Tuesday, September 27, 2016
Anne M. Anderson and Paul Brockman have posted Form 13F (Mis)Filings on SSRN with the following abstract:
We examine the reliability of Form 13F filings and document the widespread presence of significant reporting errors. Even among a select group of high-profile bank holding companies, we find that filing firms frequently (1) report their holdings of securities that do not appear on the SEC’s Official List, (2) report inaccurate market prices for securities that do appear on the SEC’s Official List, and (3) file amended 13F reports that can be less accurate than the original filings. Overall, our evidence shows that the widespread reliance on 13F filings for institutional ownership figures is unwarranted.
Jonathan M. Karpoff, Allison Koester, D. Scott Lee, and Gerald S. Martin have posted Proxies and Databases in Financial Misconduct Research on SSRN with the following abstract:
An extensive accounting and finance literature examines the causes and effects of financial misreporting or misconduct based on samples drawn from four popular databases that identify restatements, securities class action lawsuits, and Securities and Exchange Commission (SEC) Accounting and Auditing Enforcement Releases (AAERs). We show, however, that the results from empirical tests can depend on which database is accessed. To examine the causes of such discrepancies, we compare the information in each database to a detailed sample of 1,243 case histories in which the SEC brought enforcement action for financial misrepresentation. These comparisons allow us to identify, measure, and estimate the economic importance of four characteristics of each database that affect inferences from empirical tests. First, these databases contain information on only the event that is used to proxy for misconduct (e.g., restatements), so they omit other relevant announcements that affect a researcher’s interpretation and use of the events. Second, the initial public revelation of financial misconduct occurs, on average, months before the initial coverage in these databases, leading to discrepancies in event study measures and pre/post comparison tests. Third, most of the events captured by these databases are unrelated to financial fraud, and efforts to cull out non-fraud events yield heterogeneous results. Fourth, the databases omit large numbers of events they were designed to capture. We show the extent to which each database is subject to these concerns and offer suggestions for researchers seeking to use these databases.
Lin William Cong and Douglas Xu have posted Rise of Factor Investing: Asset Prices, Informational Efficiency, and Security Design on SSRN with the following abstract:
We model financial innovations such as Exchange-Traded Funds (ETFs), smart beta products, and many index-based vehicles as composite securities that facilitate trading large baskets of assets and encourage factor investing. Consistent with recent empirical findings, we show composite securities lead to larger trading costs and synchronicity for illiquid assets, and lower asset-specific but higher factor information in prices, while increasing their return volatility and co-movements. Regardless of their informedness and liquidity needs, factor investors prefer the same composite security designs that entail liquid and representative assets. We also discuss how transparency of composite security trading, distinction between composite bundles and derivatives, and endogenous information acquisition affect pricing and security design.
Monday, September 26, 2016
The following law review articles relating to securities regulation are now available in paper format:
Brian Elzweig, Valerie Chambers & Jud Stryker, After Goeller v. United States, Can the Theft Loss Treatment Now Be Applied to Investments When Corporate Deception Is Present? 38 Campbell L. Rev. 1 (2016).
Stavros Gadinis & student Colby Mangels, Collaborative Gatekeepers, 73 Wash. & Lee L. Rev. 797 (2016).
Thomas M. Madden, Significance and the Materiality of Tautology, 10 J. Bus. & Tech. L. 217 (2015).
Thomas McGuire et al., Resolving Reverse-Payment Settlements with the Smoking Gun of Stock Price Movements, 101 Iowa L. Rev. 1581 (2016).
Seth C. Oranburg, Bridgefunding: Crowdfunding and the Market for Entrepreneurial Finance, 25 Cornell J.L. & Pub. Pol'y 397 (2015).
Lu Xu, Recent development, In re Advanced Battery Technologies, Inc.: How Independent Auditors of Chinese Reverse Merger Companies Avoid Liability in Securities Fraud Litigation, 24 Tul. J. Int'l & Comp. L. 427 (2016).
