The role of option-implied information in improving a portfolio selection
Estimation of parameters such as mean and volatility from historical prices are used as inputs to a portfolio model. Researchers found that estimation parameters based on option prices have made a significant improvement in the performance of a portfolio. To date, the usefulness of an option-implied...
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| Main Authors: | , , |
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| Format: | Monograph |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/79756/1/Full%20report%20FRGS%20MIMI%20HAFIZAH%20ABDULLAH.pdf http://irep.iium.edu.my/79756/ |
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| Institution: | Universiti Islam Antarabangsa Malaysia |
| Language: | English |
| Summary: | Estimation of parameters such as mean and volatility from historical prices are used as inputs to a portfolio model. Researchers found that estimation parameters based on option prices have made a significant improvement in the performance of a portfolio. To date, the usefulness of an option-implied distribution in a portfolio selection model is still an open question. This research aims to shed some light on this conundrum based on the Dow Jones Industrial Average (DJIA) index data. Firstly, the work is to extract risk-neutral density (RND) of the underlying asset from option prices by differentiating the option prices twice. However, the interpolation and extrapolation techniques are needed in order to provide continuum option prices as required in RND assumption. Secondly, this research converts the RND into RWD. The RND is calibrated using parametric and non-parametric calibrations in order to obtain RWD. The option-implied moments which are calculated based on RND and RWD are used as inputs for a portfolio model. Thirdly, this research compares the performances of a naïve portfolio with that of option-implied distribution portfolio. Empirical evidence shows that the portfolio based on option-implied distribution outperforms the naive portfolio in which it gives lower volatility and higher Sharpe ratio. |
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