Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures

Calculating accurately the optimal hedge ratio plays an important role in the futures market for both practitioners and academicians. In this paper, we combine copula and nonparametric technique, where marginal setting is modeled by nonparametric technique and bivariate is linked by dynamic Patton (...

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Main Authors: Zhiyuan Pan, Xianchao Sun
Format: Article
Language:English
Published: EconJournals 2014-03-01
Series:International Journal of Economics and Financial Issues
Subjects:
Online Access:https://dergipark.org.tr/tr/pub/ijefi/issue/31961/351985?publisher=http-www-cag-edu-tr-ilhan-ozturk
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spelling doaj-ab9d998b90a34558b21381197cbdfb7f2020-11-24T21:50:44ZengEconJournalsInternational Journal of Economics and Financial Issues2146-41382014-03-01411071211032Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index FuturesZhiyuan PanXianchao SunCalculating accurately the optimal hedge ratio plays an important role in the futures market for both practitioners and academicians. In this paper, we combine copula and nonparametric technique, where marginal setting is modeled by nonparametric technique and bivariate is linked by dynamic Patton (2006)'s SJC copula function, to estimate the parameters of optimal hedge ratio. Various types of GARCH models to fit the marginal distribution are also compared. Furthermore, model specification for marginal setting is investigated by Hong and Li (2005)'s statistics, which test the i.i.d. and U(0,1) simultaneously. The empirical results show that transformed residuals generated by nonparametric technique are i.i.d. U(0,1), while most of one generated by popular GARCH-type are not. For hedging effectiveness, our methods perform better than traditional copula-GARCH models. The robust test also supports the results.https://dergipark.org.tr/tr/pub/ijefi/issue/31961/351985?publisher=http-www-cag-edu-tr-ilhan-ozturkhedge strategy optimal hedge ratio nonparametric estimation patton (2006)'s sjc-copula hong and li (2005)'s statistics csi 300 index futures.
collection DOAJ
language English
format Article
sources DOAJ
author Zhiyuan Pan
Xianchao Sun
spellingShingle Zhiyuan Pan
Xianchao Sun
Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures
International Journal of Economics and Financial Issues
hedge strategy
optimal hedge ratio
nonparametric estimation
patton (2006)'s sjc-copula
hong and li (2005)'s statistics
csi 300 index futures.
author_facet Zhiyuan Pan
Xianchao Sun
author_sort Zhiyuan Pan
title Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures
title_short Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures
title_full Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures
title_fullStr Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures
title_full_unstemmed Hedging Strategy Using Copula and Nonparametric Methods: Evidence from China Securities Index Futures
title_sort hedging strategy using copula and nonparametric methods: evidence from china securities index futures
publisher EconJournals
series International Journal of Economics and Financial Issues
issn 2146-4138
publishDate 2014-03-01
description Calculating accurately the optimal hedge ratio plays an important role in the futures market for both practitioners and academicians. In this paper, we combine copula and nonparametric technique, where marginal setting is modeled by nonparametric technique and bivariate is linked by dynamic Patton (2006)'s SJC copula function, to estimate the parameters of optimal hedge ratio. Various types of GARCH models to fit the marginal distribution are also compared. Furthermore, model specification for marginal setting is investigated by Hong and Li (2005)'s statistics, which test the i.i.d. and U(0,1) simultaneously. The empirical results show that transformed residuals generated by nonparametric technique are i.i.d. U(0,1), while most of one generated by popular GARCH-type are not. For hedging effectiveness, our methods perform better than traditional copula-GARCH models. The robust test also supports the results.
topic hedge strategy
optimal hedge ratio
nonparametric estimation
patton (2006)'s sjc-copula
hong and li (2005)'s statistics
csi 300 index futures.
url https://dergipark.org.tr/tr/pub/ijefi/issue/31961/351985?publisher=http-www-cag-edu-tr-ilhan-ozturk
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AT xianchaosun hedgingstrategyusingcopulaandnonparametricmethodsevidencefromchinasecuritiesindexfutures
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