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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1992
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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 |
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Asian Studies Econometrics Finance TSE, Yiu Kuen Tung, S. H. Forecasting Volatility in the Singapore Stock Market |
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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. |
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TSE, Yiu Kuen Tung, S. H. |
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TSE, Yiu Kuen Tung, S. H. |
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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 |
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Forecasting Volatility in the Singapore Stock Market |
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forecasting volatility in the singapore stock market |
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Institutional Knowledge at Singapore Management University |
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1992 |
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https://ink.library.smu.edu.sg/soe_research/214 |
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