Christina Zhu

Christina Zhu
  • Assistant Professor of Accounting

Contact Information

  • office Address:

    1320 Steinberg Hall - Dietrich Hall
    3620 Locust Walk
    Philadelphia, PA 19104

Links: CV


Professor Zhu’s primary research interest is empirical financial accounting. The underlying theme of her work is that costly information acquisition has economic consequences. Her research studies different elements of the feedback loop between investors’ information acquisition costs, stock price efficiency, and managers’ incentives and actions.

Professor Zhu received her Ph.D. in Business Administration (Accounting) from Stanford University and a B.A. in Economics and B.S. in Mathematics from Stanford University. Prior to pursuing her Ph.D. degree, she was an investment banking analyst at Perella Weinberg Partners.

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  • Alan Kwan and Christina Zhu (Working), Does Context Matter? Evidence from Internet Research Activity by Sophisticated Investors.

    Abstract: Using a unique dataset of internet research on business media sites matched to the identities of investors, we argue that broadly available media content can help sophisticated investors generate private information. Prior work finds that adverse selection increases at earnings announcements because some traders make superior assessments of firm value based on the disclosure. We find a positive relation between sophisticated investors’ pre-earnings announcement gathering of industry-relevant, “contextual” information and illiquidity at the time of the announcement, suggesting this specific source of public information provides some investors with a comparative advantage in interpreting earnings announcements.

  • Ed deHaan, Yang Song, Chloe Xie, Christina Zhu (Working), Disclosure Obfuscation in Mutual Funds.

    Abstract: Mutual funds hold 31% of the U.S. equity market and comprise 61% of retirement savings, yet retail investors consistently make poor choices when selecting funds. Theory suggests that poor choices are partially due to mutual fund managers creating unnecessarily complex disclosures to keep investors uninformed and obfuscate poor performance. An empirical challenge in investigating this “disclosure obfuscation” theory is isolating manipulated complexity from complexity arising from inherent differences across funds. We examine disclosure obfuscation among S&P 500 index funds, which have largely the same regulations, risks, and gross returns but can charge widely different fees. Using bespoke measures designed specifically for mutual funds, we find evidence consistent with funds attempting to obfuscate high fees with unnecessarily complex disclosures. Our study improves our understanding of the role of disclosure in the mutual fund market, and of how price dispersion persists among homogenous index funds. We also discuss insights for mutual fund regulation and the academic literature on corporate disclosures.

  • Charles Lee and Christina Zhu (Working), Active Funds and Bundled News.

    Abstract: We use trade-level data to examine the role of actively managed funds (AMFs) in earnings news dissemination. We find AMFs are drawn to, and participate disproportionately more in, earnings announcements (EAs) that include bundled managerial guidance. When the two pieces of news are directionally inconsistent, AMFs trade in the direction of future guidance rather than current earnings. AMFs exhibit an ability to discern, and adapt their trading to, the bias in bundled guidance. While AMF trades at EAs are generally more profitable than their non-EA trades, this result reverses when the bias in guidance is extreme. Overall, we find increased AMF trading during EAs leads to faster price adjustment. Collectively, these findings suggest AMFs are sophisticated processors of bundled earnings news, and their trading generally improves market price discovery.

  • David F. Larcker, Charles McClure, Christina Zhu (Working), Peer Group Choice and Chief Executive Officer Compensation.

    Abstract: We examine the selection of peer groups that boards of directors use when setting the level of CEO compensation. This choice is controversial because it is difficult to ascertain whether peer groups are selected to (i) attract and retain top executive talent or (ii) enable rent extraction by inappropriately increasing CEO compensation. In contrast to prior research, our analysis utilizes the degree to which the observed compensation level for the portfolio of peers is unusual relative to all potential portfolios of peers the board of directors could have reasonably selected. Using a sample of 9,247 firm-year observations from 2008 to 2014, we estimate that roughly 39% of board of directors’ choices appear to be associated with rent extraction, whereas the remaining 61% appear to be associated with attracting and retaining high-quality CEO talent. Relative to firms that appear to select peers for aspirational labor market reasons, we find rent extraction firms have more structural governance concerns and negative realized governance outcomes. Over our sample period, we estimate the aggregate excess pay for rent extraction firms is approximately $8.6 billion, or approximately 30% of their total reported compensation.

