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Τίτλος: Does Algorithmic Trading Affect Analyst Research Production?
Συγγραφείς: Kopita, Anastasia 
Karamanou, Irene 
Panayides, Marios 
Bilinski, Pawel 
Major Field of Science: Social Sciences
Field Category: Economics and Business
Λέξεις-κλειδιά: Algorithmic trading;Analyst coverage;Earnings forecasts;Stock recommendations
Ημερομηνία Έκδοσης: 27-Μαΐ-2021
Πηγή: European Accounting Association Annual Congress, 2021
Conference: European Accounting Association Annual Congress 
Περίληψη: We document a causal negative relationship between algorithmic trading (AT) and analyst research production, as captured by a decreased frequency of earnings forecasts and stock recommendations and lower analyst coverage. This is consistent with AT increasing the speed of price discovery, reducing the profitability of trades on analyst research by non-algorithmic traders and, consequently, their demand for analyst investment advice. Supporting evidence shows that the effect of AT on analyst research production is stronger for stock recommendations, which institutions follow primarily for investment decisions, and for forecasts issued before earnings announcements when analysts’ information discovery dominates the information interpretation role. We also find a negative relationship between AT and investment-focused institutional investors such as transient and non-monitoring investors. Our analysis demonstrates that AT can have long-lasting consequences on capital markets, beyond microstructure effects, through its negative effect on firm’s information environment.
URI: https://hdl.handle.net/20.500.14279/25424
Type: Conference Papers
Affiliation: University of Cyprus 
Bayes Business School 
Cyprus University of Technology 
Warwick University 
Εμφανίζεται στις συλλογές:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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