The stochastic alpha beta rho (SABR) model introduced by Hagan et al. (2002) is widely used in both fixed income and the foreign exchange (FX) markets. Continuously monitored barrier option contracts are among the most popular derivative contracts in the FX markets. In this paper, we develop...

This is a preprint of the chapter "Supercomputers" in the forthcoming book "High-Performance Computing in Finance: Problems, Methods, and Solutions", M.A.H. Dempster, J. Kanniainen, J. Keane, and E. Vynckier (Eds), Chapman and Hall/CRC, London, 2017. The chapter discusses the use of...

Crude oil derivatives form an important part of the global derivatives market. In this paper, we focus on Asian options which are favoured by risk managers being effective and cost-saving hedging instruments. The paper has both empirical and theoretical contributions: we conduct an empirical...

The credit valuation adjustment (CVA) of OTC derivatives is an important part of the Basel III credit risk capital requirements and current accounting rules. Its calculation is not an easy task - not only it is necessary to model the future value of the derivative, but also the probability of...

In this paper we consider the problem of hedging an arithmetic Asian option with discrete monitoring in an exponential Lévy model by deriving backward recursive integrals for the price sensitivities of the option. The procedure is applied to the analysis of the performance of the delta and...

This paper proposes an integrated pricing framework for convertible bonds, which comprises firm value evolving as an exponential jump diffusion, correlated stochastic interest rates movements and an efficient numerical pricing scheme. By construction, the proposed stochastic model fits in the...

In this article, the Universal Approximation Theorem of Artificial Neural Networks (ANNs) is applied to the SABR stochastic volatility model in order to construct highly efficient representations. Initially, the SABR approximation of Hagan et al. [2002] is considered, then a more accurate...

This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We...

We present effective momentum strategies over the liquid equity futures market in India. We evaluate and determine the persistence of the returns at various look-backs ranging from quarterly and weekly to more granular look-backs. We look at a universe of the liquid equity instruments traded...

We derive closed-form expressions to price European calls and puts assuming the cash flows of the underlying asset or project are normally distributed. This approach has important advantages in the context of real options applied to infrastructure projects when compared to the Black-Scholes...