The Value of Crowdsourced Earnings Forecasts

Autor:	Stanimir Markov, Russell Jame, Michael C. Wolfe, Rick Johnston
Rok vydání:	2016
Předmět:	Economics and Econometrics 050208 finance Open platform Earnings business.industry Financial economics 05 social sciences Sample (statistics) 050201 accounting Crowdsourcing Investment (macroeconomics) Task (project management) ComputerApplications_MISCELLANEOUS Accounting 0502 economics and business Value (economics) business Capital market Finance
Zdroj:	Journal of Accounting Research. 54:1077-1110
ISSN:	0021-8456
DOI:	10.1111/1475-679x.12121
Popis:	Crowdsourcing—when a task normally performed by employees is outsourced to a large network of people via an open call—is making inroads into the investment research industry. We shed light on this new phenomenon by examining the value of crowdsourced earnings forecasts. Our sample includes 51,012 forecasts provided by Estimize, an open platform that solicits and reports forecasts from over 3,000 contributors. We find that Estimize forecasts are incrementally useful in forecasting earnings and measuring the market's expectations of earnings. Our results are stronger when the number of Estimize contributors is larger, consistent with the benefits of crowdsourcing increasing with the size of the crowd. Finally, Estimize consensus revisions generate significant two-day size-adjusted returns. The combined evidence suggests that crowdsourced forecasts are a useful supplementary source of information in capital markets.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::677fbea04b3dd815b01be3b471620f26 https://doi.org/10.1111/1475-679x.12121 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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