In the Insider Trading & Market Manipulation Literature Watch, members of our Finance Practice provide summaries and links to published research about insider trading and market manipulation. The team will provide an update each quarter.
Insider Trading
Information leakages, distribution of profits from informed trading, and last mover advantage
I propose a model à la Kyle, where insiders trade via brokers who then relay the information about the insiders’ trades to their other clients, who, in turn, play the role of followers. A key feature of the model is that the insiders and the followers trade simultaneously, despite the sequential nature of the decision-making mechanism. If the followers receive a signal about the insiders’ decisions with minimal noise, and the number of insiders does not exceed the number of followers, then the followers capture nearly all the profits, leaving the insiders with a negligible portion. My model explains a recent empirical finding that insiders’ dollar profits may be quite modest.
Pankratov, Andrey, Information leakages, distribution of profits from informed trading, and last mover advantage (September 02, 2024). Available at SSRN: https://ssrn.com/abstract=4944425 or http://dx.doi.org/10.2139/ssrn.4944425
Bright Light, Dark Room: Where do Corporate Insiders Trade?
In the fragmented equity market landscape, corporate insiders may conceal high-quality information or engage in illegal activities by trading on dark markets. While existing literature extensively covers the timing and methods of insider trading, little attention is given to the specific venues utilized by corporate insiders. We analyze where corporate insiders trade and evaluate the impact of their venue choice on abnormal returns. We find that insiders are more inclined to trade on dark markets when engaging in illegal activities, but less inclined to do so when they are informed. Given insiders’ endogenous venue selection, trading on dark markets negatively impacts abnormal returns.
Hübbert, Alexander and Nordén, Lars L., Bright Light, Dark Room: Where do Corporate Insiders Trade? (September 03, 2024). Available at SSRN: https://ssrn.com/abstract=4946521 or http://dx.doi.org/10.2139/ssrn.4946521
Watching the Watchdogs: Tracking SEC Inquiries using Geolocation Data
The Securities and Exchange Commission’s investigative process remains opaque and challenging to study due to limited observability. Leveraging de-identified smartphone geolocation data, we provide new insights into the SEC’s monitoring practices by tracking SEC-associated devices that visit firm headquarters. Our findings reveal that the majority of SEC visits occur outside of formal investigations, with larger firms and those with a history of SEC enforcement actions being more frequently visited. These visits often cluster within industries. Notably, the SEC associated devices venture to firms both within and outside their own regions. On average, these visits are material, evidenced by significant stock price reactions, even in the absence of subsequent formal investigations or enforcement actions. Last, we observe a chilling effect on insider behavior around these SEC interactions; insiders are less likely to sell around visits. However, when sales do occur, insiders avoid substantial losses.
Gerken, William Christopher and Irlbeck, Steven and Painter, Marcus and Zhang, Guangli, Watching the Watchdogs: Tracking SEC Inquiries using Geolocation Data (August 30, 2024). Available at SSRN: https://ssrn.com/abstract=4941708 or http://dx.doi.org/10.2139/ssrn.4941708
Civil Insider Trading in Personal Networks
This Article, together with a predecessor companion article on criminal friends-and-family insider trading activity, is designed to provide data-driven groundwork for the study of U.S. insider trading violations involving personal—rather than business—relationships. Specifically, the Article provides a preliminary report on insider trading in personal networks based on a proprietary data set that includes information culled from eleven years of public enforcement actions in which material nonpublic information was allegedly conveyed between or among people in friendships or familial relations.
To lay a foundation for the study of insider trading in personal networks, the Article proceeds first by describing relevant aspects of insider trading doctrine and enforcement as key elements of the U.S. legal landscape relevant to a study of civil insider trading in personal networks. Next, the Article explains the methodology used for identifying and categorizing information on friends-and-family insider trading obtained from public civil enforcement actions filed between 2008 and 2018. The Article then describes that information from two key vantage points: the types of relationships represented by the participants in the alleged insider trading and the gender of those participants. The Article closes with a conclusion that offers related observations and avenues for further study.
