Insider Trading & Market Manipulation Literature Watch: Q1 2025

Quarterly literature watch highlight   The article “Insider Trading in Connected Firms during Trading Bans,” (abstract and link below) adds to the new and evolving research on “Shadow Trading.” The authors study trades made by directors that sit on multiple boards. In particular, they examine trades made by board members in companies that were not in blackout periods, while under blackout periods for another company they serve (“connected firms”). The authors find that directors frequently trade more in connected firms when they are subject to a blackout period in another firm. The study finds a positive correlation between the stock returns of firms subject to blackout periods compared to the connected firm, and that this correlation is strengthened by the proxies for potential relationships between the firms.   The authors of the article argue that the study contributes to research on “shadow trading” – trading in securities while in possession of information about another company. The SEC recently obtained a verdict based on allegations of shadow trading against Matthew Panuwat, alleging the use of confidential information about the acquisition of his then-employer, Medivation, to purchase securities in another public company, Incyte.1   Although the research paper finds a statistical relationship amongst directors’ trades in connected firms with firms subject to blackout periods, their analysis is based on a large sample of trades and does not establish whether and how information about the firms in blackout periods informed trading in connected firms. Whether there is any actual connection between trades in one firm and the information on another firm requires detailed case-by-case analysis.

Insider Trading in Connected Firms during Trading Bans

Insiders are subjected to trading bans or close periods before earnings announcements. Directors with multiple board seats can still trade in their other firms not subject to close periods. When a close period restricts insider trading, directors leverage insider information about that firm to trade in their other firms. This is supported by positive correlations between stock market reactions in close and traded firms, which are moderated by the type of firm relationships and institutional investor presence. This newly documented informational advantage, may encourage policymakers to apply the close period to all firms where a director holds board seats.

Goergen, Marc and Renneboog, Luc and Zhao, Yang, Insider Trading in Connected Firms during Trading Bans (January 01, 2025). European Corporate Governance Institute – Finance Working Paper No. 1029/2025, HKU Jockey Club Enterprise Sustainability Global Research Institute Paper No. 2025/004, Available at SSRN: https://ssrn.com/abstract=5086405 or http://dx.doi.org/10.2139/ssrn.5086405

Insider Trading

Does Uncertainty Disclosure Tone Influence Insider Trading Profitability?

We examine the relationship between uncertainty disclosure tone and insider trading profitability based on a large sample of U.S. listed firms. We find that, where financial reports exhibit higher levels of uncertainty disclosure tone, insider trading profitability is higher. Our results are robust to endogeneity tests, alternative measurement specifications, and models with additional control variables. Subsample tests show that the positive and significant relationship between uncertainty disclosure tone and insider trading profitability is sustained when firms face high litigation risk or financial reports exhibit lower levels of disclosure complexity. This study extends prior insider trading research by demonstrating that obfuscation of financial information through uncertainty in the disclosure tone can be employed to retain the private benefits of that information and to enhance trading profitability. These findings have important implications for shareholders and regulatory bodies given that the nature of the language used in financial reports may affect the integrity and transparency of financial markets.

Geng, Hongshan and Eulaiwi, Baban and Al-Hadi, Ahmed and Duong, Lien and Duong, Lien and Taylor, Grantley, Does Uncertainty Disclosure Tone Influence Insider Trading Profitability?. Available at SSRN: https://ssrn.com/abstract=5188459 or http://dx.doi.org/10.2139/ssrn.5188459

Insider Trading Patterns During the Covid Period

We investigate insider trading patterns during the Covid period and document unique patterns in purchases and sales. A significant increase in insider purchases was noted from late February to early April 2020, along with a fourfold increase in insider sales throughout 2020. We find a strong link between insider trading and market performance. Regression analysis shows insiders act as contrarians, buying undervalued and selling overvalued stocks. Insider trading during the Covid period significantly predicts future stock returns, primarily driven by opportunistic transactions, confirming that insiders trade on information during high market uncertainty.

