{"title":"预测国家橄榄球联盟的比赛结果相对于投注价差","authors":"W. Mallios","doi":"10.5750/JGBE.V6I3.609","DOIUrl":null,"url":null,"abstract":"Cointegrated time processes measuring NFL playoff game performances relative to the betting spreads are graphed in terms of candlestick charts and forecast in terms of autoregressive systems with time varying coefficients. Coefficients are modeled in terms of linear regressions on lagged shocks. Estimation is non Bayesian. Forecasts provide measures of market efficiency/inefficiency and outcome volatility. Risk assessment utilizes GARCH-type modeling in estimating volatility. Applications are presented for the New York Giants 2012 playoff games based on a data backlog of three years.","PeriodicalId":109210,"journal":{"name":"The Journal of Gambling Business and Economics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"FORECASTING NATIONAL FOOTBALL LEAGUE GAME OUTCOMES RELATIVE TO BETTING SPREADS\",\"authors\":\"W. Mallios\",\"doi\":\"10.5750/JGBE.V6I3.609\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cointegrated time processes measuring NFL playoff game performances relative to the betting spreads are graphed in terms of candlestick charts and forecast in terms of autoregressive systems with time varying coefficients. Coefficients are modeled in terms of linear regressions on lagged shocks. Estimation is non Bayesian. Forecasts provide measures of market efficiency/inefficiency and outcome volatility. Risk assessment utilizes GARCH-type modeling in estimating volatility. Applications are presented for the New York Giants 2012 playoff games based on a data backlog of three years.\",\"PeriodicalId\":109210,\"journal\":{\"name\":\"The Journal of Gambling Business and Economics\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of Gambling Business and Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5750/JGBE.V6I3.609\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Gambling Business and Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5750/JGBE.V6I3.609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FORECASTING NATIONAL FOOTBALL LEAGUE GAME OUTCOMES RELATIVE TO BETTING SPREADS
Cointegrated time processes measuring NFL playoff game performances relative to the betting spreads are graphed in terms of candlestick charts and forecast in terms of autoregressive systems with time varying coefficients. Coefficients are modeled in terms of linear regressions on lagged shocks. Estimation is non Bayesian. Forecasts provide measures of market efficiency/inefficiency and outcome volatility. Risk assessment utilizes GARCH-type modeling in estimating volatility. Applications are presented for the New York Giants 2012 playoff games based on a data backlog of three years.
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