to ensureconvergence through placing the barrier in close proximity to, or directly onto, thenodes of the tree lattice. In this paper we show that this may not be necessary toachieve accurate option price...

We model the dynamics of asset prices and associated derivatives by considerationof the dynamics of the conditional probability density process for the value of an assetat some specied time in the future. In the case where the asset is driven by Brownianmotion, an associated \master equation"...

This paper suggests a simple method based on a Chebyshev approximation at Chebyshev nodes to approximate partial differential equations. It consists in determining the value function by using a set of nodes and basis functions. We provide two examples: pricing a European option and determining...

In this paper we consider the optimal stopping problem for general dynamic monetary utility functionals. Sufficient conditions for the Bellman principle and the existence of optimal stopping times are provided. Particular attention is payed to representations which allow for a numerical...

We explain the valuation and correlation hedging of Foreign Exchange Basket Options in a multi-dimensional Black-Scholes model that allows including the smile. The technique presented is a fast analytic approximation to an accurate solution of the valuation problem.

In Monte Carlo simulation, Latin hypercube sampling (LHS) [McKay et al. (1979)] is a well-known variance reduction technique for vectors of independent random variables. The method presented here, Latin hypercube sampling with dependence (LHSD), extends LHS to vectors of dependent random...

This paper presents a new numerical method for pricing American call options when the volatility of the price of the underlying stock is stochastic. By exploiting a log-linear relationship of the optimal exercise boundary with respect to volatility changes, we derive an integral representation...

In a two-period setup we develop a generalization of good-deal bounds that allows to include in the problem the implications of asset pricing models. Our basis is the distance behind Hansen and Jagannathan's measure of model misspecification since a volatility constraint on the stochastic...

New methods for solving general linear parabolic partial differential equations (PDEs) in one space dimension are developed. The methods combine quadratic-spline collocation for the space discretization and classical finite differences, such as Crank-Nicolson, for the time discretization. The...