Daniel Taylor

Daniel Taylor
  • Professor of Accounting

Contact Information

  • office Address:

    1312 Steinberg Hall-Dietrich Hall
    3620 Locust Walk
    Philadelphia, PA 19104-6365

Research Interests: opportunistic/fraudulent reporting, insider trading, regulation

Links: CV, Personal Website, Forensic Analytics Lab

Overview

Daniel Taylor is the Arthur Andersen Chaired Professor at The Wharton School, and director of the Wharton Forensic Analytics Lab. He is an award-winning researcher and teacher with extensive expertise on corporate disclosures, insider trading, and fraud prediction. He has published extensively on these topics in leading academic journals; led seminars at dozens of top business schools across the globe; and won numerous academic and industry awards.

Prof. Taylor’s research is relevant to practitioners and regulators seeking to understand, detect, and deter, opportunistic and illicit activity in financial markets. His research frequently appears in the business media, and has been cited in rules and regulations promulgated by the SEC. His research on insider trading was the impetus behind the SEC’s decision to require electronic reporting of Form 144 filings, and to require cooling off periods and disclosures related to Rule 10B5-1 trading plans. His work inspired the Holding Foreign Insiders Accountable Act, and has informed multiple investigations by enforcement authorities.

Prof. Taylor has provided consulting services related to best practices in corporate disclosure, 10B5-1 trading plans, statistical analysis of trading activity, market surveillance, and fraud prediction, and he has co-developed and licensed intellectual property related to parsing SEC filings. His consulting clients include the DoJ, hedge funds, plaintiff and defense firms, and a Big 4 auditor.

Professor Taylor teaches a cutting-edge undergraduate course–Forensic Analytics–that applies state-of-the-art analytics to SEC filings, and teaches a doctoral seminar on data analysis. His doctoral students have gone on to become faculty at a variety of leading business schools, including Stanford, MIT, and Chicago. Professor Taylor received his bachelor’s degree from University of Delaware, his master’s from Duke University, and his PhD from Stanford University.

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Research

  • Bradford Lynch, Daniel Taylor, Robert J. Jackson, Jr. Late Filings and Insider Trading: Broken Windows or Opportunism?.

    Abstract: The Securities Act of 1934 requires corporate insiders to publicly disclose transactions in their company’s stock within two business days on Form 4. Despite this bright-line legal requirement, we identify more than 100,000 transactions, involving over $122 billion that were disclosed late. The conventional wisdom in the legal community is that these late filings are unintentional clerical errors and that it is a waste of resources to police these “broken windows.” Perhaps as a result of this, the SEC has rarely enforced the filing deadline. We examine the phenomenon of late Form 4 filings and associated lack of enforcement. In contrast to the conventional wisdom, we find that trades reported in late filings are highly opportunistic––they earn significant abnormal returns relative to trades in timely filings and appear intended to conceal trading activity prior to material corporate events. Our evidence suggests that insiders may be exploiting the SEC’s lack of enforcement of filing deadlines, resulting in unusually opportunistic insider trading.

  • Bradford Lynch, Daniel Taylor, Robert J. Jackson, Jr. Holding Foreign Insiders Accountable.

    Abstract: While corporate insiders at US-listed, US-domiciled companies must disclose their stock sales electronically within two business days on Form 4, the SEC has exempted insiders at US-listed, foreign-domiciled companies from this requirement (e.g., Astra Zeneca, Alibaba). Instead, these “foreign insiders” report their sales on a paper form mail-filed with the SEC. Using a unique dataset compiled from digitized versions of thousands of paper forms, we examine the stock sales of foreign insiders and compare their trading to that of their US-counterparts. Consistent with a lack of public scrutiny facilitating opportunism, we show that foreign insiders’ stock sales are highly opportunistic, and that opportunistic trading is concentrated in companies that are domiciled in non-extradition countries beyond the reach of US legal authorities: specifically, Russia and China. The average stock sale by foreign insiders affiliated with companies domiciled in these countries is over four times larger than that of US insiders and occurs prior to stock price declines of at least –18%. In our sample, we estimate that insiders at these companies have traded to avoid losses of over $9 billion. Collectively, we interpret our results as suggesting that corporate insiders associated with Chinese and Russian companies listed on US exchanges trade in a highly opportunistic and abusive manner; and that the SEC has unwittingly enabled such trading by exempting these insiders from Form 4 reporting requirements––preventing the market from scrutinizing and disciplining their trading behavior.

  • Brian Bushee, Daniel Taylor, Christina Zhu (Working), The Dark Side of Investor Conferences: Evidence of Managerial Opportunism.

