Volatility forecast comparison using imperfect volatility.
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable out- comes in standard methods for comparing conditional variance forecasts. We motivate our study with analytical results on the distortions caused by some widely-used loss functions, when used with stan-da...
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| Format: | Working paper |
| Language: | English |
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Oxford-Man Institute of Quantitative Finance
2007
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| _version_ | 1797054014281482240 |
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| author | Patton, A |
| author_facet | Patton, A |
| author_sort | Patton, A |
| collection | OXFORD |
| description | The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable out- comes in standard methods for comparing conditional variance forecasts. We motivate our study with analytical results on the distortions caused by some widely-used loss functions, when used with stan-dard volatility proxies such as squared returns, the intra-daily range or realised volatility. We then derive necessary and sufficient conditions on the functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some useful special cases of this class of “robust” loss functions. The methods are illustrated with an application to the volatility of returns on IBM over the period 1993 to 2003. |
| first_indexed | 2024-03-06T18:51:36Z |
| format | Working paper |
| id | oxford-uuid:106d4ae1-12a4-4bc3-a2c6-7e22778fcd06 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:51:36Z |
| publishDate | 2007 |
| publisher | Oxford-Man Institute of Quantitative Finance |
| record_format | dspace |
| spelling | oxford-uuid:106d4ae1-12a4-4bc3-a2c6-7e22778fcd062022-03-26T09:56:23ZVolatility forecast comparison using imperfect volatility.Working paperhttp://purl.org/coar/resource_type/c_8042uuid:106d4ae1-12a4-4bc3-a2c6-7e22778fcd06EnglishDepartment of Economics - ePrintsOxford-Man Institute of Quantitative Finance2007Patton, AThe use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable out- comes in standard methods for comparing conditional variance forecasts. We motivate our study with analytical results on the distortions caused by some widely-used loss functions, when used with stan-dard volatility proxies such as squared returns, the intra-daily range or realised volatility. We then derive necessary and sufficient conditions on the functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some useful special cases of this class of “robust” loss functions. The methods are illustrated with an application to the volatility of returns on IBM over the period 1993 to 2003. |
| spellingShingle | Patton, A Volatility forecast comparison using imperfect volatility. |
| title | Volatility forecast comparison using imperfect volatility. |
| title_full | Volatility forecast comparison using imperfect volatility. |
| title_fullStr | Volatility forecast comparison using imperfect volatility. |
| title_full_unstemmed | Volatility forecast comparison using imperfect volatility. |
| title_short | Volatility forecast comparison using imperfect volatility. |
| title_sort | volatility forecast comparison using imperfect volatility |
| work_keys_str_mv | AT pattona volatilityforecastcomparisonusingimperfectvolatility |