  • Christina Zhu (2019), Big Data as a Governance Mechanism, Review of Financial Studies, 32 (5), pp. 2021-2061. 10.1093/rfs/hhy081

    Abstract: This study empirically investigates two effects of alternative data availability: stock price informativeness and its disciplining effect on managers’ actions. Recent computing advancements have enabled technology companies to collect real-time, granular indicators of fundamentals to sell to investment professionals. These data include consumer transactions and satellite images. The introduction of these data increases price informativeness through decreased information acquisition costs, particularly in firms in which sophisticated investors have higher incentives to uncover information. I document two effects on managers. First, managers reduce their opportunistic trading. Second, investment efficiency increases, consistent with price informativeness improving managers’ incentives to invest and divest efficiently.

  • Elizabeth Blankespoor, Ed deHaan, John Wertz, Christina Zhu (2019), Why Do Individual Investors Disregard Accounting Information? The Roles of Information Awareness and Acquisition Costs, Journal of Accounting Research, 57 (1), pp. 53-84. 10.1111/1475-679X.12248

    Abstract: Individual investors often neglect value-relevant accounting information and instead underperform by trading on technical trends. We investigate the frictions that impede individual investors’ use of accounting information, and in particular their costs of monitoring and acquiring accounting disclosures. We do so using an archival setting where individuals are presented with automated media articles that report both current earnings news and past stock returns. Although these investors have earnings information readily available, we find no evidence that their trades incorporate earnings news. Instead we find that they trade in response to the trailing stock returns presented in the articles. Our study raises questions about the likely efficacy of regulations that aim to aid less sophisticated investors by increasing their awareness of, and access to, accounting information.

  • Elizabeth Blankespoor, Ed deHaan, Christina Zhu (2018), Capital Market Effects of Media Synthesis and Dissemination: Evidence from Robo-Journalism, Review of Accounting Studies, 23 (1), pp. 1-36. 10.1007/S11142-017-9422-2

    Abstract: In 2014, the Associated Press (AP) began using algorithms to write articles about firms’ earnings announcements. These Brobo-journalism^ articles synthesize information from firms’ press releases, analyst reports, and stock performance and are widely disseminated by major news outlets a few hours after the earnings release. The articles are available for thousands of firms on a quarterly basis, many of which previously received little or no media attention. We use AP’s staggered implementation of robo-journalism to examine the effects of media synthesis and dissemination, in a setting where the articles are devoid of private information and are largely exogenous to the firm’s earnings news and disclosure choices. We find compelling evidence that automated articles increase firms’trading volume and liquidity. The effects are most likely driven by retail traders.We find no evidence that the articles improve or impede the speed of price discovery. Our study provides novel evidence on the impact of pure synthesis and dissemination of public information in capital markets and initial insights into the implications of automated journalism for market efficiency.


Past Courses


    This course is an introduction to the basic concepts and standards underlying financial accounting systems. Several important concepts will be studied in detail, including: revenue recognition, inventory, long-lived assets, present value, and long term liabilities. The course emphasizes the construction of the basic financial accounting statements - the income statement, balance sheet, and cash flow statement - as well as their interpretation.


    This is theory course covering topics in agency theory, disclosure theory, and incentive design.

In the News

Knowledge @ Wharton


Adjusted Intraperiod Timeliness (Adjusted IPT): a measure of speed of price discovery that penalizes for inefficient overreaction.

Please see Github repository:

The simpler Adjusted IPT file contains a SAS macro to calculate the simpler Adjusted IPT measure, as implemented in “Capital Market Effects of Media Synthesis and Dissemination: Evidence from Robo-Journalism,” assumes that the daily return accumulation is immediately at open, while the more complex Adjusted IPT measure assumes even return accumulation over a given day. The Adjusted IPT file contains a SAS macro to calculate IPT (without the adjustment) and (the more complex) Adjusted IPT. For more details on the two different assumptions, please see the Internet Appendix.


In the News

How Big Data Can Inform Investment Decisions

Investors and managers need more than just reams of information to make good decisions -- they need to know which data are important and how to use them, Wharton research finds.

Knowledge @ Wharton - 2019/04/30
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