• Home
  1. Home
  2. Approximation and Calibration of Short-Term implied Volatilities under Jump-Diffusion Stochastic Volatility
Report
OA Policy
English

Approximation and Calibration of Short-Term implied Volatilities under Jump-Diffusion Stochastic Volatility

Contributors

Medvedev, Alexey; Scaillet, Olivier

Collection

  • Cahiers de recherche; 2006.01

Publication date

2006

Abstract

We derive a closed-form asymptotic expansion formula for option implied volatility under a two-factor jump-diffusion stochastic volatility model when time-to-maturity is small. Based on numerical experiments we describe the range of time-to-maturity and moneyness for which the approximation is accurate. We further propose a simple calibration procedure of an arbitrary parametric model to short-term near-the-money implied volatilities. An important advantage of our approximation is that it is free of the unobserved spot volatility. Therefore, the model can be calibrated on option data pooled across different calendar dates in order to extract information from the dynamics of the implied volatility smile. An example of calibration to a sample of S&P500 option prices is provided. We find that jumps are significant. The evidence also supports an affine specification for the jump intensity and Constant-Elasticity-of-Variance for the dynamics of the return volatility.

Keywords

  • Option pricing
  • Stochastic volatility
  • Asymptotic approximation
  • Jump-diffusion

UNIGE affiliation entities

Citation (ISO format)

MEDVEDEV, Alexey, SCAILLET, Olivier. Approximation and Calibration of Short-Term implied Volatilities under Jump-Diffusion Stochastic Volatility. 2006

Main files (1)

Report

Identifiers

  • PID : unige:5749
648views
1305downloads

Technical informations

Creation

15/04/2010 12:19:44

First validation

15/04/2010 12:19:44

Update

14/03/2023 15:26:26

Status update

14/03/2023 15:26:26

Last indexation

29/10/2024 14:22:08
All rights reserved by Archive ouverte UNIGE and the University of Geneva
OpenAIRE Indexed & Validated