{"title":"用彩票指数预测股市收益：来自中国的证据","authors":"Yaojie Zhang, Qingxiang Han, Mengxi He","doi":"10.1002/for.3100","DOIUrl":null,"url":null,"abstract":"<p>This study constructs a Chinese lottery index (LI) based on six popular lottery preference variables by using the partial least squares method and examines the relationship between the LI and future stock market returns during the period from January 2000 to December 2021. We find that the LI can negatively predict stock market excess returns in-sample and out-of-sample. In addition, the LI can generate a large economic gain for a mean–variance investor. Finally, the predictive sources of the LI stem from a cash flow channel and can be explained by the positive volume–volatility relationship and investor attention.</p>","PeriodicalId":47835,"journal":{"name":"Journal of Forecasting","volume":"43 5","pages":"1595-1606"},"PeriodicalIF":3.4000,"publicationDate":"2024-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forecasting stock market returns with a lottery index: Evidence from China\",\"authors\":\"Yaojie Zhang, Qingxiang Han, Mengxi He\",\"doi\":\"10.1002/for.3100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This study constructs a Chinese lottery index (LI) based on six popular lottery preference variables by using the partial least squares method and examines the relationship between the LI and future stock market returns during the period from January 2000 to December 2021. We find that the LI can negatively predict stock market excess returns in-sample and out-of-sample. In addition, the LI can generate a large economic gain for a mean–variance investor. Finally, the predictive sources of the LI stem from a cash flow channel and can be explained by the positive volume–volatility relationship and investor attention.</p>\",\"PeriodicalId\":47835,\"journal\":{\"name\":\"Journal of Forecasting\",\"volume\":\"43 5\",\"pages\":\"1595-1606\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-02-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Forecasting\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/for.3100\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forecasting","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/for.3100","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Forecasting stock market returns with a lottery index: Evidence from China
This study constructs a Chinese lottery index (LI) based on six popular lottery preference variables by using the partial least squares method and examines the relationship between the LI and future stock market returns during the period from January 2000 to December 2021. We find that the LI can negatively predict stock market excess returns in-sample and out-of-sample. In addition, the LI can generate a large economic gain for a mean–variance investor. Finally, the predictive sources of the LI stem from a cash flow channel and can be explained by the positive volume–volatility relationship and investor attention.
期刊介绍：
The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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