Inverting multivariate analytic characteristic functions with financial applications

This dissertation is devoted to multivariate analytic characteristic functions inversion and applications in option pricing, option sensitivities estimation, and some electronic engineering problems. We will show that under certain analytic conditions for characteristic functions, the underlying pdfs and cdfs have exponential tails. The inversion from multivariate characteristic functions to the corresponding pdfs and cdfs can be approximated by the trapezoidal rule conveniently with great accuracy. Monte Carlo methods can be applied for option sensitivity analysis. Under multi-dimensional models, acceptance-rejection method is desirable. Simulating from a distribution without explicit pdf or CDF is then transformed to sampling from an easy-to-simulate distribution. Detailed algorithms are provided and comparisons against classical methods in terms of accuracy and efficiency are included.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Industrial Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Hu, Runqi

Contributors dc:contributor

• Feng, Liming
• Feng, Runhuan
• Sirignano, Justin
• Chronopoulou, Alexandra

• Multivariate analytic characteristic function
• inversion

Statement dc:rights

• Copyright 2019 Runqi Hu

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/105056

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/105056