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Terrence Hendershott

Terrence Hendershott

· Professor | Willis H. Booth Chair in Banking and Finance II

University of California, Berkeley · Fintech

Active 2000–2025

h-index47
Citations13.1k
Papers11119 last 5y
Funding$375k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Terrence Hendershott is the Willis H. Booth Chair in Banking and Finance at UC Berkeley Haas School of Business and serves as the Faculty Director of the Master of Financial Engineering Program. His work spans a range of financial instruments trading on exchanges and over-the-counter in the U.S. and internationally. He is an expert on the structure, design, and regulation of financial markets and investigates how market participants such as market makers, high-frequency traders, and institutional investors influence price discovery and liquidity. His research also focuses on the competition between electronic and traditional markets and the role of information technology in those markets. Hendershott has chaired the NASDAQ Economic Advisory Board and served as a visiting economist at the New York Stock Exchange. His numerous honors include best paper awards from the Review of Financial Studies and the Financial Review, as well as awards from NYSE and NASDAQ for work on equity trading and market microstructure. Since 2001, he has held various positions at Haas, including faculty director and endowed chair, and has been recognized for his contributions to understanding market microstructure, electronic trading, and financial market regulation.

Research topics

  • Computer Science
  • Econometrics
  • Statistics
  • Economics
  • Mathematics
  • Computer Security
  • Financial economics
  • Monetary economics
  • Business
  • Finance

Selected publications

  • Price Discovery without Trading: Evidence from Limit Orders

    The Journal of Finance · 2019-03-19 · 257 citations

    article

    ABSTRACT We analyze the contribution to price discovery of market and limit orders by high‐frequency traders (HFTs) and non‐HFTs. While market orders have a larger individual price impact, limit orders are far more numerous. This results in price discovery occurring predominantly through limit orders. HFTs submit the bulk of limit orders and these limit orders provide most of the price discovery. Submissions of limit orders and their contribution to price discovery fall with volatility due to ch…

  • FinTech as a Game Changer: Overview of Research Frontiers

    Information Systems Research · 2021 · 200 citations

    1st authorCorresponding

    Technologies have spawned finance innovations since the early days of computer applications in businesses, most recently reaching the stage of disruptive innovations, such as mobile payments, cryptocurrencies, and digitization of business assets. This has led to the emerging field called financial technology or simply FinTech. In this editorial review, we first provide an overview on relevant technological, pedagogical, and managerial issues pertaining to FinTech teaching and research, with a fo…

  • Asset pricing: A tale of night and day

    Journal of Financial Economics · 2020 · 140 citations

    1st authorCorresponding
  • Relationship Trading in Over‐the‐Counter Markets

    The Journal of Finance · 2019-11-15 · 135 citations

    article1st authorCorresponding

    ABSTRACT We examine the network of trading relationships between insurers and dealers in the over‐the‐counter (OTC) corporate bond market. Regulatory data show that one‐third of insurers use a single dealer, whereas other insurers have large dealer networks. Execution prices are nonmonotone in network size, initially declining with more dealers but increasing once networks exceed 20 dealers. A model of decentralized trade in which insurers trade off the benefits of repeat business and faster exe…

  • Nonstandard Errors

    The Journal of Finance · 2024 · 85 citations

    ABSTRACT In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible…

Recent grants

Frequent coauthors

  • Charles M. Jones

    49 shared
  • Carole Comerton‐Forde

    University of Melbourne

    46 shared
  • Pamela C. Moulton

    43 shared
  • Mark S. Seasholes

    William Carey University

    39 shared
  • Norman Schürhoff

    Swiss Finance Institute

    21 shared
  • Michael J. Barclay

    University of Rochester

    20 shared
  • Ryan Riordan

    19 shared
  • Albert J. Menkveld

    Vrije Universiteit Amsterdam

    18 shared

Education

  • Ph.D., Economics

    University of California, Berkeley

    1985
  • M.S., Economics

    University of California, Berkeley

    1981
  • B.A., Economics

    University of California, Los Angeles

    1978

Awards & honors

  • Michael J. Brennan Best Paper Award (2014)
  • Financial Review Outstanding Publication Award (2014)
  • Philip Brown Prize (2013)
  • New York Stock Exchange Euronext Award (2001, 2008)
  • Nasdaq Award for best paper on market microstructure (2007)

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