Research

My main research interests are in information economics, market microstructure, cybersecurity in finance, big data and machine learning applications in finance.

My papers are available online on SSRN.

Publications

Inverted Fee Structures, Tick Size, and Market Quality

Journal of Financial Economics Volume 134, Issue 1, 2019, Pages 141-164

With Carole Comerton-Forde and Zhuo Zhong

[JFE] [SSRN] [Online Appendix]

Award: Best Paper on Market Microstructure Award, NFA 2017

Shaping Expectations and Coordinating Attention: The Unintended Consequences of FOMC Press Conferences

Journal of Financial and Quantitative Analysis Volume 54, Issue 6, 2019, Pages 2327–2353

With Oliver Boguth and Charles Martineau

[JFQA] [SSRN] [Internet Appendix]

Award: Best Paper on Financial Institutions and Markets Award, 7th Financial Markets and Corporate Governance Conference (2016)

Media:

The Rise of Passive Investing and Index-linked Comovement

North American Journal of Economics and Finance Volume 51, 101059

[NAJEF] [SSRN] [Online Appendix]

Pre-PhD Publications

Using copulas to model price dependence in energy markets

Energy Risk, 2008 with Christian Genest and Michel Gendron

[CiteSeerX]

Visible and infrared imagery for surveillance applications: software and hardware considerations

Quantitative InfraRed Thermography Journal, 2007 with Amar El-Maadi, Louis St-Laurent, Hélène Torresan, Benoit Turgeon, Donald Prévost, Patrick Hébert, Denis Laurendeau, Benoit Ricard and Xavier Maldague

[Taylor & Francis]

Working Papers

Price Revelation from Insider Trading: Evidence from Hacked Earnings News

Revise and resubmit at Journal of Financial Economics

With Pat Akey and Charles Martineau

[Available on SSRN]

From 2010-2015, a group of traders illegally accessed earnings information hours before their public release by hacking several major newswire services. We use their informed trading as a natural experiment to investigate how efficiently markets incorporate private information in trades. 15% of a firm’s earnings surprise was incorporated into its stock price prior to its public release, when the hackers were trading. Their trading activity sharply increased order flow, causing liquidity providers to charge higher spreads, consistent with classical models of market microstructure. The increase in spreads was large enough to reduce the profitability of uniformed trades, suggesting that informed trading can have adverse effects on financial markets.

Media:

How is Earnings News Transmitted to Stock Prices?

Revise and resubmit at Journal of Accounting Research

With Charles Martineau

[SSRN]

Most corporate news occurs in the after-hours market, a very illiquid trading environment. We examine the relationship between liquidity and price discovery around after-hours earnings announcements. Prices reflect earnings surprises through changes in quotes rather than through trades. Following announcements, ask (bid) prices adjust quickly to positive (negative) surprises while bid (ask) prices are slower to adjust. Returns computed from trade prices underestimate the speed and magnitude of price reactions following announcements relative to midquote returns. These findings emphasize the importance of using quotes and not trade prices when studying price discovery in the after-hours market. This is especially crucial when there are confounding events, which we illustrate using analyst recommendation revisions.

Double Bonus? Implicit Incentives for Money Managers with Explicit incentives

With Juan Sotes-Paladino

[SSRN]

We use a unique dataset of European performance-fee mutual funds to examine the interaction between explicit incentives (performance fees) and implicit incentives (fund flows) of asset managers. Funds with performance fees can face substantially steeper implicit incentives compared to non-performance-fee funds. Among performance-fee funds, investors’ flows depend on the performance fee level and tend to attenuate the asymmetry in the total pay for performance of higher-fee funds. Thus, the investor preferences that we elicit favor performance-sensitive but not necessarily asymmetric compensation schedules for fund companies. Our results shed new light on several aspects of the contracting problem in asset delegation.

Do Mutual Fund Managers Adjust NAV for Stale Prices?

[SSRN]

Mutual fund returns are predictable when the Net Asset Value is computed from prices that do not reflect all available information. This problem was brought to the public eye with the late trading and market timing scandal of 2003, which led to SEC intervention in 2004. Since these events, mutual fund managers have been more active in adjusting NAV, reducing predictability by about half. The simple trading strategy I present yields annual returns of 33% from 2001 to 2004 and 16% from 2005 to 2010. Even after accounting for trading restrictions in mutual funds, an arbitrager could earn annual returns of 2.73% from 2005 to 2010, suggesting the problem is not fully resolved. The main methodological contribution of this paper is to develop a filtering approach based on a state-space model that embeds the fund manager problem, thus accounting for unobserved actions of fund managers. I also show that predictability increases significantly when information sources suggested by prior literature, such as index and futures returns, are supplemented by premiums on related exchange traded funds).

Work in Progress

Fake Volume in Cryptocurrency Markets

With Steven Riddiough and Zhuo Zhong