Bryan R. Routledge

Associate Professor of Finance




GSIA - Tepper School of Business - Room 305



University of British Columbia - Ph D - 1996
Queen's University at Kingston - BA - 1987


asset pricing, natural language processing, commodities and commodity pricing, macroeconomics, finance, corporate finance, preference theory


Bryan Routledge is an Associate Professor of Finance at the Tepper School of Business, Carnegie Mellon University. He received his Ph.D. from the University of British Columbia in 1996 and a Bachelor of Commerce from Queens University in 1987. His research focuses on a broad selection of topics in finance. Current research applies quantitative text analysis and natural language processing to economic and financial research questions (e.g, how management discussion and analysis conveys risk, and how Twitter can track public opinion). Other recent research investigates the quantitative properties of asset prices and macroeconomics such as the positive correlation of asset returns with future economic growth, understanding the connection between risk attitudes and asset pricing dynamics, and the risk and return properties of oil prices. He has taught a wide variety of courses at the Tepper School in many of their programs. Current teaching includes the introductory Finance class to MBA students, Financial Economics for MSCF students, and a more specialized class called "Alpha: Implementing Quantitative Strategies." He is also a frequent teacher in the Tepper Schools Executive Education Programs in finance.


  • The Utility of Text: The Case of Amicus Briefs and the Supreme Court.

    (author(s): Yanchuan Sim, Bryan Routledge, Noah Smith) Proceedings of the AAAI Conference on Artificial Intelligence , 2015

  • Large Scale Insider Trading Analysis: Patterns and Discoveries

    (author(s): Acar Tamersoy, Bo Xie, Stephen Lenkey, Bryan Routledge, Duen Horng Chau, Shamkant Navathe) Social Network Analysis and Mining

  • Narrative framing of consumer sentiment in online restaurant reviews

    (author(s): Dan Jurafsky, Victor Chahuneau, Bryan Routledge, Noah Smith) First Monday

  • Dynamic Models of Streaming Text.

    (author(s): Dani Yogatama, Chomg Wang, Bryan Routledge, Noah Smith, Eric Xing) Transactions of the Association for Computational Linguistics

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  • Predicting Merger Targets and Acquirers from Text

    (author(s): Bryan Routledge, Stefano Sacchetto, Noah Smith)

  • Extracting a Corporate Social Network from Text

    (author(s): Bill McDowell, Lingpeng Kong, Bryan Routledge, Noah Smith)

  • Extracting a Corporate Social Network from Text, Technical Report

    (author(s): Bill McDowell, Lingpeng Kong, Bryan Routledge, Noah Smith) 2013

  • Modest versus Ostentatious Language for Product Differentiation: A Case Study in Restaurant Menus

    (author(s): Dan Jurafsky, Victor Chahuneau, Bryan Routledge, Noah Smith)

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  • International Institute of Forecasters - SAS/IIF Grant to Promote Research on Forecasting (2013)


  • Weil Prize Selection Committee, Committee Member, (2014 - )
  • Weil Prize Selection Committee, Committee Member, (2013 - )
  • Base Camp Presentation for Finance "vertical" day, Guest Speaker, (2013 - )
  • Welcome Weekend Speaker, Guest Speaker, Presentation to potential MBA students, (2013 - )
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  • Canadian Institute of Chartered Accountants, Member, (2002 - )


  • Tepper Executive Education (January 2012 -)


  • Officer: Secretary/Treasurer , Western Finance Association (September 2013 -)
  • Associate Editor, Critical Financial Review (January 2010 -)
  • Associate Editor, Journal of Finance and Quantitative Analysis (January 2004 -)
  • Associate Editor, Management Science (January 2001 - 2009)


  • Seminar in Finance I (47721)
    2015 Mini 3 Section: A
    2009 Mini 3 Section: A
    2008 Mini 3 Section: A
    2007 Mini 3 Section: A
  • Venture Capital and Private Equity (45824)
    2015 Mini 3 Section: A
  • MSCF Finance (46972)
    2014 Mini 1 Section: I, M
    2013 Mini 1 Section: I
  • Asset Management (46979)
    2014 Mini 2 Section: I, M
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Bryan Routledge