Heminway, Joan MacLeod, Civil Insider Trading in Personal Networks (June 03, 2024). Available at SSRN: https://ssrn.com/abstract=4926127 or http://dx.doi.org/10.2139/ssrn.4926127
How Do Directors and Officers React to Insider Trading in Peer Firms?
Directors and officers increase their trading activity (probability and frequency) and the profitability of trades following published insider trades in product-market peer companies. Trading is more likely to happen in the same direction as in peers, which is consistent with a peer effect and with learning from peer trades about industrywide information. Using a sub-sample of peer trades that are most likely influenced by factors orthogonal to the focal firm, the results are consistent with the learning channel, but evidence for peer effects is limited. I find insiders’ industry knowledge to be useful to close peer firms only, and that insiders in smaller firms profit from larger firms’ information, but not vice versa.
Steiner, Christian, How Do Directors and Officers React to Insider Trading in Peer Firms? (July 31, 2024). Available at SSRN: https://ssrn.com/abstract=4938097 or http://dx.doi.org/10.2139/ssrn.4938097
Institutional Investor Cliques, Information Dissemination, and the Value of Information: Evidence from Insider Trading
We examine the dynamics of insider trading outcomes in relation to the insiders’ information environment within institutional investor networks, leveraging the Louvain method to identify the formation of investor cliques. Employing difference-in-differences methodologies, we produce evidence of information dissemination throughout these uniquely structured networks, where members are quasi-randomly selected. Our findings highlight that insider transactions within larger cliques result in lower abnormal trading profits, alongside a notable increase in trading frequency and trade size, suggesting a direct correlation between clique size and the extent of information dissemination. This also indicates the attenuation of valuable information within expansive cliques. While most existing studies rely on one dimension of commonality (e.g., personal ties, professional ties, geographic proximity) to construct the social network, we document the formation of the institutional investor groups (cliques) that exogenously connect firm-level insiders within the social network. The application of the Louvain method not only enriches our understanding of social networks’ influence on trading behaviors but also underscores the methodological significance in scrutinizing the complex web of information flow.
Zhang, Zhenyu and Du Pon, Adam W., Institutional Investor Cliques, Information Dissemination, and the Value of Information: Evidence from Insider Trading. Available at SSRN: https://ssrn.com/abstract=4918772
Are Trades by Large Individual Shareholders More Informative Than Those by Large Institutional Shareholders and Managers?
We investigate the profitability of insider trading by large non-family individual shareholders (LISs) and its sources. LISs earn higher profits from both purchases and sales when firms have higher information asymmetry and poorer governance. Their past firm affiliations before becoming LISs are the main source of their profits with personal traits, such as age, geographic location, education level, and experience, also enhancing profitability. While LISs purchase more shares than other insiders except large institutional shareholders, they sell fewer shares than all other insiders. We further find that their net purchases are informative in predicting firms’ future performance.
Cha, Yun Ju and Kang, Jun-Koo, Are Trades by Large Individual Shareholders More Informative Than Those by Large Institutional Shareholders and Managers? (July 22, 2024). Nanyang Business School Research Paper No. 24-12, Available at SSRN: https://ssrn.com/abstract=4905348 or http://dx.doi.org/10.2139/ssrn.4905348
Insider Trading by Other Means
For more than thirty years, one of the most prevalent strategies for insider trading has gone undetected and unaddressed. This Article uncovers the techniques by which executives and directors sell overvalued stock worth more than $100 billion per year, shifting losses to ordinary investors. The basic idea is that insiders conceal their suspicious trades by publicly reporting them (as they are required to do) in ways that confuse or discourage investigators. We develop a taxonomy of concealment strategies, complete with suggestive examples. We then empirically test our taxonomy using a database of essentially all stock trades since 1992. We find that insiders who trade using the subterfuges we describe outperform the market by up to 20% on average. Worse yet, we find evidence that this simple subterfuge works. Essentially no one has ever been prosecuted for undertaking one of these suspicious trades. Nor do journalists or scholars seem to appreciate them. Accordingly, we call for scholars and prosecutors to cast a wider net in their studies and market surveillance, then discuss implications for the design of insider-trading reporting requirements and related legal rules.