Ma, Yun and Ma, Xiaoli and Jiang, George, Insider Trading Patterns During the Covid Period. Available at SSRN: https://ssrn.com/abstract=5163490 or http://dx.doi.org/10.2139/ssrn.5163490

Insider Trading as a Compensation Mechanism

We investigate whether insiders at small firms trade more often to supplement their compensation. Specifically, we find that insiders at small firms trade more often in patterns indicating the use of private information and they realize abnormal returns following these transactions. The relation between insider trading at small firms and compensation is dependent on the type of compensation. For equity-based compensation there is an insignificant relation. Instead, the greater amount of trading at small firms is driven by sales and is only present relative to the cash-based compensation insiders receive. This indicates that when the level of compensation received is not directly tied to firm value, the insider is more likely to trade opportunistically, even if their trade transmits a negative market signal through selling. Overall, these results support the flexible contracting hypothesis developed in legal theory which states that employees at resource constrained firms tend to use insider trading to tailor their compensation.

Houston, Caleb and Chen, Jiawei and Jansen, Benjamin, Insider Trading as a Compensation Mechanism. Available at SSRN: https://ssrn.com/abstract=5158078 or http://dx.doi.org/10.2139/ssrn.5158078

Trade as I say, Not as I do: Management Rhetoric and Insider Stock Sales

In recent years, company filings have featured a notable rise in anti-short selling rhetoric. This paper investigates whether changes in such language help explain fluctuations in abnormal insider equity sales. Despite disclosures suggesting an artificially suppressed stock price, we estimate a 70% increase in the probability of an insider sale following the use of certain buzzwords in public company filings, a result that contrasts with established theory. These insider sales often precede significant stock price declines and correlate with future accounting restatements, suggesting potential private information and timing effects. Additionally, we provide evidence that this rhetoric influences retail investors, who engage in increased discussion and purchases of a firm’s stock after it employs anti-short selling language.

Balthrop, Justin and Bitting, Jonathan and Clark, Ryan, Trade as I say, Not as I do: Management Rhetoric and Insider Stock Sales (February 26, 2025). Available at SSRN: https://ssrn.com/abstract=5156207 or http://dx.doi.org/10.2139/ssrn.5156207

Reverse Timing of Insider Trading

In 2000, the SEC enacted Rule 10b5-1, which allows insiders to preplan transactions to avoid trading on material nonpublic information. However, it is unclear whether corporate executives strategically influence the timing and content of information disclosure to benefit their preplanned trades. Examining stock returns around preplanned insider transactions, we find that insiders appear to be “perfect” timers. In addition, we find significantly more frequent 8-K filings and corporate releases before insider trades. Moreover, the information content of corporate releases significantly contribute to stock return patterns around insider transactions. The evidence suggests that corporate disclosure correlates with and benefits preplanned trades.

Ma, Yun and Jiang, George, Reverse Timing of Insider Trading (June 28, 2024). Available at SSRN: https://ssrn.com/abstract=5127723 or http://dx.doi.org/10.2139/ssrn.5127723

The Fish Rots from the Head Down: CEO and Non-CEO Opportunistic Insider Trading

We empirically analyze how a CEO’s opportunistic insider trades influence the subsequent opportunistic trading activities of non-CEO insiders within the same firm. Our findings suggest that the CEO’s trades encourage similar behavior among other insiders, serving not only as a source of boldness for non-CEO insiders but also providing them with a financial incentive to trade. Through the boldness channel, the CEO’s trading erodes the corporate culture of integrity, lowers psychological barriers, and emboldens non-CEO insiders. Through the incentive channel, we find that the trades of non-CEO insiders who trade following those of the CEO yield superior stock returns. Our cross-sectional analysis reveals that the CEO’s influence is more pronounced in firms with stronger corporate governance, where non-CEO insiders rely on the CEO’s lead; in firms with weaker governance, non-CEO insiders engage in insider trading independently. We establish causality utilizing an instrumental variable approach. Finally, we perform a rich series of robustness checks, and our findings remain consistent with our main analyses.

Chemmanur, Thomas J. and Jiang, Cheng and Yang, Lukai and Zhang, Jingyu, The Fish Rots from the Head Down: CEO and Non-CEO Opportunistic Insider Trading (November 14, 2024). Available at SSRN: https://ssrn.com/abstract=5086417 or http://dx.doi.org/10.2139/ssrn.5086417

Mandatory Data Breach Disclosure and Insider Trading

We examine whether mandatory data breach disclosure affects insider-selling behavior and find that selling profits are greater after states require firms to disclose data breaches. The effect is more pronounced for firms with weaker corporate governance, higher cybersecurity risk, and without prior investment in material cyber protection programs. However, insiders profit less when they operate in states with stricter laws and face higher litigation risks. The evidence is consistent with managers personally hedging risks in the capital market when mandatory disclosure laws designed to protect customers are weakly enforced. Laws designed to improve transparency in the product markets may have the unintended effect of reducing the integrity of financial markets. However, insider sales also facilitate the incorporation of bad news in stock prices, making idiosyncratic crashes less likely.

