Volatility Forecasting: Downside Risk, Jumps and Leverage Effect
We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the size of positive and negative jumps and propose a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-02-01
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| Series: | Econometrics |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2225-1146/4/1/8 |
| _version_ | 1797999189489090560 |
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| author | Francesco Audrino Yujia Hu |
| author_facet | Francesco Audrino Yujia Hu |
| author_sort | Francesco Audrino |
| collection | DOAJ |
| description | We provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the size of positive and negative jumps and propose a methodology to estimate the size of jumps in the quadratic variation. The leverage effect is separated into continuous and discontinuous effects, and past volatility is separated into “good” and “bad”, as well as into continuous and discontinuous risks. Using a long history of the S & P500 price index, we find that the continuous leverage effect lasts about one week, while the discontinuous leverage effect disappears after one day. “Good” and “bad” continuous risks both characterize the volatility persistence, while “bad” jump risk is much more informative than “good” jump risk in forecasting future volatility. The volatility forecasting model proposed is able to capture many empirical stylized facts while still remaining parsimonious in terms of the number of parameters to be estimated. |
| first_indexed | 2024-04-11T11:00:44Z |
| format | Article |
| id | doaj.art-4e9bf2b5ff3346468522642edfb4aa26 |
| institution | Directory Open Access Journal |
| issn | 2225-1146 |
| language | English |
| last_indexed | 2024-04-11T11:00:44Z |
| publishDate | 2016-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Econometrics |
| spelling | doaj.art-4e9bf2b5ff3346468522642edfb4aa262022-12-22T04:28:38ZengMDPI AGEconometrics2225-11462016-02-0141810.3390/econometrics4010008econometrics4010008Volatility Forecasting: Downside Risk, Jumps and Leverage EffectFrancesco Audrino0Yujia Hu1Institute of Mathematics and Statistics, Department of Economics, University of St. Gallen, Bodanstrasse 6, 9000 St. Gallen, SwitzerlandInstitute of Mathematics and Statistics, Department of Economics, University of St. Gallen, Bodanstrasse 6, 9000 St. Gallen, SwitzerlandWe provide empirical evidence of volatility forecasting in relation to asymmetries present in the dynamics of both return and volatility processes. Using recently-developed methodologies to detect jumps from high frequency price data, we estimate the size of positive and negative jumps and propose a methodology to estimate the size of jumps in the quadratic variation. The leverage effect is separated into continuous and discontinuous effects, and past volatility is separated into “good” and “bad”, as well as into continuous and discontinuous risks. Using a long history of the S & P500 price index, we find that the continuous leverage effect lasts about one week, while the discontinuous leverage effect disappears after one day. “Good” and “bad” continuous risks both characterize the volatility persistence, while “bad” jump risk is much more informative than “good” jump risk in forecasting future volatility. The volatility forecasting model proposed is able to capture many empirical stylized facts while still remaining parsimonious in terms of the number of parameters to be estimated.http://www.mdpi.com/2225-1146/4/1/8high frequency datarealized volatility forecastingdownside riskleverage effect |
| spellingShingle | Francesco Audrino Yujia Hu Volatility Forecasting: Downside Risk, Jumps and Leverage Effect Econometrics high frequency data realized volatility forecasting downside risk leverage effect |
| title | Volatility Forecasting: Downside Risk, Jumps and Leverage Effect |
| title_full | Volatility Forecasting: Downside Risk, Jumps and Leverage Effect |
| title_fullStr | Volatility Forecasting: Downside Risk, Jumps and Leverage Effect |
| title_full_unstemmed | Volatility Forecasting: Downside Risk, Jumps and Leverage Effect |
| title_short | Volatility Forecasting: Downside Risk, Jumps and Leverage Effect |
| title_sort | volatility forecasting downside risk jumps and leverage effect |
| topic | high frequency data realized volatility forecasting downside risk leverage effect |
| url | http://www.mdpi.com/2225-1146/4/1/8 |
| work_keys_str_mv | AT francescoaudrino volatilityforecastingdownsideriskjumpsandleverageeffect AT yujiahu volatilityforecastingdownsideriskjumpsandleverageeffect |