{"title":"Transform analysis and asset pricing for diffusion processes: a recursive approach","authors":"M. Goovaerts, R. Laeven, Zhaoning Shang","doi":"10.21314/JCF.2012.245","DOIUrl":null,"url":null,"abstract":"Diffusion processes play a major role in continuous-time modeling in economics, particularly in continuous-time finance. In most cases, however, the transition density function of a diffusion process is not available in closed form. Using Feynman-Kac integration, we construct a recursive scheme for the Laplace transform (in time) of the transition density function. This provides a semianalytic and highly accurate solution to a wide range of asset pricing problems. Generalizations of our technique to functionals of non-Gaussian processes are also briefly discussed.","PeriodicalId":51731,"journal":{"name":"Journal of Computational Finance","volume":"16 1","pages":"47-81"},"PeriodicalIF":0.8000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Finance","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/JCF.2012.245","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 2
Abstract
Diffusion processes play a major role in continuous-time modeling in economics, particularly in continuous-time finance. In most cases, however, the transition density function of a diffusion process is not available in closed form. Using Feynman-Kac integration, we construct a recursive scheme for the Laplace transform (in time) of the transition density function. This provides a semianalytic and highly accurate solution to a wide range of asset pricing problems. Generalizations of our technique to functionals of non-Gaussian processes are also briefly discussed.
期刊介绍:
The Journal of Computational Finance is an international peer-reviewed journal dedicated to advancing knowledge in the area of financial mathematics. The journal is focused on the measurement, management and analysis of financial risk, and provides detailed insight into numerical and computational techniques in the pricing, hedging and risk management of financial instruments. The journal welcomes papers dealing with innovative computational techniques in the following areas: Numerical solutions of pricing equations: finite differences, finite elements, and spectral techniques in one and multiple dimensions. Simulation approaches in pricing and risk management: advances in Monte Carlo and quasi-Monte Carlo methodologies; new strategies for market factors simulation. Optimization techniques in hedging and risk management. Fundamental numerical analysis relevant to finance: effect of boundary treatments on accuracy; new discretization of time-series analysis. Developments in free-boundary problems in finance: alternative ways and numerical implications in American option pricing.