Chen, Xi and Hilary, Gilles and Tian, Xiaoli (Shaolee), Mandatory Data Breach Disclosure and Insider Trading (March 01, 2019). Journal of Business Finance and Accounting, forthcoming, Available at SSRN: https://ssrn.com/abstract=5012929 or http://dx.doi.org/10.2139/ssrn.5012929

The Nexus Between Insider Trading and Organized Crime: Challenges in Enforcing Ethical Market Practices

The intersection of insider trading and organized crime poses significant challenges for maintaining ethical market practices and safeguarding financial markets. Insider trading, the unlawful use of non-public information for personal gain, undermines market integrity and investor trust. When coupled with organized crime, the risks extend beyond financial losses, enabling criminal networks to launder money, manipulate markets, and exploit regulatory loopholes. This nexus creates systemic vulnerabilities that compromise global economic stability and strain enforcement mechanisms. This paper explores the intricate relationship between insider trading and organized crime, emphasizing its implications for market ethics and regulatory frameworks. It examines the methods employed by criminal organizations, including collusion with corporate insiders and the exploitation of complex financial instruments, to perpetrate these activities. The research also evaluates the challenges faced by regulators, such as detecting sophisticated schemes, navigating jurisdictional constraints, and addressing resource limitations. Through a critical analysis of enforcement strategies, including surveillance technologies, cross-border cooperation, and legislative reforms, the study highlights the need for a multi-faceted approach to address these issues effectively. The paper also underscores the importance of fostering a culture of ethical compliance within organizations to mitigate insider trading risks. By analysing case studies and reviewing current regulatory practices, this research offers actionable insights for strengthening market integrity. It advocates for enhanced international collaboration, robust regulatory oversight, and the integration of advanced technologies to detect and deter illicit activities. The findings underscore the urgency of addressing this nexus to promote ethical market practices and protect the global financial ecosystem.

Mesioye, Olubusayo. (2025). The Nexus Between Insider Trading and Organized Crime: Challenges in Enforcing Ethical Market Practices. International Journal of Research Publication and Reviews. 6. 1817-1831. 10.55248/gengpi.6.0125.0414.

Market Manipulation

Opening Call Auction Designs and Price Manipulation for Price Discovery: An Experimental Study

We conduct laboratory experiments under different opening call auction designs to improve the price discovery process. We find price manipulations in a call market with cancellations. However, we can mitigate manipulative behavior when prohibiting order cancellations or executing orders periodically before the end of a call auction. The price discovery can be quickly achieved in periodic clearings, suggesting that price manipulations and longer non-trading minutes result in slower price discoveries. We further demonstrate the important role of reinforcement learning on price manipulations and the price discovery process. We conclude the periodic clearings for the best opening call auction design.

Yamamoto, Ryuichi and FANG, XIN and Funaki, Yukihiko, Opening Call Auction Designs and Price Manipulation for Price Discovery: An Experimental Study. Available at SSRN: https://ssrn.com/abstract=5120224 or http://dx.doi.org/10.2139/ssrn.5120224

Artificial Intelligence in Financial Services: Advancements in Fraud Detection, Risk Management, And Algorithmic Trading Optimization

Fraud detection, risk management, and algorithmic trading optimization are being revolutionized by AI in financial services. AI reduces false positives and speeds up fraud detection by spotting trends and anomalies in real time using advanced machine learning techniques. Financial institutions can now fight sophisticated cyber attacks with AI-powered fraud detection systems that analyze massive databases and detect illicit conduct with unparalleled accuracy. AI-powered predictive analytics are changing how financial organizations identify and mitigate risks. Institutions can predict credit defaults, market swings, and operational weaknesses using big data and AI. Natural language processing (NLP) techniques are extracting insights from unstructured data sources including regulatory filings and market news to improve decision-making. Real-time risk monitoring systems enable proactive interventions to reduce losses and assure regulatory compliance. AI is transforming algorithmic trading, another financial breakthrough. Advanced machine learning models analyze historical and live market data to predict price movements, find arbitrage opportunities, and execute trades in milliseconds. Reinforcement learning is helping design adaptable algorithms that respond to market changes, increasing profitability and reducing risk. AI also promotes ethical and transparent trading tactics, solving market manipulation problems. This study analyses the newest AI applications in financial services and their disruptive influence. Generative AI, federated learning, and quantum computing will further transform the sector. AI adoption has many benefits, but data privacy, algorithmic bias, and legal complexity must be addressed to sustain progress. AI can improve financial services efficiency, resilience, and creativity, creating a future where technology drives trust and strategic advantage.

