The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series
This paper proposes the cross-quantilogram to measure the quantile dependence between two time series. We apply it to test the hypothesis that one time series has no directional predictability to another time series. We establish the asymptotic distribution of the cross-quantilogram and the correspo...
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| Sprache: | Englisch |
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Elsevier
2019
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| Online-Zugang: | https://demo7.dspace.org/handle/123456789/471 |
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| author | Han, Heejoon Linton, Oliver Oka, Tatsushi Whang, Yoon-Jae |
| author2 | Systemic Physiological and Ecotoxicological Research (SPHERE) |
| author_browse | Han, Heejoon Linton, Oliver Oka, Tatsushi Systemic Physiological and Ecotoxicological Research (SPHERE) Whang, Yoon-Jae |
| author_facet | Systemic Physiological and Ecotoxicological Research (SPHERE) Han, Heejoon Linton, Oliver Oka, Tatsushi Whang, Yoon-Jae |
| author_sort | Han, Heejoon |
| collection | DSpace |
| description | This paper proposes the cross-quantilogram to measure the quantile dependence between two time series. We apply it to test the hypothesis that one time series has no directional predictability to another time series. We establish the asymptotic distribution of the cross-quantilogram and the corresponding test statistic. The limiting distributions depend on nuisance parameters. To construct consistent confidence intervals we employ a stationary bootstrap procedure; we establish consistency of this bootstrap. Also, we consider a self-normalized approach, which yields an asymptotically pivotal statistic under the null hypothesis of no predictability. We provide simulation studies and two empirical applications. First, we use the cross-quantilogram to detect predictability from stock variance to excess stock return. Compared to existing tools used in the literature of stock return predictability, our method provides a more complete relationship between a predictor and stock return. Second, we investigate the systemic risk of individual financial institutions, such as JP Morgan Chase, Morgan Stanley and AIG. |
| id | oai:localhost:123456789-471 |
| institution | DSPACE.FCHPT |
| language | English |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | oai:localhost:123456789-4712021-04-07T16:30:12Z The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series Han, Heejoon Linton, Oliver Oka, Tatsushi Whang, Yoon-Jae Systemic Physiological and Ecotoxicological Research (SPHERE) This paper proposes the cross-quantilogram to measure the quantile dependence between two time series. We apply it to test the hypothesis that one time series has no directional predictability to another time series. We establish the asymptotic distribution of the cross-quantilogram and the corresponding test statistic. The limiting distributions depend on nuisance parameters. To construct consistent confidence intervals we employ a stationary bootstrap procedure; we establish consistency of this bootstrap. Also, we consider a self-normalized approach, which yields an asymptotically pivotal statistic under the null hypothesis of no predictability. We provide simulation studies and two empirical applications. First, we use the cross-quantilogram to detect predictability from stock variance to excess stock return. Compared to existing tools used in the literature of stock return predictability, our method provides a more complete relationship between a predictor and stock return. Second, we investigate the systemic risk of individual financial institutions, such as JP Morgan Chase, Morgan Stanley and AIG. 2019-04-26T08:57:25Z 2019-04-26T08:57:25Z 30/03/16 https://demo7.dspace.org/handle/123456789/471 en Elsevier |
| spellingShingle | Han, Heejoon Linton, Oliver Oka, Tatsushi Whang, Yoon-Jae The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series |
| title | The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series |
| title_full | The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series |
| title_fullStr | The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series |
| title_full_unstemmed | The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series |
| title_short | The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series |
| title_sort | cross quantilogram measuring quantile dependence and testing directional predictability between time series |
| url | https://demo7.dspace.org/handle/123456789/471 |
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