{"title":"收益预测模型能增加经济价值吗?","authors":"Tolga Cenesizoglu, A. Timmermann","doi":"10.2139/ssrn.1913736","DOIUrl":null,"url":null,"abstract":"We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.","PeriodicalId":331246,"journal":{"name":"24th Australasian Finance & Banking Conference 2011 (Archive)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Do Return Prediction Models Add Economic Value?\",\"authors\":\"Tolga Cenesizoglu, A. Timmermann\",\"doi\":\"10.2139/ssrn.1913736\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.\",\"PeriodicalId\":331246,\"journal\":{\"name\":\"24th Australasian Finance & Banking Conference 2011 (Archive)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"24th Australasian Finance & Banking Conference 2011 (Archive)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.1913736\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"24th Australasian Finance & Banking Conference 2011 (Archive)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.1913736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.