An Alternative Approach to Measure Co-Movement between Two Time Series
The study of the dependences between different assets is a classic topic in financial literature. To understand how the movements of one asset affect to others is critical for derivatives pricing, portfolio management, risk control, or trading strategies. Over time, different methodologies were prop...
| Main Authors: | , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
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MDPI
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/7743 |
| _version_ | 1789406754506801152 |
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| author | Ramos Requena, José Pedro Trinidad Segovia, Juan Evangelista Sánchez Granero, Miguel Ángel |
| author_facet | Ramos Requena, José Pedro Trinidad Segovia, Juan Evangelista Sánchez Granero, Miguel Ángel |
| author_sort | Ramos Requena, José Pedro |
| collection | DSpace |
| description | The study of the dependences between different assets is a classic topic in financial literature. To understand how the movements of one asset affect to others is critical for derivatives pricing, portfolio management, risk control, or trading strategies. Over time, different methodologies were proposed by researchers. ARCH, GARCH or EGARCH models, among others, are very popular to model volatility autocorrelation. In this paper, a new simple method called HP is introduced to measure the co-movement between two time series. This method, based on the Hurst exponent of the product series, is designed to detect correlation, even if the relationship is weak, but it also works fine with cointegration as well as non linear correlations or more complex relationships given by a copula. This method and different variations thereaof are tested in statistical arbitrage. Results show that HP is able to detect the relationship between assets better than the traditional correlation method. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-7743 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2020 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-77432023-04-12T19:10:51Z An Alternative Approach to Measure Co-Movement between Two Time Series Ramos Requena, José Pedro Trinidad Segovia, Juan Evangelista Sánchez Granero, Miguel Ángel Hurst exponent pairs trading correlation co-movement The study of the dependences between different assets is a classic topic in financial literature. To understand how the movements of one asset affect to others is critical for derivatives pricing, portfolio management, risk control, or trading strategies. Over time, different methodologies were proposed by researchers. ARCH, GARCH or EGARCH models, among others, are very popular to model volatility autocorrelation. In this paper, a new simple method called HP is introduced to measure the co-movement between two time series. This method, based on the Hurst exponent of the product series, is designed to detect correlation, even if the relationship is weak, but it also works fine with cointegration as well as non linear correlations or more complex relationships given by a copula. This method and different variations thereaof are tested in statistical arbitrage. Results show that HP is able to detect the relationship between assets better than the traditional correlation method. 2020-03-02T11:40:26Z 2020-03-02T11:40:26Z 2020-02-17 info:eu-repo/semantics/article 2227-7390 http://hdl.handle.net/10835/7743 en https://www.mdpi.com/2227-7390/8/2/261 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess MDPI |
| spellingShingle | Hurst exponent pairs trading correlation co-movement Ramos Requena, José Pedro Trinidad Segovia, Juan Evangelista Sánchez Granero, Miguel Ángel An Alternative Approach to Measure Co-Movement between Two Time Series |
| title | An Alternative Approach to Measure Co-Movement between Two Time Series |
| title_full | An Alternative Approach to Measure Co-Movement between Two Time Series |
| title_fullStr | An Alternative Approach to Measure Co-Movement between Two Time Series |
| title_full_unstemmed | An Alternative Approach to Measure Co-Movement between Two Time Series |
| title_short | An Alternative Approach to Measure Co-Movement between Two Time Series |
| title_sort | alternative approach to measure co-movement between two time series |
| topic | Hurst exponent pairs trading correlation co-movement |
| url | http://hdl.handle.net/10835/7743 |
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