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Big Data: Long-Term Implications for Financial Markets and Firms.

An NBER conference on Big Data: Long-Term Implications for Financial Markets and Firms took place March 8 in Cambridge. Itay Goldstein of the University of Pennsylvania, Research Associate Chester S. Spatt of Carnegie Mellon University, and Faculty Research Fellow Mao Ye of the University of Illinois at Urbana-Champaign organized the meeting, which was supported by the National Science Foundation in conjunction with the The Review of Financial Studies. These researchers' papers were presented and discussed:

* Zheng Tracy Ke, Harvard University; Bryan T. Kelly, Yale University and NBER; and Dacheng Xiu, University of Chicago, "Predicting Returns with Text Data"

* Amber Anand, Syracuse University; Mehrdad Samadi and Kumar Venkataraman, Southern Methodist University; Jonathan Sokobin, Financial Industry Regulatory Authority, "Institutional Order Handling and Broker-Affiliated Trading Venues"

* Michael Gofman, University of Rochester; Sajjad Jafri, Queen's University; and James T. Chapman, Bank of Canada, "High-Frequency Analysis of Financial Stability"

* David Easley, Cornell University; Marcos Lopez de Prado, AQR Capital Management; Maureen O'Hara, Cornell University; and Zhibai Zhang, NYU Tandon, "Microstructure in the Machine Age"

* Jura Liaukonyte, Cornell University, and Alminas Zaldokas, Hong Kong University of Science and Technology, "Background Noise? TV Advertising Affects Real Time Investor Behavior"

* Hedi Benamar and Clara Vega, Federal Reserve Board, and Thierry Foucault, HEC Paris School of Management, "Demand for Information, Uncertainty, and the Response of U.S. Treasury Securities to News"

* Robert P. Bartlett III, Richard Stanton, and Nancy Wallace, University of California, Berkeley, and Adair Morse, University of California, Berkeley and NBER, "Consumer-Lending Discrimination in the FinTech Era"

* Isil Erel, Ohio State University; Lea H. Stern, University of Washington; Chenhao Tan, University of Colorado Boulder; and Michael S. Weisbach, Ohio State University and NBER, "Selecting Directors Using Machine Learning" (NBER Working Paper No. 24435)

* Bo Cowgill, Columbia University, and Eric Zitzewitz, Dartmouth College and NBER, "Stock Compensation and Employee Attention"

Summaries of these papers are at www.nber.org/conferences/2019/BDFMs19/summary.html

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Title Annotation:Conference
Publication:NBER Reporter
Date:Mar 1, 2019
Words:316
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