We examine analysts' implied expected rates of return for recent IPO firms relative to more seasoned firms. We document that analysts have relatively more optimistic expectations about recent IPO firms relative to seasoned firms, and these optimistic expectations persist, on average, for four years following the IPO. We also document that the market has optimistic expectations for recent IPO firms relative to more seasoned firms, but only for the first year following listing. Our results are robust to controls for industry, size, book-to-market, the age of the firm, analysts' expected long-term growth, the number of analysts following the firms, the level of dispersion in analysts' forecasts, and external financing activities. Our results suggest that analysts' retain optimistic expectations regarding recent IPO firms relative to more seasoned firms for an extended period of time after the IPO event.
{"title":"The Extent and Duration of Analysts' Optimistic Expectations of Initial Public Offer Firms","authors":"Asher Curtis, J. Yeo","doi":"10.2139/ssrn.891195","DOIUrl":"https://doi.org/10.2139/ssrn.891195","url":null,"abstract":"We examine analysts' implied expected rates of return for recent IPO firms relative to more seasoned firms. We document that analysts have relatively more optimistic expectations about recent IPO firms relative to seasoned firms, and these optimistic expectations persist, on average, for four years following the IPO. We also document that the market has optimistic expectations for recent IPO firms relative to more seasoned firms, but only for the first year following listing. Our results are robust to controls for industry, size, book-to-market, the age of the firm, analysts' expected long-term growth, the number of analysts following the firms, the level of dispersion in analysts' forecasts, and external financing activities. Our results suggest that analysts' retain optimistic expectations regarding recent IPO firms relative to more seasoned firms for an extended period of time after the IPO event.","PeriodicalId":442653,"journal":{"name":"Capital Market Intermediaries","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129625701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Boris Groysberg, P. Healy, C. Chapman, Devin M. Shanthikumar, Yang Gui
We examine the performance of buy-side analysts relative to that of the sell-side. Our tests show that buy-side analysts at a large investment firm make less optimistic stock recommendations than sell-side analysts, consistent with their facing fewer conflicts of interest. However, their earnings forecasts are relatively optimistic and inaccurate and returns to their buy recommendations under-perform sell-side recommendations. Large sample tests that compare the performance of sell-side analyst recommendations and portfolio managers who rely exclusively on buy-side research confirm the sell-side's superiority. These performance differences appear to be partially explained by the buy-side's higher retention of poor-performing analysts and by differences in performance benchmarks used to evaluate buy- and sell-side analysts.
{"title":"Do Buy-Side Analysts Out-Perform the Sell-Side?","authors":"Boris Groysberg, P. Healy, C. Chapman, Devin M. Shanthikumar, Yang Gui","doi":"10.2139/ssrn.806264","DOIUrl":"https://doi.org/10.2139/ssrn.806264","url":null,"abstract":"We examine the performance of buy-side analysts relative to that of the sell-side. Our tests show that buy-side analysts at a large investment firm make less optimistic stock recommendations than sell-side analysts, consistent with their facing fewer conflicts of interest. However, their earnings forecasts are relatively optimistic and inaccurate and returns to their buy recommendations under-perform sell-side recommendations. Large sample tests that compare the performance of sell-side analyst recommendations and portfolio managers who rely exclusively on buy-side research confirm the sell-side's superiority. These performance differences appear to be partially explained by the buy-side's higher retention of poor-performing analysts and by differences in performance benchmarks used to evaluate buy- and sell-side analysts.","PeriodicalId":442653,"journal":{"name":"Capital Market Intermediaries","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122232324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We model and estimate analysts' herding propensity with I/B/E/S annual earnings forecast data. Compared to prior studies, our paper has three unique features. First, we estimate analysts' true posterior beliefs of a firm's earnings assuming rational expectations rather than using analysts' own prior forecasts. Second, we estimate analysts' herding propensity at aggregate and the analyst levels rather than the forecast level. Third, we perform out-of-sample rather than in-sample tests on the usefulness of our herding propensity estimates. We document pervasive herding behavior. At the aggregate level, we find that herding propensity is positively related to forecast horizon and analyst coverage, but negatively related to analysts' general experience and brokerage size. At the analyst level, we find that about 75% (15%) of the analysts in our sample tend to herd (anti-herd). Moreover, our in-sample herding propensity estimates are useful in explaining the cross-sectional variation in analysts' out-of-sample herding behavior and forecast accuracy.
{"title":"Analysts' Herding Propensity: Theory and Evidence from Earnings Forecasts","authors":"M. Krishnan, Steve C. Lim, P. Zhou","doi":"10.2139/ssrn.929467","DOIUrl":"https://doi.org/10.2139/ssrn.929467","url":null,"abstract":"We model and estimate analysts' herding propensity with I/B/E/S annual earnings forecast data. Compared to prior studies, our paper has three unique features. First, we estimate analysts' true posterior beliefs of a firm's earnings assuming rational expectations rather than using analysts' own prior forecasts. Second, we estimate analysts' herding propensity at aggregate and the analyst levels rather than the forecast level. Third, we perform out-of-sample rather than in-sample tests on the usefulness of our herding propensity estimates. We document pervasive herding behavior. At the aggregate level, we find that herding propensity is positively related to forecast horizon and analyst coverage, but negatively related to analysts' general experience and brokerage size. At the analyst level, we find that about 75% (15%) of the analysts in our sample tend to herd (anti-herd). Moreover, our in-sample herding propensity estimates are useful in explaining the cross-sectional variation in analysts' out-of-sample herding behavior and forecast accuracy.","PeriodicalId":442653,"journal":{"name":"Capital Market Intermediaries","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122007300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：