{"title":"前景理论与交易人群主观行为测度","authors":"Leilei Shi","doi":"10.2139/ssrn.2512319","DOIUrl":null,"url":null,"abstract":"We measure crowd’s decision weights in trading by trading volume distribution and determine a reference price about crowd’s assessment value of an individual stock by the maximum volume price in stock market. We examine a reference-dependent preferences hypothesis in trading by two sets of explicit trading volume distribution models, which are connected to an explicit S-shaped value function in prospect theory. It is true with 82.42% in our tests, using high frequency data in China stock market. We explain the patterns of volume distribution by four behavioral features: mental accounting, disposition, decision weight, and coherence or agreement. Moreover, crowd’s traders update a reference price about the assessment value of an individual stock in jump from time to time. It takes place about 11.92% on a trading day. The measure of subjective behaviors by a volume dimension suggests the new openings of asset pricing models and test methodologies in financial economics.","PeriodicalId":198417,"journal":{"name":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Prospect Theory and Measurement on Crowd’s Subjective Behaviors in Trading\",\"authors\":\"Leilei Shi\",\"doi\":\"10.2139/ssrn.2512319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We measure crowd’s decision weights in trading by trading volume distribution and determine a reference price about crowd’s assessment value of an individual stock by the maximum volume price in stock market. We examine a reference-dependent preferences hypothesis in trading by two sets of explicit trading volume distribution models, which are connected to an explicit S-shaped value function in prospect theory. It is true with 82.42% in our tests, using high frequency data in China stock market. We explain the patterns of volume distribution by four behavioral features: mental accounting, disposition, decision weight, and coherence or agreement. Moreover, crowd’s traders update a reference price about the assessment value of an individual stock in jump from time to time. It takes place about 11.92% on a trading day. The measure of subjective behaviors by a volume dimension suggests the new openings of asset pricing models and test methodologies in financial economics.\",\"PeriodicalId\":198417,\"journal\":{\"name\":\"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.2512319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DecisionSciRN: Stock Market Decision-Making (Sub-Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.2512319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prospect Theory and Measurement on Crowd’s Subjective Behaviors in Trading
We measure crowd’s decision weights in trading by trading volume distribution and determine a reference price about crowd’s assessment value of an individual stock by the maximum volume price in stock market. We examine a reference-dependent preferences hypothesis in trading by two sets of explicit trading volume distribution models, which are connected to an explicit S-shaped value function in prospect theory. It is true with 82.42% in our tests, using high frequency data in China stock market. We explain the patterns of volume distribution by four behavioral features: mental accounting, disposition, decision weight, and coherence or agreement. Moreover, crowd’s traders update a reference price about the assessment value of an individual stock in jump from time to time. It takes place about 11.92% on a trading day. The measure of subjective behaviors by a volume dimension suggests the new openings of asset pricing models and test methodologies in financial economics.