Patil, Dimple, Artificial Intelligence In Financial Services: Advancements In Fraud Detection, Risk Management, And Algorithmic Trading Optimization (November 20, 2024). Available at SSRN: https://ssrn.com/abstract=5057412 or http://dx.doi.org/10.2139/ssrn.5057412

The DeepFake and its Impact on Trading Signals

Deepfake technology, powered by advanced artificial intelligence techniques such as generative adversarial networks (GANs), has emerged as a disruptive force with profound implications for financial markets. By enabling the creation of hyper-realistic but fraudulent multimedia content, deepfakes pose a significant threat to the integrity of trading signals, market sentiment, and investor decision-making. This paper explores the multifaceted impact of deepfakes on trading signals, focusing on their ability to manipulate market sentiment, disrupt algorithmic trading systems, and exploit the vulnerabilities of retail investors.

Through a detailed analysis, the study identifies key mechanisms by which deepfakes influence financial markets, including falsified corporate announcements, misrepresentation of policy statements, and amplification of misinformation via social media. The paper also highlights the susceptibility of algorithmic trading systems to deepfake-driven misinformation and the broader implications for market stability, such as increased volatility and erosion of trust in traditional information sources.

To address these challenges, the paper proposes a combination of mitigation strategies, including the development of AI-based detection tools, public education initiatives, regulatory frameworks, and the integration of blockchain technology for content authentication. By emphasizing interdisciplinary collaboration among technologists, financial experts, and policymakers, the study provides a roadmap for safeguarding market integrity in the face of emerging threats posed by deepfake technology.

This research underscores the urgency of proactive measures to counteract the risks associated with deepfakes, ensuring that financial markets remain resilient, transparent, and trustworthy in an increasingly digital and interconnected world.

Shamo, Sebastian Anetey, The DeepFake and its Impact on Trading Signals (August 08, 2024). Available at SSRN: https://ssrn.com/abstract=5070125 or http://dx.doi.org/10.2139/ssrn.5070125

Detecting Pump & Dump stock market manipulation from online forums

The intersection of social media, low-cost trading platforms, and naive investors has created an ideal situation for information-based market manipulations, especially pump &dumps. Manipulators accumulate small-cap stocks, disseminate false information on social media to inflate their price, and sell at the peak. We collect a dataset of stocks whose price and volume profiles have the characteristic shape of a pump &dump, and social media posts for those same stocks that match the timing of the initial price rises. From these we build predictive models for pump &dump events based on the language used in the social media posts. There are multiple difficulties: not every post will cause the intended market reaction, some pump &dump events may be triggered by posts in other forums, and there may be accidental confluences of post timing and market movements. Nevertheless, our best model achieves a prediction accuracy of 85% and an F1-score of 62%. Such a tool can provide early warning to investors and regulators that a pump &dump may be underway.

Nam, D., Skillicorn, D.B. Detecting Pump &Dump stock market manipulation from online forums. Digit Finance (2025). https://doi.org/10.1007/s42521-024-00121-4

The effect of analyst following on market manipulation

Utilizing a sample of suspected stock manipulation cases identified through intraday data, we find a significantly negative relationship between the analyst following and the frequency of market manipulation. This relationship remains consistent when considering index reconstitutions as an instrumental variable to address potential endogeneity concerns related to analyst following. Furthermore, our findings indicate that the suppressive effect of analyst following on market manipulation is driven by the enhancement of pricing efficiency. Additionally, our results suggest that a higher level of independent institutional ownership can potentiate the impact of analysts following on curbing manipulation.

Liu, J., Chen, Y., & Lin, G. (2025). The effect of analyst following on market manipulation. Applied Economics Letters, 1–5. https://doi.org/10.1080/13504851.2025.2466737