Nonstandard Errors

The Journal of Finance · 2024 · 85 citations

• Computer Science
• Econometrics
• Statistics

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 or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

Distributed Ledger Technology and the Securities Markets of the Future: A Stakeholder Survey

Columbia Business Law Review · 2022 · 2 citations

• Business
• Computer Security
• Computer Science

This Article evaluates the implications of distributed ledger technology (DLT) for the securities markets of the future and their regulation. DLT is an integral part of the larger revolution in computing, communication and data storage capacity that has transformed securities markets over the last few decades and promises further radical change in the years to come. The potential of DLT, if it can be realized, could improve the functioning of our securities markets while at the same time sharply reducing costs. Based on an interview survey of about 100 persons who play prominent roles in actually making these markets work or in regulating them, this Article reports on the most important topics and themes that have emerged from the wide range of interviewees’ opinions about the extent to which DLT will affect the future of securities markets and their regulation. A significant number saw the potential for DLT to transform securities markets and market structure, from the possibility of stock trading on DLT to the potential impact on intermediaries, the ordinary retail investor, and on preventing wrongdoing in the stock market. However, key questions remain about implementation and the appetite for making DLT-based changes among both market participants and regulators.

A Report by the Ad Hoc Academic Committee on Equity and Options Market Structure Conditions in Early 2021

SSRN Electronic Journal · 2022 · 7 citations

• Political Science
• Business
• Medicine

Entrepreneurial Ability, Venture Investments, and Risk Sharing*

Routledge eBooks · 2022 · 57 citations

• Business
• Finance
• Economics

A number of issues that relate to the desirability and implications of new venture financing are examined within a principal-agent framework that captures the essence of the relationship between entrepreneurs and venture capitalists. The model suggests: (I) As long as the skill levels of entrepreneurs are common knowledge, all will choose to involve venture capital investors, since the risk sharing provided by outside participation dominates the agency relationship that is created. (2) The less able entrepreneurs will choose to involve venture capitalists, whereas the more profitable ventures will be developed without external participation because of the adverse selection problem associated with asymmetric information. (3) If a costly signal is available that conveys the entrepreneur’s ability, some entrepreneurs will invest in such a signal and then sell to investors; these entrepreneurs, however, need not be the more able ones. The implications for new venture financing of these and other findings are discussed and illustrated by example. (ENTREPRENEURSHIP; VENTURE CAPITAL, ADVERSE SELECTION, MORAL HAZARD; RISK REDUCTION)

Spoofing and its Regulation

Columbia Business Law Review · 2022 · 8 citations

• Political Science
• Computer Science
• Law and economics

Nearly a century after the United States enacted its first securities laws, urgent questions remain as to the scope of manipulation law: whether manipulation is possible in principle, and if so, how the law should respond in practice. Sharp disagreement among courts, economists, and legal scholars as to whether trading or quoting activity constitutes illegal manipulation has led to a legal framework that lacks precision and cogency. Moreover, the poorly articulated normative basis for court rulings has resulted in enforcement that is both under-inclusive and over-inclusive in ways that do a poor job of discouraging socially harmful transactions and enabling socially beneficial ones. This Article seeks to clarify this confusion. Drawing on microstructure and financial economics, this Article offers a new understanding of a common kind of quote-driven manipulation, often referred to as “spoofing.” By employing an analytical and normative framework developed previously by two of the authors in assessing another major form of manipulation, trade-driven manipulation, this Article assesses the impact of spoofing on what occurs in the securities markets and carefully evaluates its effects on social welfare and economic efficiency. The result is a new understanding of quote-based manipulation that helps resolve essential questions in manipulation law and provides guidance for future regulation and enforcement.