{"title":"中国商品期货市场的配对交易:自适应协整方法","authors":"Danni Chen, Jing Cui, Yan Gao, Leilei Wu","doi":"10.1111/acfi.12335","DOIUrl":null,"url":null,"abstract":"This study comprehensively examines pairs trading in Chinese commodity futures markets, which, although less researched, represents an important scenario for analysing commodity price behaviour. Based on a sample of daily future returns from 2006 to 2016, we propose a cointegration model that employs an adaptive learning process, and we show that our model yields an average annualised return of 26.94 percent before trading costs, using a closed‐loop strategy. Our results are robust to various tests, including parameter uncertainty, holding period constraints, trading period selection and trading costs.","PeriodicalId":306457,"journal":{"name":"ERN: Futures (Topic)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Pairs Trading in Chinese Commodity Futures Markets: An Adaptive Cointegration Approach\",\"authors\":\"Danni Chen, Jing Cui, Yan Gao, Leilei Wu\",\"doi\":\"10.1111/acfi.12335\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study comprehensively examines pairs trading in Chinese commodity futures markets, which, although less researched, represents an important scenario for analysing commodity price behaviour. Based on a sample of daily future returns from 2006 to 2016, we propose a cointegration model that employs an adaptive learning process, and we show that our model yields an average annualised return of 26.94 percent before trading costs, using a closed‐loop strategy. Our results are robust to various tests, including parameter uncertainty, holding period constraints, trading period selection and trading costs.\",\"PeriodicalId\":306457,\"journal\":{\"name\":\"ERN: Futures (Topic)\",\"volume\":\"282 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Futures (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1111/acfi.12335\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Futures (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1111/acfi.12335","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Pairs Trading in Chinese Commodity Futures Markets: An Adaptive Cointegration Approach
This study comprehensively examines pairs trading in Chinese commodity futures markets, which, although less researched, represents an important scenario for analysing commodity price behaviour. Based on a sample of daily future returns from 2006 to 2016, we propose a cointegration model that employs an adaptive learning process, and we show that our model yields an average annualised return of 26.94 percent before trading costs, using a closed‐loop strategy. Our results are robust to various tests, including parameter uncertainty, holding period constraints, trading period selection and trading costs.