Avci, Sureyya Burcu and Schipani, Cindy A. and Seyhun, H. Nejat and Verstein, Andrew, Insider Trading by Other Means (July 19, 2024). Harvard Business Law Review, Available at SSRN: https://ssrn.com/abstract=4899359 or http://dx.doi.org/10.2139/ssrn.4899359
Negative Trading in Congress
We investigate negative trading, such as short selling, by members of Congress. We find, based on a new comprehensive dataset of trades by members of Congress, that negative trading not only is common, but also is associated with positive abnormal financial returns. Simply put, members of Congress’s bets on stock price drops make money.
In contrast, we do not find a similar association for long positions taken by members of Congress. In other words, there is an asymmetry between “positive” versus “negative” Congressional trading.
This asymmetry has multiple implications for public policy. Our main message is that proposals to regulate Congressional trading should reflect the empirical evidence that reveals key differences between positive and negative trading, and we show how current approaches fail to do so. Perhaps more controversially, we also argue that, depending on how one balances efficiency against fairness concerns, negative trading by members of Congress could be socially valuable and justify promotion, rather than suppression. Our empirical evidence also raises implications for the optimal disclosure regulation of Congressional trading in different financial instruments, particularly individual stocks versus mutual funds and stock options. Finally, our results support the emerging academic critique of Tobin’s Q as an unreliable measure of firm value.
Molk, Peter and Partnoy, Frank, Negative Trading in Congress (July 15, 2024). Indiana Law Journal forthcoming, University of Florida Levin College of Law Research Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=4895427 or http://dx.doi.org/10.2139/ssrn.4895427
Insider Trading Amid Political Signals and Sentiment
Inside shareholders of firms have information advantage over outsiders, and this is reflected in their trading activities in firm shares. This study investigates how political uncertainty influences insider trading using a sample of 6,834 US firms for the period 2000 to 2018. I find evidence that insider trading in the form of net stock buying rises with increases in political uncertainty. In contrast, the political sentiment of insiders is not found to be significantly related with their trading pattern, signifying the relevance of information asymmetry for insider trading. A higher proportion of short-term institutional ownership moderates the impact of political uncertainty on insider trading, suggesting that institutional investors closely monitor the firm management and minimize the degree of information asymmetry during such periods. The results are robust after employing different proxies for insider trading and political uncertainty as well as controlling for potential endogeneity and sample selection biases.
Khawaja, Mohsin, Insider Trading Amid Political Signals and Sentiment. Available at SSRN: https://ssrn.com/abstract=4889177 or http://dx.doi.org/10.2139/ssrn.4889177
Market Manipulation
Timely Cybersecurity Disclosure and Information Manipulation
Regulators have increasingly mandated firms to promptly disclose material cybersecurity incidents upon discovering these incidents. We find suggestive evidence indicating that some firms manipulate the discovery date (“misreport”) of a cybersecurity incident to postpone the disclosure of the incident, as evidenced by a pronounced spike in insider sales before the reported discovery date. We also find that misreporting is more prevalent among firms with weak internal control systems, when firms face low litigation risk, and when firms have greater pressure to meet a disclosure deadline. Further, firms suspected of misreporting tend to disclose their remedial actions and assert the restoration of business, mitigating negative market reactions upon disclosure of incidents. Collectively, our results suggest that firms might strategically misreport information about a cybersecurity incident to delay disclosure to gain additional time for remedial actions, which helps them prevent exposing vulnerabilities to malicious actors and alleviate stakeholder anxiety.
Lin, Xuanpu and She, Guoman, Timely Cybersecurity Disclosure and Information Manipulation (August 01, 2022). Available at SSRN: https://ssrn.com/abstract=4898168 or http://dx.doi.org/10.2139/ssrn.4898168
Do Buy-Side Analysts in Earnings Conference Calls Manipulate Stock Prices?
We investigate the generalizability of widely perceived notions that buy-side analysts try to influence or manipulate a firm’s stock price by praising or criticizing management during a public earnings conference call. Despite two institutional factors that make it difficult to detect empirically, we find some evidence of stock influence behavior by using a combination of data on conference call transcripts and trading by the institutions that employ the buy-side analysts. However, we also find evidence consistent with the null hypothesis that buy-side analysts are acquiring information rather than manipulating the stock price. Subsample analyses suggest that stock influence is more detectable among hedge funds, while information acquisition is the norm among traditional buy-and-hold institutions. The evidence we provide on each behavior should be of interest to firm managers who host conference calls, market participants who use conference calls to collect company information, as well as regulators who monitor for possible market manipulation.
