Quarterly literature watch highlight   This edition’s highlight features two papers studying how modern information channels, particularly social media platforms, impact markets: “Pump and Dump: Price Manipulation in Experimental Markets,” and “Social Media Noise and Stock Manipulation” (abstracts and links below).   “Pump and Dump: Price Manipulation in Experimental Markets” explores how social media messaging affects asset markets. The authors argue that the widespread use of social networks has made it easier to produce and disseminate misinformation cheaply to swing investor sentiment and manipulate prices. The authors implement a trading game that emulates markets and includes a simplified version of social media, allowing “informed” and “uninformed” subjects to send bearish, neutral, or bullish messages anonymously to the market. The study compares these markets against identical treatments without the use of messaging. The authors find that the ability to post messages does not improve price efficiency, and observed frequent misinformation produced by both informed and uninformed subjects. In about 38% of trading rounds, subjects were found to have employed a pump and dump strategy, with price manipulators earning more on average than other informed traders.   “Social Media Noise and Stock Manipulation” employs a stock manipulation model to investigate social media’s impact on investor decision-making, examining additional variables such as the mass of misinformation and number of followers held by price manipulators. The authors argue that their model highlights the criticality of these variables to misleading small investors, finding that a one percent increase in the followers count is associated with around 0.1% (0.6%) increases in manipulators’ profits (trading volume). A social media noise index proposed by the authors further supports these findings, observing that a unit increase in the index is associated with between 6% – 7% (50%) increases in manipulators’ profits (trading volume).

Pump and Dump: Price Manipulation in Experimental Markets *

We study how social media messaging affects asset markets using experimental methods. Participants trade in markets with asymmetric information, some markets with and some without    the ability to send anonymous public messages. Rather than improving market efficiency through information sharing, we find that messaging facilitates profitable pump-and-dump strategies. Informed traders systematically post misleading messages to manipulate prices. These manipulation schemes are frequently successful, with price manipulators earning substantially more than other informed traders. We also observe deceptive strategies by uninformed traders, though these were generally unprofitable. Both successful and unsuccessful manipulation schemes reduced market efficiency, highlighting an important consequence of investors using social media for financial communication.

Kluger, Brian and Saglam, Mehmet, Pump and Dump: Price Manipulation in Experimental Markets * (October 31, 2025). Available at SSRN: https://ssrn.com/abstract=5687922 or http://dx.doi.org/10.2139/ssrn.5687922

Social Media Noise and Stock Manipulation

This paper models stock manipulations where investors interact via social network communications. We propose a novel noise index in social media platforms. The model predicts that high volumes of social media noise significantly increase probability of success, profitability for manipulators as well as heighten trading volume of manipulated stocks. In addition, manipulation profitability increases with respect to the number of followers in social media posts mentioned the manipulated stock. Empirical investigations, based on over 3,800 U.S. small-cap stocks during January 2010 to 2018 December, confirm the theoretical predictions and hypotheses. Our paper demonstrates an urgent need for monitoring social media platforms in safeguarding financial market efficiency.

Cumming, Douglas J. and Tran, Vu, Social Media Noise and Stock Manipulation (January 15, 2025). Available at SSRN: https://ssrn.com/abstract=5971854 or http://dx.doi.org/10.2139/ssrn.5971854

Insider Trading

Insider Trading Against the Corporation

Corporate officers and directors learn bad news about their companies before the public. They can avoid losses if they quickly sell, but such sales face problems. Potential buyers may be reluctant to buy what insiders are frantic to sell. They may also sue or alert law enforcement. Insiders would prefer counterparties who are slow to ask questions or complain. One such counterparty may be the corporation itself, because the insiders (by definition) control it.

In this empirical project, we examine a large sample of insider sales to their corporation. We find strong evidence that such sales tend to precede a large drop in company value. When an insider sells stock back to their company, it is indeed consistent with them shifting losses to the company and its public investors.

Despite our finding, the SEC has tended to assume that insider transactions with the corporation are especially trustworthy and granted them partial exemptions from prophylactic law. The insider trading literature likewise overlooks this strategy. Our project corrects the course for regulators and scholars and asks what it means that both groups underestimated this possibility for so long.

Avci, Sureyya Burcu, Seyhun, H. Nejat and Verstein, Andrew, Insider Trading Against the Corporation (September 22, 2025). UCLA School of Law, Public Law Research Paper. Available at SSRN: https://ssrn.com/abstract=5518879 or http://dx.doi.org/10.2139/ssrn.5518879

Tell Me You Have a Plan! Insider Trade Signals from Firms Undergoing Corporate Downsizing

Firms routinely reduce their employee headcount in response to competitive and economic pressures. The effectiveness of downsizing appears mixed as firms enjoy positive excess returns but also increased delisting and default likelihoods, consistent with compensating investors for additional risk. We explore insider trading activity as a signal of firm downsizing effectiveness. While insiders purchase more and sell fewer shares when firms downsize workforces, we focus on the downsizing group. Exploiting heterogeneity within downsizing firms, we find that the excess returns observed in downsizing firms are concentrated in firms where insiders purchase shares. Further, insider purchases are followed by lower future delisting likelihoods and financial distress in downsizing firms. Finally, we observe that insider purchases at downsizing firms are more prominent when trades are easily observable. Our results are consistent with insiders intentionally providing costly, credible signals about corporate executives’ plan for firm improvement following downsizing.

