✦ LIBER ✦

Forecasting stock market volatility using (non-linear) Garch models

✍ Scribed by Philip Hans Franses; Dick Van Dijk

Publisher: John Wiley and Sons
Year: 1996
Tongue: English
Weight: 444 KB
Volume: 15
Category: Article
ISSN: 0277-6693
DOI: 10.1002/(sici)1099-131x(199604)15:3<229::aid-for620>3.0.co;2-3

No coin nor oath required. For personal study only.

✦ Synopsis

In this paper we study the performance of the GARCH model and two of its non-linear modifications to forecast weekly stock market volatility. The models are the Quadratic GARCH (Engle and Ng, 1993) and the Glosten, Jagannathan and Runkle (1992) models which have been proposed to describe, for example, the often observed negative skewness in stock market indices. We find that the QGARCH model is best when the estimation sample does not contain extreme observations such as the 1987 stock market crash and that the GJR model cannot be recommended for forecasting.

📜 SIMILAR VOLUMES

Forecasting volatility of emerging stock

Forecasting volatility of emerging stock markets: linear versus non-linear GARCH models

✍ Suleyman Gokcan 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 99 KB

Performance of GARCH models in forecasti

Performance of GARCH models in forecasting stock market volatility

✍ Choo Wei Chong; Muhammad Idrees Ahmad; Mat Yusoff Abdullah 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 127 KB 👁 1 views

This paper studies the performance of GARCH model and its modi®cations, using the rate of returns from the daily stock market indices of the Kuala Lumpur Stock Exchange (KLSE) including Composite Index, Tins Index, Plantations Index, Properties Index, and Finance Index. The models are stationary GAR

A non-linear filtering approach to stoch

A non-linear filtering approach to stochastic volatility models with an application to daily stock returns

✍ Toshiaki Watanabe 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 199 KB 👁 1 views

This paper develops a new method for the analysis of stochastic volatility (SV) models. Since volatility is a latent variable in SV models, it is dicult to evaluate the exact likelihood. In this paper, a non-linear ®lter which yields the exact likelihood of SV models is employed. Solving a series of

Seasonal forecasting of South African ra

Seasonal forecasting of South African rainfall using a non-linear discriminant analysis model

✍ Mason, S. J. 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 481 KB 👁 1 views

Statistical models have been used to provide operational seasonal forecasts of rainfall over southern Africa since 1992. The Climatology Research Group has been using a quadratic discriminant analysis model since November 1994. The model relates rainfall over different areas of South Africa to princ