Hu, Gang and Jung, Michael J. and Wong, M.H. Franco and Yu, Danlei Bonnie and Zhang, Frank, Do Buy-Side Analysts in Earnings Conference Calls Manipulate Stock Prices? (August 20, 2024). Journal of Corporate Finance, forthcoming , Available at SSRN: https://ssrn.com/abstract=4931582 or http://dx.doi.org/10.2139/ssrn.4931582
Pumping Up the Seos: The Rewards of Uninformed Speculation
Our research unveils the dynamics of seasoned secondary offerings, where issue size surpasses average market turnover. This creates an opportunity for market manipulation by speculators with restricted shares, even without fundamental information. Uninformed speculators strategically buy shares in the market before the offering, driving up both the market price and the price of their restricted shares. Unlike traditional manipulation models, our findings demonstrate that profitable manipulation doesn’t require multiple trading rounds. Instead, the difference in size between the offering and market turnover empowers speculators to inflate issue prices and stimulate excessive investment, offsetting the costs of stock-price distortion through restricted share liquidation. Our model presents novel testable implications that provide valuable insights into SEO process.
Banerjee, Suman and Wang, Kai and Noe, Thomas, Pumping Up the Seos: The Rewards of Uninformed Speculation. Available at SSRN: https://ssrn.com/abstract=4943144 or http://dx.doi.org/10.2139/ssrn.4943144
The GameStop Short Squeeze as a Case Study in Business Law Education
This article describes the GameStop short squeeze of January 2021, which was driven by retail investors from the online Reddit forum WallStreetBets. The short squeeze resulted in unprecedented market volatility and significant losses for institutional investors like hedge funds, leading to controversial trading restrictions by brokerages like Robinhood. This case study uses the GameStop saga to delve into key legal and ethical issues pertinent to an undergraduate business law class, including market manipulation, regulatory oversight/compliance, and conflicts of interest. It also examines fiduciary duties and class action lawsuits. By exploring these aspects, the study highlights the event’s educational value in demonstrating many real-life examples of business law concepts while underscoring the need for robust regulatory frameworks in an era shaped by social media and technological advances.
Pomparelli, Tara, The GameStop Short Squeeze as a Case Study in Business Law Education (June 30, 2024). Available at SSRN: https://ssrn.com/abstract=4880888
Odd Lots & Optics: Manipulation in Response to Scrutiny
We study the 2015 introduction of a voluntary disclosure program that focused on the execution quality of equity trades under 100 shares, known as odd lots. The disclosure program was enacted during a period of increased regulatory and media scrutiny of how market makers fulfilled odd lot orders. We show the percentage of odd lot orders that receive price improvement from market makers jumped discontinuously at the outset of the program. This jump was driven by trivially small price improvement given to a larger fraction of orders, and an offsetting reduction in larger price improvement for a small handful of orders. These changes resulted in no material difference in overall execution quality but allowed market makers and brokers to tout high execution quality statistics via their disclosures. Together, our evidence suggests that public scrutiny creates incentives for firms to use mutually reinforcing operational and disclosure changes to manipulate public sentiment.
Downing, Charles and Lynch, Bradford and Phillips, Matthew and So, Eric C., Odd Lots & Optics: Manipulation in Response to Scrutiny (July 02, 2024). MIT Sloan Research Paper No. 7070-24, Available at SSRN: https://ssrn.com/abstract=4883535 or http://dx.doi.org/10.2139/ssrn.4883535
Deep Unsupervised Anomaly Detection in High-Frequency Markets
Inspired by recent advances in the deep learning literature, this article introduces a novel hybrid anomaly detection framework specifically designed for limit order book (LOB) data. A modified Transformer autoencoder architecture is proposed to learn rich temporal LOB subsequence representations, which eases the separability of normal and fraudulent time series. A dissimilarity function is then learned in the representation space to characterize normal LOB behavior, enabling the detection of any anomalous subsequences out-of-sample. We also develop a complete trade–based manipulation simulation methodology able to generate a variety of scenarios derived from actual trade–based fraud cases. The complete framework is tested on LOB data of five NASDAQ stocks in which we randomly insert synthetic quote stuffing, layering, and pump-and-dump manipulations. We show that the proposed asset–independent approach achieves new state-of-the-art fraud detection performance, without requiring any prior knowledge of manipulation patterns.
