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: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
1992
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/soe_research/214 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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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