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Volatility estimation of underlying assets for valuing low liquidity call options
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Scopus
University of the Thai Chamber of Commerce
Date Issued
2015
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University of the Thai Chamber of Commerce. Research Support Office
Abstract
This study explored optimal models for estimating the implied volatility of the SET50 index on the Thailand Futures Exchange (TFEX). Our data covered a 12yearperiod from Jan 1, 2000 to Dec 31, 2011. The volatilityestimating models used were GARCH (1,1) and historical models. Our results showed that oneday,lagged, historical volatility is equivalent to the conditional variance form of the GARCH (1,1) model. We used estimated volatility from both the GARCH (1,1) and historical models for pricing call options with the BlackScholes model. We also compared estimated call option values to actual call option market prices. Our results showed that 6 month historical volatility outperforms for estimating call option values compared to the conditional variance from the GARCH (1,1) model. Because call option trading liquidity on the TFEXis low, therefore, call option values estimated using constant implied volatility from longperiod historical volatility ares superior to call option value estimation using timevarying volatility. In order to boost financial risk management by using derivatives on the TFEX, exchange regulators should focus on an increase in derivatives trading liquidity.
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University of the Thai Chamber of Commerce
Bibliographic Citation
R. Manowattanakul, T. Boonvorachote (2015) Volatility estimation of underlying assets for valuing low liquidity call options. Kasetsart Journal Social Sciences Vol.36 No.2, 244-257.
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