    Abstract: While the shareholder benefits of investor conferences are well-documented, evidence on whether these conferences facilitate managerial opportunism is scarce. In this paper, we examine whether managers opportunistically exploit heightened attention around the conference to “hype” the stock. We find that managers increase the quantity of voluntary disclosure leading up to the conference; that these disclosures are more positive in tone and increase prices to a greater extent than post-conference disclosures; and that these disclosures are more pronounced when insiders sell their shares immediately prior to the conference. In circumstances where pre-conference disclosures coincide with pre-conference insider selling, we find evidence of a significant return reversal––large positive returns before the conference, and large negative returns after the conference––and that the firm is more likely to be named in a securities class action lawsuit. Collectively, our findings are consistent with some managers hyping the stock prior to the conference.

  • Jung Min Kim, Daniel Taylor, Robert E. Verrecchia (2021), Voluntary Disclosure when Private Information and Disclosure Costs are Jointly Determined (Review of Accounting Studies),.

    Abstract: Classical models of voluntary disclosure feature two economic forces: the existence of an adverse selection problem (e.g., a manager possesses some private information) and the cost of ameliorating the problem (e.g., costs associated with disclosure). Traditionally these forces are modelled independently. In this paper, we use a simple model to motivate empirical predictions in a setting where these forces are jointly determined––where greater adverse selection entails greater costs of disclosure. We show that joint determination of these forces generates a pronounced non-linearity in the probability of voluntary disclosure. We find that this non-linearity is empirically descriptive of multiple measures of voluntary disclosure in two distinct empirical settings that are commonly thought to feature both private information and proprietary costs: capital investments and sales to major customers.

  • Bradford Lynch and Daniel Taylor, The Information Content of Corporate Websites.

    Abstract: In 2008, the SEC published guidance allowing firms to use corporate websites as an alternative disclosure channel to EDGAR. While the information content and market reaction to traditional disclosure channels such as EDGAR filings and press releases are well-documented, evidence on corporate websites as a disclosure channel is scarce. In this paper, we shed light on corporate websites as an important but unregulated source of information to investors. We begin by developing a novel measure of corporate website content. We then identify large changes in corporate websites content that do not occur in close proximity to EDGAR filings and press releases and examine what effect, if any, these standalone changes in website content have on markets, and information production by analysts and journalists. Using standard event study methods, we find that standalone changes in the corporate websites provide significant value-relevant information to investors, reduce information asymmetry, and precede significant revisions in analyst forecasts and increases in media coverage. Collectively, our findings indicate that corporate websites are an economically significant source of new information to markets and information intermediaries that supplements traditional disclosure channels considered in prior literature.

  • Jung Min Kim, Daniel Taylor, Jared N Jennings, Joshua A. Lee, Measurement Error and Bias in Causal Models in Accounting Research.

    Abstract: Measurement error biases against [finding results]” is an often-repeated phrase used to dismiss validity threats arising from measurement error. As a general rule, this phrase is false. We provide examples of commonly encountered circumstances where the variable of interest is exogenous––the gold standard for causal inference––but where measurement error in empirical proxies nonetheless bias in favor of rejecting a true null hypothesis. In addition, we show that the common practice of including high-dimensional fixed effects, specifically firm fixed effects, can exacerbate this bias and lead researchers to spuriously estimate a causal effect when none exists. Finally, we show that measurement error pervades the accounting literature, and illustrate the effect of measurement error on causal inferences in a popular quasi-natural experimental setting where we can observe the measurement error in the treatment variable. We encourage researchers to triangulate inferences across multiple empirical proxies and to report results from specifications with and without high-dimensional fixed effects.

  • Terrence Blackburne, John Kepler, Phillip Quinn, Daniel Taylor (Working), Undisclosed SEC Investigations.

    Abstract: One of the hallmarks of the SEC’s investigative process is that it is shrouded in secrecy––only the SEC staff, high-level managers of the company being investigated, and outside counsel are typically aware of active investigations. We obtain novel data on the targets of all SEC investigations closed between 2000 and 2017––data that was heretofore non-public––and find that such investigations portend economically meaningful declines in firm performance. Despite the materiality of these investigations, firms are not required to disclose them, and only 19% of targeted firms initially disclose the investigation. We examine whether corporate insiders exploit the undisclosed nature of these investigations for personal gain. We find a pronounced spike in insider trading at the outset of the investigation; that the increase in trading is attributable to corporate officers but not to independent directors; and that abnormal trading activity appears highly opportunistic and earns significant abnormal returns. Our results suggest that SEC investigations are often material non-public events, and that insiders trade based on private information about these events.

  • Salman Arif, John Kepler, Joseph Schroeder, Daniel Taylor (Working), Audit Process, Private Information, and Insider Trading.

