Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models
We consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps. First, using the local average of the range-based variance, we propose a crude estimator of the spot volatility. Second, we use usual nonpar...
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/5048925 |
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| _version_ | 1832566017984823296 |
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| author | Jingwei Cai |
| author_facet | Jingwei Cai |
| author_sort | Jingwei Cai |
| collection | DOAJ |
| description | We consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps. First, using the local average of the range-based variance, we propose a crude estimator of the spot volatility. Second, we use usual nonparametric kernel smoothing to reconstruct the volatility function from the crude estimator. By inference, we find such a double smoothing operation can effectively reduce the estimation error. |
| format | Article |
| id | doaj-art-b5c56d16fa5a413191abd32614995e21 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-b5c56d16fa5a413191abd32614995e212025-02-03T01:05:22ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/50489255048925Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion ModelsJingwei Cai0School of Science, Jinling Institute of Technology, Nanjing 211169, ChinaWe consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps. First, using the local average of the range-based variance, we propose a crude estimator of the spot volatility. Second, we use usual nonparametric kernel smoothing to reconstruct the volatility function from the crude estimator. By inference, we find such a double smoothing operation can effectively reduce the estimation error.http://dx.doi.org/10.1155/2020/5048925 |
| spellingShingle | Jingwei Cai Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models Complexity |
| title | Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models |
| title_full | Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models |
| title_fullStr | Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models |
| title_full_unstemmed | Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models |
| title_short | Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models |
| title_sort | nonparametric range based double smoothing spot volatility estimation for diffusion models |
| url | http://dx.doi.org/10.1155/2020/5048925 |
| work_keys_str_mv | AT jingweicai nonparametricrangebaseddoublesmoothingspotvolatilityestimationfordiffusionmodels |