Forecasting Volatility in the Singapore Stock Market

Data from the Stock Exchange of Singapore (SES) are used to compare 3 methods of forecasting the volatility of derivative securities: 1. the naive method based on historical sample variance, 2. the exponentially weighted moving average (EWMA) method, and 3. the generalized autoregressive conditional...

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Main Authors: TSE, Yiu Kuen, Tung, S. H.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 1992
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Online Access:https://ink.library.smu.edu.sg/soe_research/214
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Institution: Singapore Management University
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spelling sg-smu-ink.soe_research-12132010-09-23T05:48:03Z Forecasting Volatility in the Singapore Stock Market TSE, Yiu Kuen Tung, S. H. Data from the Stock Exchange of Singapore (SES) are used to compare 3 methods of forecasting the volatility of derivative securities: 1. the naive method based on historical sample variance, 2. the exponentially weighted moving average (EWMA) method, and 3. the generalized autoregressive conditional heteroskedasticity (GARCH) model. The data used are the daily closing prices of 5 value-weighted SES indexes covering the period from March 19, 1975, to October 25, 1988. Study findings indicate that the EWMA mehtod is superior to the naive method and the GARCH model. The GARCH model, while the most sophisticated, is the poorest method, which can be partially attributed to the method's stringent data requirements. Therefore, the EWMA is particularly appealing in actual applications in the pricing of derivative securities, given its superior forecasts and simplicity. 1992-01-01T08:00:00Z text https://ink.library.smu.edu.sg/soe_research/214 Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Asian Studies Econometrics Finance
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Asian Studies
Econometrics
Finance
spellingShingle Asian Studies
Econometrics
Finance
TSE, Yiu Kuen
Tung, S. H.
Forecasting Volatility in the Singapore Stock Market
description Data from the Stock Exchange of Singapore (SES) are used to compare 3 methods of forecasting the volatility of derivative securities: 1. the naive method based on historical sample variance, 2. the exponentially weighted moving average (EWMA) method, and 3. the generalized autoregressive conditional heteroskedasticity (GARCH) model. The data used are the daily closing prices of 5 value-weighted SES indexes covering the period from March 19, 1975, to October 25, 1988. Study findings indicate that the EWMA mehtod is superior to the naive method and the GARCH model. The GARCH model, while the most sophisticated, is the poorest method, which can be partially attributed to the method's stringent data requirements. Therefore, the EWMA is particularly appealing in actual applications in the pricing of derivative securities, given its superior forecasts and simplicity.
format text
author TSE, Yiu Kuen
Tung, S. H.
author_facet TSE, Yiu Kuen
Tung, S. H.
author_sort TSE, Yiu Kuen
title Forecasting Volatility in the Singapore Stock Market
title_short Forecasting Volatility in the Singapore Stock Market
title_full Forecasting Volatility in the Singapore Stock Market
title_fullStr Forecasting Volatility in the Singapore Stock Market
title_full_unstemmed Forecasting Volatility in the Singapore Stock Market
title_sort forecasting volatility in the singapore stock market
publisher Institutional Knowledge at Singapore Management University
publishDate 1992
url https://ink.library.smu.edu.sg/soe_research/214
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