Fractional Brownian markets with time-varying volatility and high-frequency data
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2017
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| _version_ | 1866914814334337024 |
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| author | Lahiri, Ananya Sen, Rituparna |
| author_facet | Lahiri, Ananya Sen, Rituparna |
| contents | Diffusion processes driven by Fractional Brownian motion (FBM) have often been considered in modeling stock price dynamics in order to capture the long range dependence of stock price observed in reality. Option prices for such models had been obtained by Necula (2002) under constant drift and volatility. We obtain option prices under time varying volatility model. The expression depends on volatility and the Hurst parameter in a complicated manner. We derive a central limit theorem for the quadratic variation as an estimator for volatility for both the cases, constant as well as time varying volatility. That will help us to find estimators of the option prices and to find their asymptotic distributions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1707_06416 |
| institution | arXiv |
| publishDate | 2017 |
| record_format | arxiv |
| spellingShingle | Fractional Brownian markets with time-varying volatility and high-frequency data Lahiri, Ananya Sen, Rituparna Statistics Theory Diffusion processes driven by Fractional Brownian motion (FBM) have often been considered in modeling stock price dynamics in order to capture the long range dependence of stock price observed in reality. Option prices for such models had been obtained by Necula (2002) under constant drift and volatility. We obtain option prices under time varying volatility model. The expression depends on volatility and the Hurst parameter in a complicated manner. We derive a central limit theorem for the quadratic variation as an estimator for volatility for both the cases, constant as well as time varying volatility. That will help us to find estimators of the option prices and to find their asymptotic distributions. |
| title | Fractional Brownian markets with time-varying volatility and high-frequency data |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/1707.06416 |