Implied Volatility Surface
Electricity Prices
Random Samples from Gaussian Copula
American CatEPut Price Surface
American Spread Option Exercise Surface
Results of MSc Thesis
 
Papers
  • A Levy Based Framework for Commodity Derivative Valuation via FFT (with Sebastian Jaimungal) (November 17, 2008) [SSRN] [BIB]
    Energy commodities, such as oil, gas and electricity, lack the liquidity of equity markets, have large costs associated with storage, exhibit high volatilities and can have significant spikes in prices. Furthermore, and possibly most importantly, commodities tend to revert to long run equilibrium prices. Many complex commodity contingent claims exist in the markets, such as swing and interruptible options; however, the current method of valuation relies heavily on Monte Carlo simulations and tree based methods. In this article, we develop a new framework for dealing with mean-reverting jump-diffusion (and pure jump) models by working in Fourier space. The method is based on the Fourier space time stepping algorithm of Jackson, Jaimungal, and Surkov (2008), but is tailored for mean-reverting models. We demonstrate the utility of the method by applying it to the valuation of European, American and barrier options on a single underlier, European and Bermudan spread options on two-dimensional underliers, and swing options.

  • Stepping Through Fourier Space (with Sebastian Jaimungal)  (October 9, 2008) [SSRN]
    Diverse finite-difference schemes for solving pricing problems with Levy underliers have been used in the literature. Invariably, the integral and diffusive terms are treated asymmetrically, large jumps are truncated, the methods are difficult to extend to higher dimensions and cannot easily incorporate regime switching or stochastic volatility. We present a new efficient approach which switches between Fourier and real space as time propagates backwards. We dub this method Fourier Space Time-Stepping (FST). The FST method applies to regime switching Levy models and is applicable to a wide class of path-dependent options (such as Bermudan, barrier, shout and catastrophe linked options) and options on multiple assets.

  • Parallel Option Pricing with Fourier Space Time-stepping Method on Graphics Processing Units  (October 8, 2007) [SSRN] [BIB]
    With the evolution of Graphics Processing Units (GPUs) into powerful and cost-efficient computing architectures, their range of application has expanded tremendously, especially in the area of computational finance. Current research in the area, however, is limited in terms of options priced and complexity of stock price models. This paper presents algorithms, based on the Fourier Space Time-stepping (FST) method, for pricing single and multi-asset European and American options with Levy underliers on a GPU. Furthermore, the single-asset pricing algorithm is parallelized to attain greater efficiency.

  • Option Pricing with Regime Switching Levy Processes Using Fourier Space Time-stepping (with Ken Jackson and Sebastian Jaimungal)  (April 30, 2007) [PDF] [BIB]
    Although jump-diffusion and Levy models have been widely used in industry, the pricing partial-integro differential equations poses various difficulties for valuation. Diverse finite-difference schemes for solving the problem have been introduced in the literature. Invariably, the integral and diffusive terms are treated asymmetrically, large jumps are truncated and the methods are difficult to extend to higher dimensions. We present a new efficient transform approach for regime-switching Levy models which is applicable to a wide class of path-dependent options (such as Bermudan, barrier, and shout options) and options on multiple assets.

  • Fourier Space Time-stepping for Option Pricing with Levy Models (with Ken Jackson and Sebastian Jaimungal)  (March 14, 2007) [SSRN]
    It is well known that the Black-Scholes-Merton model suffers from several deficiencies. Jump-diffusion and Levy models have been widely used to partially alleviate some of the biases inherent in this classical model. Unfortunately, the resulting pricing problem requires solving a more difficult partial-integro differential equation (PIDE) and although several approaches for solving the PIDE have been suggested in the literature, none are entirely satisfactory. All treat the integral and diffusive terms asymmetrically and are difficult to extend to higher dimensions. We present a new, efficient algorithm, based on transform methods, which symmetrically treats the diffusive and integrals terms, is applicable to a wide class of path-dependent options (such as Bermudan, barrier, and shout options) and options on multiple assets, and naturally extends to regime-switching Levy models. We present a concise study of the precision and convergence properties of our algorithm for several classes of options and Levy models and demonstrate that the algorithm is second-order in space and first-order in time for path-dependent options.

  • Valuation of Mortgage-Backed Securities in a Distributed Environment (February 18, 2004) [PDF]
    Valuation of Mortgage-Backed Securities, regarded as integration in high-dimensional space, can be readily performed using the Monte Carlo method. The Quasi-Monte Carlo method, by utilizing low-discrepancy sequences, has been able to achieve better convergence rates at computational finance problems despite analysis suggesting that the improved convergence comes into effect only at sample sizes growing exponentially with dimension. This may be attributed to the fact that the integrands are of low effective dimension and quasi-random sequences' good equidistribution properties in low dimensions allow for the faster convergence rates to be attained at feasible sample sizes. The Brownian bridge discretization is traditionally used to reduce the effective dimension although an alternate choice of discretization can produce superior results. This paper examines the standard Brownian bridge representation and offers a reparametrization to further reduce dimension. The performance is compared both in terms of improvement in convergence and reduced effective dimensionality as computed using ANOVA decomposition. Also, porting of the valuation algorithm to a distributed environment using Microsoft .NET is presented.