Pricing Nikkei 225 Options Using Realized Volatility
AbstractThis article analyzes whether daily realized volatility, which is the sum of squared intraday returns over a day, is useful for option pricing. Different realized volatilities are calculated with or without taking account of microstructure noise and with or without using overnight and lunch-time returns. ARFIMA, ARFIMAX, HAR, HARX models are employed to specify the dynamics of realized volatility. ARFIMA and HAR models can capture the long-memory property and ARFIMAX and HARX models can also capture the asymmetry in volatility depending on the sign of previous day's return. Option prices are derived under the assumption of risk-neutrality. For comparison, GARCH, EGARCH and FIEGARCH models are estimated using daily returns, where option prices are derived by assuming the risk-neutrality and by using the Duan (1995) method in which the assumption of risk-neutrality is relaxed. Main results using the Nikkei 225 stock index and its put options prices are: (1) ARFIMAX model with daily realized volatility performs best, (2) the Hansen and Lunde ( 2005a) adjustment without using overnight and lunch-time returns can improve the performance, (3) if the Hansen and Lunde (2005a), which also plays a role to remove the bias caused by the microstructure noise by setting the sample mean of realized volatility equal to the sample variance of daily returns, is used, the other methods for taking account of microstructure noise do not necessarily improve the performance and (4) the Duan (1995) method does not improve the performance compared with assuming the risk neutrality.
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Bibliographic InfoPaper provided by Institute for Monetary and Economic Studies, Bank of Japan in its series IMES Discussion Paper Series with number 11-E-18.
Date of creation: Aug 2011
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microstructure noise; Nikkei 225 stock index; non-trading hours; option pricing; realized volatility;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-08-29 (All new papers)
- NEP-FMK-2011-08-29 (Financial Markets)
- NEP-MST-2011-08-29 (Market Microstructure)
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