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Performance of GARCH models in forecasting stock market volatility.

This paper studies the performance of GARCH model and its modifications, 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 G...

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Main Authors: Choo, Wei Chong, Ahmad, Muhammad Idrees, Abdullah, Mat Yusoff
Format: Article
Language:English
English
English
Published: John Wiley and Sons 1999
Subjects:
Finance - Mathematical models
Stock price forecasting - Mathematical models.
Investments - Mathematical models.
Online Access:http://psasir.upm.edu.my/id/eprint/16140/1/Performance%20of%20GARCH%20models%20in%20forecasting%20stock%20market%20volatility.pdf
http://psasir.upm.edu.my/id/eprint/16140/7/Journal%20of%20Forecasting%20-%201999%20-%20Chong%20-%20Performance%20of%20GARCH%20models%20in%20forecasting%20stock%20market%20volatility.pdf
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spelling oai:psasir.upm.edu.my:16140 http://psasir.upm.edu.my/id/eprint/16140/ Performance of GARCH models in forecasting stock market volatility. Choo, Wei Chong Ahmad, Muhammad Idrees Abdullah, Mat Yusoff This paper studies the performance of GARCH model and its modifications, 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 GARCH, unconstrained GARCH, non-negative GARCH, GARCH-M, exponential GARCH and integrated GARCH. The parameters of these models and variance processes are estimated jointly using the maximum likelihood method. The performance of the within-sample estimation is diagnosed using several goodness-of-fit statistics. We observed that, among the models, even though exponential GARCH is not the best model in the goodness-of-fit statistics, it performs best in describing the often-observed skewness in stock market indices and in out-of-sample (one-step-ahead) forecasting. The integrated GARCH, on the other hand, is the poorest model in both respects. John Wiley and Sons 1999 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/16140/1/Performance%20of%20GARCH%20models%20in%20forecasting%20stock%20market%20volatility.pdf text en http://psasir.upm.edu.my/id/eprint/16140/7/Journal%20of%20Forecasting%20-%201999%20-%20Chong%20-%20Performance%20of%20GARCH%20models%20in%20forecasting%20stock%20market%20volatility.pdf Choo, Wei Chong and Ahmad, Muhammad Idrees and Abdullah, Mat Yusoff (1999) Performance of GARCH models in forecasting stock market volatility. Journal of Forecasting, 18 (5). pp. 333-343. ISSN 1099-131X http://ehis.ebscohost.com/eds/pdfviewer/pdfviewer?sid=f49af050-ffd8-45ca-881c-b6037c31e530%40sessionmgr14&vid=1&hid=22 Finance - Mathematical models Stock price forecasting - Mathematical models. Investments - Mathematical models. English
institution UPM IR
collection UPM IR
language English
English
English
topic Finance - Mathematical models
Stock price forecasting - Mathematical models.
Investments - Mathematical models.
spellingShingle Finance - Mathematical models
Stock price forecasting - Mathematical models.
Investments - Mathematical models.
Choo, Wei Chong
Ahmad, Muhammad Idrees
Abdullah, Mat Yusoff
Performance of GARCH models in forecasting stock market volatility.
description This paper studies the performance of GARCH model and its modifications, 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 GARCH, unconstrained GARCH, non-negative GARCH, GARCH-M, exponential GARCH and integrated GARCH. The parameters of these models and variance processes are estimated jointly using the maximum likelihood method. The performance of the within-sample estimation is diagnosed using several goodness-of-fit statistics. We observed that, among the models, even though exponential GARCH is not the best model in the goodness-of-fit statistics, it performs best in describing the often-observed skewness in stock market indices and in out-of-sample (one-step-ahead) forecasting. The integrated GARCH, on the other hand, is the poorest model in both respects.
format Article
author Choo, Wei Chong
Ahmad, Muhammad Idrees
Abdullah, Mat Yusoff
author_facet Choo, Wei Chong
Ahmad, Muhammad Idrees
Abdullah, Mat Yusoff
author_sort Choo, Wei Chong
title Performance of GARCH models in forecasting stock market volatility.
title_short Performance of GARCH models in forecasting stock market volatility.
title_full Performance of GARCH models in forecasting stock market volatility.
title_fullStr Performance of GARCH models in forecasting stock market volatility.
title_full_unstemmed Performance of GARCH models in forecasting stock market volatility.
title_sort performance of garch models in forecasting stock market volatility.
publisher John Wiley and Sons
publishDate 1999
url http://psasir.upm.edu.my/id/eprint/16140/1/Performance%20of%20GARCH%20models%20in%20forecasting%20stock%20market%20volatility.pdf
http://psasir.upm.edu.my/id/eprint/16140/7/Journal%20of%20Forecasting%20-%201999%20-%20Chong%20-%20Performance%20of%20GARCH%20models%20in%20forecasting%20stock%20market%20volatility.pdf
_version_ 1819293996689653760
score 13.4562235

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