{"title":"预测石油价格走势:利用未来市场的信息","authors":"A. Coppola","doi":"10.2139/ssrn.967408","DOIUrl":null,"url":null,"abstract":"Relying on the cost of carry model, we investigate the long-run relationship between spot and futures prices and use the information implied in these cointegrating relationships to forecast out of sample oil spot and futures price movements. In order to forecast oil price movements, we employ a Vector Error Correction Model (VECM), where the deviations from the long-run relationships between spot and futures prices constitute the equilibrium error. In order to evaluate forecasting performance we use the Random Walk Model (RWM) as a benchmark. We .nd that: (i) in-sample, the information in the futures market can explain a sizeable portion of oil price movements; (ii) out-of-sample, the VECM is able to beat the random walk model, both in terms of point forecasting and in terms of market timing ability","PeriodicalId":416571,"journal":{"name":"CEIS: Centre for Economic & International Studies Working Paper Series","volume":"375 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Forecasting Oil Price Movements: Exploiting the Information In the Future Market\",\"authors\":\"A. Coppola\",\"doi\":\"10.2139/ssrn.967408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Relying on the cost of carry model, we investigate the long-run relationship between spot and futures prices and use the information implied in these cointegrating relationships to forecast out of sample oil spot and futures price movements. In order to forecast oil price movements, we employ a Vector Error Correction Model (VECM), where the deviations from the long-run relationships between spot and futures prices constitute the equilibrium error. In order to evaluate forecasting performance we use the Random Walk Model (RWM) as a benchmark. We .nd that: (i) in-sample, the information in the futures market can explain a sizeable portion of oil price movements; (ii) out-of-sample, the VECM is able to beat the random walk model, both in terms of point forecasting and in terms of market timing ability\",\"PeriodicalId\":416571,\"journal\":{\"name\":\"CEIS: Centre for Economic & International Studies Working Paper Series\",\"volume\":\"375 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CEIS: Centre for Economic & International Studies Working Paper Series\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.967408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CEIS: Centre for Economic & International Studies Working Paper Series","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.967408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forecasting Oil Price Movements: Exploiting the Information In the Future Market
Relying on the cost of carry model, we investigate the long-run relationship between spot and futures prices and use the information implied in these cointegrating relationships to forecast out of sample oil spot and futures price movements. In order to forecast oil price movements, we employ a Vector Error Correction Model (VECM), where the deviations from the long-run relationships between spot and futures prices constitute the equilibrium error. In order to evaluate forecasting performance we use the Random Walk Model (RWM) as a benchmark. We .nd that: (i) in-sample, the information in the futures market can explain a sizeable portion of oil price movements; (ii) out-of-sample, the VECM is able to beat the random walk model, both in terms of point forecasting and in terms of market timing ability