Alldredge, Dallin and Blank II, Douglas Brian and Biggerstaff, Lee, Tell Me You Have a Plan! Insider Trade Signals from Firms Undergoing Corporate Downsizing (September 26, 2025). Available at SSRN: https://ssrn.com/abstract=5550238 or http://dx.doi.org/10.2139/ssrn.5550238

Leniency Laws and Lucrative Trades: The Impact of Antitrust Policy on Insider Profits

We study the impact of antitrust enforcement on insiders’ trading profits. The notion is that trading profits and product market collusion are related because collusion enhances insiders’ informational advantage. Using staggered crosscountry adoption of leniency laws, we show stronger enforcement curbs trading profits. Likewise, trading profits increase when enforcement decreases due to nearby DOJ office closures. Sensitivity of trading profits to antitrust enforcement varies with a firm’s likely role in collusive arrangements, its monitoring effectiveness, degree of information asymmetry between insiders and outsiders, and the industry’s propensity for collusion. We also document that stronger antitrust enforcement lowers the informativeness of insider trades.

Kurucak, Umit, Nanda, Vikram K. and Yayvak, Berk, Leniency Laws and Lucrative Trades: The Impact of Antitrust Policy on Insider Profits (September 15, 2025). Available at SSRN: https://ssrn.com/abstract=5705103 or http://dx.doi.org/10.2139/ssrn.5705103

AI-Driven Financial Market Surveillance of Shadow Insider Trading

The landmark SEC v. Panuwat case in 2024 broadened the scope of insider trading to include “shadow trading,” where material non-public information about one firm is used to trade in economically related firms. This expansion presents regulators and compliance officers with an exponential increase in surveillance complexity, as conventional correlation or event-study methods struggle to capture the vast network of potential cross-firm linkages. We address this challenge by developing an Adaptive Graph Multi-Attention Network (AGMAN) that integrates three complementary dimensions: (i) dynamic price co-movements, (ii) sectoral and industry affiliations, and (iii) corporate governance linkages. Using NYSE and NASDAQ data and benchmarking against traditional statistical approaches, we demonstrate that AGMAN successfully identifies Incyte as a shadow trading target in the Panuwat case – while correlation methods rank it far lower – and generalizes effectively across other insider trading cases. Our approach not only reduces false positives but also yields interpretable signals suitable for regulatory investigation. The findings highlight the potential of AI-driven graph learning to advance financial market surveillance and regulatory enforcement.

Li, Boyu, Stenfors, Alexis, Dilshani, Kaveesha, Guo, Andy, Mere, Peter and Chen, Fang, AI-Driven Financial Market Surveillance of Shadow Insider Trading. Available at SSRN: https://ssrn.com/abstract=5722753 or http://dx.doi.org/10.2139/ssrn.5722753

When Disasters Strike: How Do Corporate Insiders Respond to Climate Risk?

We also document that stronger antitrust enforcement lowers the informativeness of insider trades. This paper examines the impact of climate disasters on insider trading behavior. We investigate whether corporate insiders who directly experience climate shocks change their trading strategies concerning firms with different levels of climate risk. We find that insiders significantly increase their selling and reduce their buying activities after directly experiencing a disaster. These effects are more pronounced for firms with high exposure to climate-related risks. We further explore the mechanisms underlying these trading responses and provide evidence that insiders acquire and act on information gained through their personal experience of the event. In line with this mechanism, we find that the effects are stronger for more experienced insiders and for firms with greater information asymmetry. We also find that the effects are concentrated in non-routine trades, they are particularly pronounced immediately following blackout periods and yield significant abnormal returns.

Faralli, Matilde and Tveiten, Hedda Rytter, When Disasters Strike: How Do Corporate Insiders Respond to Climate Risk? (June 25, 2025). Available at SSRN: https://ssrn.com/abstract=5804063 or http://dx.doi.org/10.2139/ssrn.5804063

Does Insider Trading Correct Mispricing?

We examine whether insider trading corrects mispricing and improves stock price efficiency. Using established measures to identify overvalued and undervalued stocks, we find that insider trading helps correct mispricing – but asymmetrically: insider sales have an immediate impact on correcting overvaluation in the short term, whereas insider purchases correct undervaluation only over longer horizons. To understand the underlying mechanism, we show that insider trades overall contain information about long-term fundamentals, particularly for overvalued firms. However, only a small portion of this information is incorporated into stock prices immediately. To sharpen our analysis on the effect of informed insider trading, we exclude routine and preplanned insider transactions and show that mispricing correction is driven primarily by opportunistic insider trades. Our findings highlight the informativeness of certain types of insider transactions and the overall limited role in stock price discovery.