The Harvard Law School Program on Corporate Governance is currently seeking applicants for two positions:
The Harvard Law School Program on Corporate Governance invites applications for the position of Executive Director. Together with the Faculty Director and others, the Executive Director of the Program works on building, developing, and managing the full range of activities of the Program. Under the Faculty Director’s oversight, the Executive Director manages the wide range of the Program’s operations; collaborates with major corporations, law firms, investors, advisers, and other organizations; participates in developing and directing conferences and other events for the Program; and manages the administration and personnel of the program, including fellows, research assistants, and staff. The Executive Director also collaborates with constituent groups and other professionals; participates in fundraising activities; interacts with donors and visitors; and takes on other management roles within the Program as needed. The Executive Director is involved in overseeing the Program’s website and other media outreach efforts, as well as the Program’s blog, the Harvard Law School Forum on Corporate Governance and Financial Regulation.
Applications will be considered on a rolling basis. Candidates should have a J.D. or another graduate degree in law, policy, or social science, and 3+ years of experience in a relevant field of law or policy. This is a full-time term appointment. Start date is flexible. Additional information on the Executive Director position, as well as detailed instructions on how to apply, is available through ASPIRE.
The Harvard Law School Program on Corporate Governance invites applications for Post-Graduate Academic Fellows. Candidates should be interested in spending two or three years at Harvard Law School in preparation for a career in academia or policy research, and should have a J.D., LL.M. or S.J.D. from a U.S. law school (or expect to have completed most of the requirements for such a degree by the time they commence their fellowship). During the term of their appointment, Post-Graduate Academic Fellows work on research and corporate governance activities of the Program, depending on their interests and Program needs. Fellows may also work on their own research and publishing, and some former Fellows of the Program now teach in leading law schools in the U.S. and abroad.
Applications are considered on a rolling basis. Interested candidates should submit a CV, list of references, law school grades, and a writing sample and cover letter to the coordinator of the Program, Ms. Jordan Figueroa, at firstname.lastname@example.org. The cover letter should describe the candidate’s experience, reasons for seeking the position, career plans, and the kinds of Program projects and activities in which they would like to be involved. The position includes Harvard University benefits and a competitive fellowship salary. Start date is flexible.
Sunday, September 25, 2016
Donna M. Nagy has posted Beyond Dirks: Gratuitous Tipping and Insider Trading on SSRN with the following abstract:
Does a corporate insider who gratuitously shares material nonpublic information with a friend or relative — with no expectation of receiving anything in return — commit securities fraud? The Supreme Court is poised to answer that question in Salman v. United States, after steering clear of insider trading law for nearly two decades. It has been even longer still since the Court last addressed securities fraud liability relating to stock trading tips; it articulated a “personal benefit” test for joint tipper-tippee liability in 1983 in Dirks v. SEC, a decision reinforcing the “classical” theory of insider trading. In 2015, a circuit split arose as to whether gratuitous tipping constitutes a violation of the antifraud provisions in the federal securities laws, and the Court has granted certiorari in Salman to resolve that issue. This article disagrees with the Second Circuit’s finding that gratuitous tips do not result in a personal benefit and supports the Ninth Circuit’s conclusion that such tips are illegal. But in arguing that gratuitous tips satisfy the personal benefit test, this article draws from a potent combination of four post-Dirks developments in corporate and securities law: 1) the Court’s endorsement of the “misappropriation” theory in United States v. O’Hagan; 2) federal securities legislation in 1984, 1988, and 2012 that evidences Congress's support for an expansive antifraud proscription against insider trading and tipping; 3) the SEC’s decision to effectively ban the practice of selective disclosure through its adoption of Regulation FD; and 4) state court decisions that construe fiduciary disloyalty to include not only self-dealing but also other conscious actions taken by agents in bad faith. These developments should prompt the Court not only to affirm the Ninth Circuit’s decision but also to look beyond Dirks to consolidate the Court’s prior complementary theories of insider trading liability — the classical and misappropriation theories — into a new unified framework that would regard insider trading as a “fraud on contemporaneous traders.”