Poutré, Cédric and Chételat, Didier and Morales, Manuel, Deep Unsupervised Anomaly Detection in High-Frequency Markets (July 6, 2023). Available at SSRN: https://ssrn.com/abstract=4502662 or http://dx.doi.org/10.2139/ssrn.4502662
Spoofing: Effective Market Power Building Through Perception Alignment
This paper aims to show that market power exists in financial markets and analyze how spoofing is used by a high-frequency trader to build market power by taking advantage of both behavioral weaknesses of individual investors and microstructural loopholes of trading venues.
Design/Methodology/Approach:
After showing that market power exists in the financial market, this paper centers around the question of how market power is constructed in the financial market. To sharpen the answer to the question, the paper compares the conditions needed for market power construction in the financial market with those needed in the goods market. The paper selects spoofing, the frequently used order-based tactic in high-frequency trading strategies, to analyze in detail how spoof orders can ignite herding with market power building as the essence. The Flash Crash that occurred in the New York Stock Exchange on May 6, 2010 provides an excellent case of market power construction exhibited in spoofing
Findings:
The behavioral mechanism of market power construction in the case of spoofing is perception alignment. It becomes effective when two necessary conditions are met: the spoof trader takes advantage of the incomplete order display set up by the exchange; and the behavioral weaknesses exhibited by numerous individual investors. In addition to these key conditions, this paper finds other ones for market power to be created in the financial market. They are easier, quicker, more secret, more flexible and less risky relative to the conditions for market power building in the goods market.
Practical Implications:
The detailed analysis points to the behavioral mechanism, i.e. perception alignment, and microstructural mechanism, i.e. incomplete order display, that could be responsive to regulation.
Originality/Value:
The originality of the findings is to uncover the mechanism of spoofing in taking advantage of behavioral biases of individual investors. The value is to gain more complete understanding of the essence of herding caused by spoofing.
Michael, Bryane and Dalko, Viktoria, Spoofing: Effective Market Power Building Through Perception Alignment (June 10, 2020). Available at SSRN: https://ssrn.com/abstract=4876988
AI Governance in Algorithmic Trading: Some Regulatory Insights from the EU AI Act
The frenzied race toward Artificial Intelligence (AI) adoption is causing profound transformations within the financial sector, rendering capital markets an increasingly complex system. These dramatic and sweeping changes are most pronounced in data-intensive and high-performance computing domains, such as algorithmic trading. While AI-powered trading offers numerous benefits to financial firms, markets, and society, it also raises significant concerns regarding potential risks to market quality, integrity, and stability. Recent studies underscore the dangers posed by AI advancements, particularly when not accompanied by robust governance and regulatory frameworks, which could lead to new and heightened risks of market abuse. Amidst this risk-prone environment, there is growing recognition among policymakers and financial regulators of the pressing need to regulate AI deployment. This emerging awareness is crucial, as effective AI governance is essential to ensure that the benefits of technological innovation are not overshadowed by its inherent risks. In this very direction, the EU AI Act stands out as a landmark effort in establishing comprehensive AI regulation. Hence, this Article critically examines this fundamental piece of (global) legislation and compares it to sectoral regulation on algorithmic trading. By focusing on key legal provisions, the analysis demonstrates the potential superiority of the EU AI Act’s regulatory requirements for providers of “high-risk” AI systems over those for deployers of algorithmic trading systems under MiFID II. The Article concludes with some ideas for future risk-based regulation of AI applications in financial trading.
Azzutti, Alessio, AI Governance in Algorithmic Trading: Some Regulatory Insights from the EU AI Act (August 27, 2024). Available at SSRN: https://ssrn.com/abstract=4939604 or http://dx.doi.org/10.2139/ssrn.4939604
