Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash 99 tok/s
Gemini 2.5 Pro 43 tok/s Pro
GPT-5 Medium 28 tok/s
GPT-5 High 35 tok/s Pro
GPT-4o 94 tok/s
GPT OSS 120B 476 tok/s Pro
Kimi K2 190 tok/s Pro
2000 character limit reached

Calibration of Local Volatility Model with Stochastic Interest Rates by Efficient Numerical PDE Method (1803.03941v1)

Published 11 Mar 2018 in q-fin.MF

Abstract: Long maturity options or a wide class of hybrid products are evaluated using a local volatility type modelling for the asset price S(t) with a stochastic interest rate r(t). The calibration of the local volatility function is usually time-consuming because of the multi-dimensional nature of the problem. In this paper, we develop a calibration technique based on a partial differential equation (PDE) approach which allows an efficient implementation. The essential idea is based on solving the derived forward equation satisfied by P(t; S; r)Z(t; S; r), where P(t; S; r) represents the risk neutral probability density of (S(t); r(t)) and Z(t; S; r) the projection of the stochastic discounting factor in the state variables (S(t); r(t)). The solution provides effective and sufficient information for the calibration and pricing. The PDE solver is constructed by using ADI (Alternative Direction Implicit) method based on an extension of the Peaceman-Rachford scheme. Furthermore, an efficient algorithm to compute all the corrective terms in the local volatility function due to the stochastic interest rates is proposed by using the PDE solutions and grid points. Different numerical experiments are examined and compared to demonstrate the results of our theoretical analysis.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Ai Generate Text Spark Streamline Icon: https://streamlinehq.com

Paper Prompts

Sign up for free to create and run prompts on this paper using GPT-5.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.

Authors (2)