Dual Valuation and Hedging of Bermudan Options

Abstract. Some years ago, a different characterization of the value of a Bermudan option was discovered which can be thought of as the viewpoint of the seller of the option, in contrast to the conventional characterization which took the viewpoint of the buyer. Since then, there has been a lot of interest in finding numerical methods which exploit this dual characterization. This paper presents a pure dual algorithm for pricing and hedging Bermudan options

Dual Valuation and Hedging of Bermudan Options

Abstract. Some years ago now, a different characterisation of the value of a Bermudan option was discovered, which can be thought of as the viewpoint of the seller of the option, in contrast to the conventional characterisation which took the viewpoint of the buyer. Since then, there has been a lot of interest in finding numerical methods which exploit this dual characterisation. This paper presents a pure dual algorithm for pricing and hedging Bermudan options

An Irregular Grid Approach for Pricing High-Dimensional American Options

We propose and test a new method for pricing American options in a high-dimensional setting.The method is centred around the approximation of the associated complementarity problem on an irregular grid.We approximate the partial differential operator on this grid by appealing to the SDE representation of the underlying process and computing the root of the transition probability matrix of an approximating Markov chain.Experimental results in five dimensions are presented for four different payoff functions.option pricing;inequality;markov chains

Pricing and hedging American-style options with deep learning

In this paper we introduce a deep learning method for pricing and hedging American-style options. It first computes a candidate optimal stopping policy. From there it derives a lower bound for the price. Then it calculates an upper bound, a point estimate and confidence intervals. Finally, it constructs an approximate dynamic hedging strategy. We test the approach on different specifications of a Bermudan max-call option. In all cases it produces highly accurate prices and dynamic hedging strategies with small replication errors

An Irregular Grid Approach for Pricing High-Dimensional American Options

We propose and test a new method for pricing American options in a high-dimensional setting.The method is centred around the approximation of the associated complementarity problem on an irregular grid.We approximate the partial differential operator on this grid by appealing to the SDE representation of the underlying process and computing the root of the transition probability matrix of an approximating Markov chain.Experimental results in five dimensions are presented for four different payoff functions

A backward dual representation for the quantile hedging of Bermudan options

Within a Markovian complete financial market, we consider the problem of hedging a Bermudan option with a given probability. Using stochastic target and duality arguments, we derive a backward numerical scheme for the Fenchel transform of the pricing function. This algorithm is similar to the usual American backward induction, except that it requires two additional Fenchel transformations at each exercise date. We provide numerical illustrations

Sensitivities for Bermudan Options by Regression Methods

In this article we propose several pathwise and finite difference based methods for calculating sensitivities of Bermudan options using regression methods and Monte Carlo simulation. These methods rely on conditional probabilistic representations which allow, in combination with a regression approach, for efficient simultaneous computation of sensitivities at many initial positions. Assuming that the price of a Bermudan option can be evaluated sufficiently accurate, we develop a method for constructing deltas based on least squares. We finally propose a testing procedure for assessing the performance of the developed methods.American and Bermudan options, Optimal stopping times, Monte Carlo simulation, Deltas, Conditional probabilistic representations, Regression methods