{"title":"飞涨的全球食品价格:长期记忆过程的证据","authors":"I. Onour, B. Sergi","doi":"10.2139/ssrn.3049049","DOIUrl":null,"url":null,"abstract":"This paper analyze volatility persistence in global prices of wheat, rice and corn using monthly price data for two sample periods, before and after the shock on global food commodity markets on November 2007. Our findings show evidence of structural change in price trend in the post-shock period indicated by upward shift in the mean of the commodity series. Evidence of mean shift imply permanent demand side effects on price levels of these commodities. The result of changing price swings (covariance non-stationary) invalidate constant variance option-based pricing of future contracts on these commodities. Furthermore, given price series are covariance non-stationary and returning to the series long term trend “attractor” may take long time, forecast of future trend require non-standard statistical tools.","PeriodicalId":111133,"journal":{"name":"ERN: Agricultural Economics (Topic)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Soaring Global Food Commodity Prices: Evidence of Long Memory Process\",\"authors\":\"I. Onour, B. Sergi\",\"doi\":\"10.2139/ssrn.3049049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper analyze volatility persistence in global prices of wheat, rice and corn using monthly price data for two sample periods, before and after the shock on global food commodity markets on November 2007. Our findings show evidence of structural change in price trend in the post-shock period indicated by upward shift in the mean of the commodity series. Evidence of mean shift imply permanent demand side effects on price levels of these commodities. The result of changing price swings (covariance non-stationary) invalidate constant variance option-based pricing of future contracts on these commodities. Furthermore, given price series are covariance non-stationary and returning to the series long term trend “attractor” may take long time, forecast of future trend require non-standard statistical tools.\",\"PeriodicalId\":111133,\"journal\":{\"name\":\"ERN: Agricultural Economics (Topic)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Agricultural Economics (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3049049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Agricultural Economics (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3049049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Soaring Global Food Commodity Prices: Evidence of Long Memory Process
This paper analyze volatility persistence in global prices of wheat, rice and corn using monthly price data for two sample periods, before and after the shock on global food commodity markets on November 2007. Our findings show evidence of structural change in price trend in the post-shock period indicated by upward shift in the mean of the commodity series. Evidence of mean shift imply permanent demand side effects on price levels of these commodities. The result of changing price swings (covariance non-stationary) invalidate constant variance option-based pricing of future contracts on these commodities. Furthermore, given price series are covariance non-stationary and returning to the series long term trend “attractor” may take long time, forecast of future trend require non-standard statistical tools.