Momentum and Reversal Strategies in Chinese Commodity Futures Markets

Yurun Yang, Ahmet Göncü, A. Pantelous
{"title":"Momentum and Reversal Strategies in Chinese Commodity Futures Markets","authors":"Yurun Yang, Ahmet Göncü, A. Pantelous","doi":"10.2139/ssrn.3069253","DOIUrl":null,"url":null,"abstract":"This paper tests a wide range of momentum and reversal strategies at different trading frequencies for the complete Chinese commodity futures market dataset. Accurate estimates of transaction costs for each commodity and the minute level futures prices are utilized to obtain the most realistic out-of-sample backtesting results. Distinctively from the existing literature, our dataset does not suffer from liquidity problems since the intra-day data is constructed from the most actively traded contracts for each and every of the 31 commodities included in our sample. Overall, there are three main findings of this study. First, momentum and reversal trading strategies can generate robust and consistent returns over time; however, the intra-day strategies used cannot generate sufficiently enough high excess returns to cover the excessive costs due to the higher frequency of trading. Secondly, at lower trading frequencies and longer holding periods momentum and reversal strategies can generate excess returns, but with higher maximum drawdown risk. Finally, the double-sort strategies statistically improve the performance of the trading strategies.","PeriodicalId":177064,"journal":{"name":"ERN: Other Econometric Modeling: Derivatives (Topic)","volume":"41 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Econometric Modeling: Derivatives (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3069253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

Abstract

This paper tests a wide range of momentum and reversal strategies at different trading frequencies for the complete Chinese commodity futures market dataset. Accurate estimates of transaction costs for each commodity and the minute level futures prices are utilized to obtain the most realistic out-of-sample backtesting results. Distinctively from the existing literature, our dataset does not suffer from liquidity problems since the intra-day data is constructed from the most actively traded contracts for each and every of the 31 commodities included in our sample. Overall, there are three main findings of this study. First, momentum and reversal trading strategies can generate robust and consistent returns over time; however, the intra-day strategies used cannot generate sufficiently enough high excess returns to cover the excessive costs due to the higher frequency of trading. Secondly, at lower trading frequencies and longer holding periods momentum and reversal strategies can generate excess returns, but with higher maximum drawdown risk. Finally, the double-sort strategies statistically improve the performance of the trading strategies.
中国商品期货市场的动量与反转策略
本文对中国商品期货市场完整数据集在不同交易频率下的动量和反转策略进行了广泛的测试。利用对每种商品的交易成本和分钟级期货价格的准确估计,获得最真实的样本外回测结果。与现有文献不同的是,我们的数据集没有流动性问题,因为日内数据是根据我们样本中31种商品中每一种交易最活跃的合约构建的。总的来说,这项研究有三个主要发现。首先,随着时间的推移,动量和反转交易策略可以产生强劲而持续的回报;然而,所使用的日内策略不能产生足够高的超额回报来弥补由于交易频率较高而产生的超额成本。其次,在较低的交易频率和较长的持有时间下,动量和反转策略可以产生超额回报,但具有较高的最大回撤风险。最后,双排序策略在统计上提高了交易策略的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信