Revisit hemline index theory: Forecasting daily trading of short skirts by stock market in China

Hao Chen, Ying-hong Dong, Kaisheng Lai
{"title":"Revisit hemline index theory: Forecasting daily trading of short skirts by stock market in China","authors":"Hao Chen, Ying-hong Dong, Kaisheng Lai","doi":"10.1109/BESC.2016.7804479","DOIUrl":null,"url":null,"abstract":"There are many similarities on fluctuations between clothing styles and finance so that many theorists approach to analyze the relationship of them, the best known of which is the Hemline Index Theory. When the economy is flourishing, hemlines increase, and when the economic situation is deteriorating, the hemlines drop, perhaps even to the floor. In contrast with measuring the illustrations from the fashion magazines of monthly publication traditionally, we collected daily time series of the hemline indicator using the searching volume and trading volume of short skirts on Taobao Index website. Then we evaluated it against the closing price of Shanghai Composite Index by Granger causality analysis and liner regression model during the period of March 1, 2013 to November 30, 2013. The main finding is that the closing price of stock market is the Granger causality of the searching volume and trading volume of short skirts. The rising of closing price in stock market can predict the more searching volume and purchase of short skirts one day later which verifies the hemline index theory on daily basis. Further confirmation based on different data resources and fashion measures is needed.","PeriodicalId":225942,"journal":{"name":"2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BESC.2016.7804479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

There are many similarities on fluctuations between clothing styles and finance so that many theorists approach to analyze the relationship of them, the best known of which is the Hemline Index Theory. When the economy is flourishing, hemlines increase, and when the economic situation is deteriorating, the hemlines drop, perhaps even to the floor. In contrast with measuring the illustrations from the fashion magazines of monthly publication traditionally, we collected daily time series of the hemline indicator using the searching volume and trading volume of short skirts on Taobao Index website. Then we evaluated it against the closing price of Shanghai Composite Index by Granger causality analysis and liner regression model during the period of March 1, 2013 to November 30, 2013. The main finding is that the closing price of stock market is the Granger causality of the searching volume and trading volume of short skirts. The rising of closing price in stock market can predict the more searching volume and purchase of short skirts one day later which verifies the hemline index theory on daily basis. Further confirmation based on different data resources and fashion measures is needed.
回顾裙摆指数理论:预测中国股市短裙的日交易量
服装款式的波动与金融有许多相似之处,因此许多理论家都试图分析它们之间的关系,其中最著名的是裙摆指数理论。当经济繁荣时,裙摆会变长,而当经济形势恶化时,裙摆会下降,甚至落在地板上。与传统的月刊时尚杂志插图测量不同,我们利用淘宝指数网站上短裙的搜索量和交易量来收集裙摆指标的日时间序列。然后对2013年3月1日至2013年11月30日上证综指收盘价进行格兰杰因果分析和线性回归模型评价。主要发现是股票市场收盘价是短裙搜索量和交易量的Granger因果关系。股票市场收盘价的上涨可以预测一天后短裙的搜索量和购买量,从而验证裙摆指数理论。需要根据不同的数据资源和时尚措施进一步确认。
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