|
EconStor >
Frankfurt School of Finance and Management, Frankfurt a. M. >
CPQF Working Paper Series, Frankfurt School of Finance and Management >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10419/40187
|
| | |
| Title: | | Accelerating the calibration of stochastic volatility models  |
| Authors: | | Kilin, Fiodar |
| Issue Date: | | 2007 |
| Series/Report no.: | | CPQF Working Paper Series 6 |
| Abstract: | | This paper compares the performance of three methods for pricing vanilla options in models with known characteristic function: (1) Direct integration, (2) Fast Fourier Transform (FFT), (3) Fractional FFT. The most important application of this comparison is the choice of the fastest method for the calibration of stochastic volatility models, e.g. Heston, Bates, Barndorff-Nielsen-Shephard models or Levy models with stochastic time. We show that using additional cache technique makes the calibration with the direct integration method at least seven times faster than the calibration with the fractional FFT method. |
| Subjects: | | Stochastic Volatility Models Calibration Numerical Integration Fast Fourier Transform |
| JEL: | | G13 |
| Document Type: | | Working Paper |
| Appears in Collections: | | CPQF Working Paper Series, Frankfurt School of Finance and Management
|
| Files in This Item:
| |
|
| No. of Downloads:
| |
| last Month |
last 3 Month |
total |
|
|
|
|
|
| |
| | |
Download bibliographical data as:
BibTeX
|
| |
Share on:http://hdl.handle.net/10419/40187
|
Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.
|