Estimation of a Stochastic Volatility and Jumps Model Using Generalized Method of Moments with Ordinary Moment Conditions

Date

2024-4-16

Author

Yakut, Şeref Kutay

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

227
views

75
downloads

Cite This

One of the first works estimating jump risk premium in financial markets is the seminal work of Jun Pan published in 2002. In this work Pan uses the generalized method of moments (GMM) to estimate the parameters of a stochastic volatility price model with jumps from index and option price data. In the implementation of GMM, Pan uses a set of optimal moment conditions. In this thesis, we simulate the stochastic model used in Pan's work and apply the GMM estimation algorithm using ordinary moment conditions on simulated data. The estimation results suggest that the ordinary moment conditions are not very sensitive to model parameters and as a result the estimation algorithm quickly converges to a point around the initial parameter estimate. We applied the same algorithm to a stock price and a call option quoted on Borsa İstanbul and observed a similar performance.

Subject Keywords

Jump Risk Premium, Option Prices, Stochastic Differential Equations, Borsa İstanbul

URI

https://hdl.handle.net/11511/109475

Collections

Graduate School of Applied Mathematics, Thesis