Gradient Estimation and Mountain Range Options

24 Pages Posted: 28 Dec 2018

See all articles by Andrew O. Hall

Andrew O. Hall

Department of Mathematical Sciences, USMA

Michael Fu

University of Maryland - College Park

Date Written: December 11, 2018

Abstract

This application of gradient estimation drawn from financial engineering and ex- plores several exotic derivatives that are collectively known Mountain Range options, employing Monte Carlo simulation to price these options and developing gradient es- timates to study the sensitivities to underlying parameters, known as “the Greeks”. We find that IPA and LR/SF methods are efficient methods of gradient estimation for Mountain Range products at a considerably reduced computation cost compared with the commonly used finite difference methods.

Keywords: Monte Carlo Simulation,Option Pricing, Gradient Estimation, Mountain Range Options

JEL Classification: G12, C63

Suggested Citation

Hall, Andrew O. and Fu, Michael, Gradient Estimation and Mountain Range Options (December 11, 2018). Available at SSRN: https://ssrn.com/abstract=3299798 or http://dx.doi.org/10.2139/ssrn.3299798

Andrew O. Hall (Contact Author)

Department of Mathematical Sciences, USMA ( email )

600 Thayer Rd
West Point, NY 10996
United States

Michael Fu

University of Maryland - College Park ( email )

College Park, MD 20742
United States

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