Arjya B. Majumdar and Umakanth Varottil have posted Regulating Equity Crowdfunding in India: Walking a Tightrope on SSRN with the following abstract:
Start-up companies face difficulties in raising finances, and the situation has intensified since the global financial crisis in 2008. As a result, crowdfunding has made its appearance as an attractive alternative capital-raising mechanism by harnessing technology (primarily the Internet) to access funding from the “crowd.”
In this chapter, we explore the core question of how should one regulate equity crowdfunding in a manner that enhances its appeal to engender the development of small and new-age businesses through accessible funding opportunities and at the same time protect investors against undue risks, such as fraud, which arise from the activity. We analyse the regulatory conundrum on equity crowdfunding by examining the legal regime for crowdfunding in India.
The rules relating to fundraising by companies in India have been considerably tightened under the Companies Act, 2013 that limits crowdfunding activity. However, the Securities and Exchange Board of India (SEBI) has issued a consultation paper that proposes a framework for ushering in crowdfunding in India. We find that the unduly onerous conditions imposed by SEBI have the effect of deterring rather than promoting the growth of crowdfunding. The existing (and proposed) legal framework in India have erred on the side of caution and sought to emphasise more on investor protection than to engender the market for crowdfunding.
Joanna Diane Caytas has posted Developing Blockchain Real-Time Clearing and Settlement in the EU, U.S., and Globally on SSRN with the following abstract:
Clearing and settlement of international securities transactions for indirectly held securities presents major challenges as the immense potential of blockchain technology creates the possibility of a tamper-proof consolidated audit trail, of almost infinitesimal transaction cost, and increased transactional velocity. While true real-time clearing and settlement will remain utopia for the foreseeable future, disruptive fintech innovations are being tested by major financial institutions around the globe as realization takes hold that critical mass is not a limiting criterion in a cloud-based blockchain world. But while technology develops virtually at the speed of IT-based innovation, banks realize the threat of losing control of payment systems and the notion of negative float is dwindling toward zero, exposing banks to additional risks and challenges to liquidity and collateral management in order to be able to make technologically possible instant payments. At the same time, the regulatory framework both in the U.S and the EU lags alarmingly behind the pace of technology as sudden institutional and supervisory concerns about Bitcoin and other cryptocurrencies have showed. While blockchain technology is not only capable of revolutionizing payments, clearing, and settlement, but indeed any form of transaction processing or verifiable vote, it raises issues of data protection, BigData processing, but also of identifying systemic payment risks. While both U.S. and EU regulators have shown valuable and highly appropriate restraint so as not to throttle innovation, regulation and oversight remain conditions precedent to broad-based use and safe application.
J.B. Heaton, Nick Polson, and Jan Hendrik Witte have posted Deep Learning for Finance: Deep Portfolios on SSRN with the following abstract:
We explore the use of deep learning hierarchical models for problems in financial prediction and classification. Financial prediction problems – such as those presented in designing and pricing securities, constructing portfolios, and risk management – often involve large data sets with complex data interactions that currently are difficult or impossible to specify in a full economic model. Applying deep learning methods to these problems can produce more useful results than standard methods in finance. In particular, deep learning can detect and exploit interactions in the data that are, at least currently, invisible to any existing financial economic theory.
Jack Sarkissian has posted Express Measurement of Market Volatility Using Ergodicity Concept on SSRN with the following abstract:
We propose a number of volatility measures that are based on ensemble averaging instead of time averaging. These measures allow fast measurement of current volatility without relying on series of past data (realized volatility) of future expectations (implied volatility). The introduced quantities are tested on a model market and are then related to actual market data. They display very adequate behavior and are great complement to traditional volatility measures in analytics, securities valuation, risk management and portfolio management.