Modeling Stochastic Volatility with Application to Stock Returns:

A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was consiste...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Krichene, Noureddine (VerfasserIn)
Format: Elektronisch E-Book
Sprache:English
Veröffentlicht: Washington, D.C International Monetary Fund 2003
Schriftenreihe:IMF Working Papers Working Paper No. 03/125
Online-Zugang:UBW01
UEI01
LCO01
SBR01
UER01
SBG01
UBG01
FAN01
UBT01
FKE01
UBY01
UBA01
FLA01
UBM01
UPA01
UBR01
FHA01
FNU01
BSB01
TUM01
Volltext
Zusammenfassung:A stochastic volatility model where volatility was driven solely by a latent variable called news was estimated for three stock indices. A Markov chain Monte Carlo algorithm was used for estimating Bayesian parameters and filtering volatilities. Volatility persistence being close to one was consistent with both volatility clustering and mean reversion. Filtering showed highly volatile markets, reflecting frequent pertinent news. Diagnostics showed no model failure, although specification improvements were always possible. The model corroborated stylized findings in volatility modeling and has potential value for market participants in asset pricing and risk management, as well as for policymakers in the design of macroeconomic policies conducive to less volatile financial markets
Beschreibung:1 Online-Ressource (27 p)
ISBN:1451854846
9781451854848

Es ist kein Print-Exemplar vorhanden.

Fernleihe Bestellen Achtung: Nicht im THWS-Bestand! Volltext öffnen