  • Mirko S. Heinle, Delphine Samuels, Daniel Taylor (Working), Proprietary costs and disclosure substitution: Theory and empirical evidence.

    Abstract: A growing empirical literature suggests managers view mandatory and voluntary disclosure as substitutes. We formalize the intuition in this literature in the context of a simple model of mandatory and voluntary disclosure. We use our model to highlight the limitations of existing empirical intuition, and discuss conditions under which mandatory and voluntary disclosure are (and are not) substitutes. We consider a setting where mandatory disclosure is a disaggregated disclosure (e.g., a financial statement), voluntary disclosure is an aggregate disclosure (e.g., an earnings forecast), and the costs of voluntary and mandatory disclosure are distinct. In this setting, we show that concerns about the proprietary cost of mandatory disclosure motivate managers to reduce the quality of mandatory disclosure and substitute voluntary disclosure. We test our predictions using a comprehensive sample of mandatory disclosures where the SEC allows the firm to redact information that would otherwise jeopardize its competitive position. Consistent with our predictions, we find strong evidence that redacted mandatory disclosure is associated with greater voluntary disclosure.

  • Brian Bushee, Ian Gow, Daniel Taylor (2018), Linguistic Complexity in Firm Disclosures: Obfuscation or Information?, Journal of Accounting Research.

Teaching

Introduction to Financial Accounting (ACCT1010); Predictive Analytics with Financial Disclosures (ACCT2700); Empirical Design in Accounting Research (ACCT9300)

Current Courses (Fall 2022)

  • WH1508 - Evaluating Evidence

    WH 150 provides an introduction to all stages of the research process for business topics. In the first third of the course, we discuss theory building, hypothesis development, and research design choices particularly in casual research. In the second third, we discuss data collection methods (e.g., surveys, experiments, case studies and fieldwork) and the use of archival databases. This part of the course emphasizes the interplay between research design and sampling/data collection methods. In the final third of the course, we introduce data analysis and interpretation, including methods for converting raw data into measurable constructs suited to statistical analysis.

    WH1508301 ( Syllabus )

    WH1508302 ( Syllabus )

All Courses

  • ACCT1010 - Acct & Financial Report

    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.

  • ACCT2700 - Forensic Analytics

    Recent trends in Big Data and predictive analytics are revolutionizing the way stakeholders analyze financial data. This course teaches students the hands-on skills necessary to manipulate large-scale financial databases and build predictive models useful for strategic and investment decisions. The course will cover three applications of predictive analytics: (i) forecasting future earnings, (ii) predicting accounting fraud, and (iii) detecting insider trading. The course will draw on cutting-edge academic research in each area; introduce students to the basic SQL coding skills necessary to manipulate Big Data and conduct meaningful analyses; and leverage the datasets and computing power of Wharton Research Data Services. The course is organized as a hybrid of a traditional seminar course and a computer science course. The first few classes of each unit will cover the conceptual material and source material related to each topic. The later classes in each unit will cover the technical material and programming skills needed to manipulate the respective datasets, estimate predication models, and backtest algorithms.

  • ACCT9300 - Empir Design in Acct Res

    This is an empirical research design course covering topics related to empirical methodology, causal inference, econometric analysis, and panel data approaches. At least one graduate level course in econometrics is recommended.

  • WH1508 - Evaluating Evidence

    WH 150 provides an introduction to all stages of the research process for business topics. In the first third of the course, we discuss theory building, hypothesis development, and research design choices particularly in casual research. In the second third, we discuss data collection methods (e.g., surveys, experiments, case studies and fieldwork) and the use of archival databases. This part of the course emphasizes the interplay between research design and sampling/data collection methods. In the final third of the course, we introduce data analysis and interpretation, including methods for converting raw data into measurable constructs suited to statistical analysis.

Awards and Honors

  • AICPA Notable Contribution to the Accounting Literature, 2020
  • Outstanding Paper, Jacobs Levy Center for Quantitative Financial Research, 2019
  • Best Academic Paper, Weinberg Corporate Governance Symposium, 2019
  • Morgan-Stanley Best Discussant Prize, 2017
  • Dean’s Research Grant, 2011
  • Who’s Who in Business Education, 2011

In the News

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Latest Research

Bradford Lynch, Daniel Taylor, Robert J. Jackson, Jr. Late Filings and Insider Trading: Broken Windows or Opportunism?.
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In the News

How to Hold Foreign Corporate Insiders Accountable

A Research paper co-authored by Wharton’s Daniel Taylor formed the basis for a bill in Congress that aims to level the ground on insider trading disclosures.Read More

Knowledge at Wharton - 5/31/2022
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