{"title":"全球天气交易策略","authors":"Ming Dong, A. Tremblay","doi":"10.2139/ssrn.3111467","DOIUrl":null,"url":null,"abstract":"We estimate the profitability of global index-level trading strategies formed on daily weather conditions across 49 countries. We use pre-market weather conditions (sunshine, wind, rain, snow, and temperature) and the statistical relationship between weather and returns to predict index returns each day. In the out-of-sample test for our 1993-2012 sample, a global weather-based hedge strategy produces a mean annual return of 15.2% compared to a mean world index return of 3.1%, corresponding to a Sharpe ratio of 0.462 relative to 0.005 for the world index. Our findings confirm that multiple weather conditions exert economically important impacts on stock returns around the globe.","PeriodicalId":10477,"journal":{"name":"Cognitive Social Science eJournal","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Global Weather-Based Trading Strategies\",\"authors\":\"Ming Dong, A. Tremblay\",\"doi\":\"10.2139/ssrn.3111467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We estimate the profitability of global index-level trading strategies formed on daily weather conditions across 49 countries. We use pre-market weather conditions (sunshine, wind, rain, snow, and temperature) and the statistical relationship between weather and returns to predict index returns each day. In the out-of-sample test for our 1993-2012 sample, a global weather-based hedge strategy produces a mean annual return of 15.2% compared to a mean world index return of 3.1%, corresponding to a Sharpe ratio of 0.462 relative to 0.005 for the world index. Our findings confirm that multiple weather conditions exert economically important impacts on stock returns around the globe.\",\"PeriodicalId\":10477,\"journal\":{\"name\":\"Cognitive Social Science eJournal\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Social Science eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3111467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Social Science eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3111467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We estimate the profitability of global index-level trading strategies formed on daily weather conditions across 49 countries. We use pre-market weather conditions (sunshine, wind, rain, snow, and temperature) and the statistical relationship between weather and returns to predict index returns each day. In the out-of-sample test for our 1993-2012 sample, a global weather-based hedge strategy produces a mean annual return of 15.2% compared to a mean world index return of 3.1%, corresponding to a Sharpe ratio of 0.462 relative to 0.005 for the world index. Our findings confirm that multiple weather conditions exert economically important impacts on stock returns around the globe.