EconPapers    
Economics at your fingertips  
 

Volatility and GMM: Monte Carlo studies and empirical estimations

Hartmut Nagel and Rainer Schöbel

No 69, Tübinger Diskussionsbeiträge from University of Tübingen, School of Business and Economics

Abstract: In this paper we examine small sample properties of a generalized method of moments (GMM) estimation using Monte Carlo simulations. We assume that the generated time series describe the stochastic variance rate of a stock index. We use a mean reverting square-root prooess to simulate the dynamics of this instantaneous variance rate. The generated time series consist of 63, 250, and 1000 data points, respectively. They are used to estimate the Parameters of the assumed variance rate process by applying GMM. The results obtained are described and compared to our estimates from empirical volatility data. We use the German volatility index VDAX, historical volatilities of the German stock index DAX over 10, 22 and 33 trading days as well as daily volume data of the German stock market.

Date: 1996
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/104963/1/tdb069.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:tuedps:69

Access Statistics for this paper

More papers in Tübinger Diskussionsbeiträge from University of Tübingen, School of Business and Economics Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics (econstor@zbw-workspace.eu).

 
Page updated 2025-03-20
Handle: RePEc:zbw:tuedps:69