Grzegorz Andruszkiewicz, Mark H. A. Davis, Sébastien Lleo
{"title":"Estimating animal spirits: conservative risk calculation","authors":"Grzegorz Andruszkiewicz, Mark H. A. Davis, Sébastien Lleo","doi":"10.1080/21649502.2014.946234","DOIUrl":null,"url":null,"abstract":"In this paper, we estimate behavioural factors—Keynes’ ‘animal spirits’—in the property market. An enhanced hidden Markov model is used, for both the Shiller Home Price Index and a consumer confidence index. We conclude that both house prices and consumer confidence are driven by another hidden behavioural factor, interpreted as ‘animal spirits’. Both data series imply similar paths of the hidden factor. The estimated model is used for value-at-risk calculation and forecasting. We introduce an intuitive method to include crisis scenarios in the model, which proves to produce much better risk estimates during the credit crunch, without substantially affecting the distribution during growth periods.","PeriodicalId":438897,"journal":{"name":"Quantitative Finance Letters","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quantitative Finance Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/21649502.2014.946234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, we estimate behavioural factors—Keynes’ ‘animal spirits’—in the property market. An enhanced hidden Markov model is used, for both the Shiller Home Price Index and a consumer confidence index. We conclude that both house prices and consumer confidence are driven by another hidden behavioural factor, interpreted as ‘animal spirits’. Both data series imply similar paths of the hidden factor. The estimated model is used for value-at-risk calculation and forecasting. We introduce an intuitive method to include crisis scenarios in the model, which proves to produce much better risk estimates during the credit crunch, without substantially affecting the distribution during growth periods.