Faralli, Ma, Yun and Jiang, George, Does Insider Trading Correct Mispricing?. Available at SSRN: https://ssrn.com/abstract=5852457 or http://dx.doi.org/10.2139/ssrn.5852457

Wealth or Stealth? The Camouflage Effect in Insider Trading

We consider a Kyle-type model where insider trading takes place among a potentially large population of liquidity traders and is subject to legal penalties. Insiders exploit the liquidity provided by the trading masses to “camouflage” their actions and balance expected wealth with the necessary stealth to avoid detection. Under a diverse spectrum of prosecution schemes, we establish the existence of equilibria for arbitrary population sizes and a unique limiting equilibrium. A convergence analysis determines the scale of insider trading by a stealth index γ, revealing that the equilibrium can be closely approximated by a simple limit due to diminished price informativeness. Empirical aspects are derived from two calibration experiments using non-overlapping data sets spanning from 1980 to 2018, which underline the indispensable role of a large population in insider trading models with legal risk, along with important implications for the incidence of stealth trading and the deterrent effect of legal enforcement.

Ma, Jin, Xia, Weixuan and Zhang, Jianfeng, Wealth or Stealth? The Camouflage Effect in Insider Trading (November 30, 2025). Available at SSRN: https://ssrn.com/abstract=5836802 or http://dx.doi.org/10.2139/ssrn.5836802

CEO Origin and Insider Trading

This study investigates the impact of CEO origin on insider trading. We find that outside CEOs generate higher profits from insider sales than their inside counterparts, with the results being significant over various event windows within a one-year period, but not from insider purchases. Given that sales involve greater legal risk than purchases, these findings suggest that outside CEOs may have greater access to non-firm specific information. Our results remain robust after excluding routine trades and using dollar profits as a measure of trading profitability, as well as after addressing potential endogeneity concerns. Further analysis indicates that the informational advantage of outside CEOs is primarily attributable to their enhanced involvement in R&D activities, greater  access to non-firm specific knowledge through interlocking directorships, and superior information processing skills derived from prior professional experience. This advantage is particularly pronounced in firms with higher information asymmetry, the presence of principal customers, and during the early stages of the CEOs’ tenure. Overall, we shed new light on the importance of CEO origin in explaining insider trading profitability.

Wang, Shaoyi, Yi, Lingxue and Bai, John (Jianqiu), CEO Origin and Insider Trading. Available at SSRN: https://ssrn.com/abstract=5908312 or http://dx.doi.org/10.2139/ssrn.5908312

Insider Trading and Position Limits

Federal law has long prohibited insider trading in securities such as stocks and bonds. Yet many other financial assets-particularly derivatives and commodities-have historically fallen outside those rules. This Article asks why insider trading is penalized for some assets but not others. It argues that the goals of insider trading law are often pursued through alternative mechanisms. Markets lacking insider trading prohibitions are not unregulated; rather, they are governed by substitute regimes that achieve similar ends through different means. By examining the relationship between securities insider trading law and derivatives position limits, this Article clarifies the function of insider trading regulation and illuminates its boundaries. It shows that position-limit rules, though rarely analyzed in this way, can serve as functional substitutes for insider trading restrictions, offering a broader perspective on how law manages informed trading across markets.

Verstein, Andrew, Insider Trading and Position Limits (December 12, 2025). UCLA School of Law, Law-Econ Research Paper Forthcoming, Available at SSRN: https://ssrn.com/abstract=5911003 or http://dx.doi.org/10.2139/ssrn.5911003

Market Manipulation

The Cost of Oversight: Hedge Fund Regulatory Risk and Market Efficiency

Regulators enforce rules to deter misconduct and maintain orderly markets. However, their task is complicated by hedge funds’ complex strategies, which are difficult to classify as legitimate or manipulative. Regulatory risk, the likelihood of investigation or litigation, deters manipulation but can also discourage legitimate trading. Thus, the net effect of regulatory risk on financial markets is an empirical question. This paper examines the impact of hedge fund regulatory risk on stock market efficiency. Increased regulatory risk hurts weak-form price efficiency and price informativeness, as hedge funds reduce informed trading in response. The results indicate that efficiency gains from deterring manipulation are outweighed by efficiency losses from reduced legitimate trading.

Yang, Jeffrey, The Cost of Oversight: Hedge Fund Regulatory Risk and Market Efficiency (October 31, 2025). Available at SSRN: https://ssrn.com/abstract=5692322 or http://dx.doi.org/10.2139/ssrn.5692322

Bot-Induced Social Media Manipulation and Stock Market Distortion

Using an exogenous shock to bot activity, we show that bot presence and their impact rise with the ease of infiltrating social platforms. Bots significantly manipulate social media attention and are most likely to target firms that are more volatile with recent momentum and around earnings releases. When bot penetration is high, stock price synchronicity increases and post-earnings announcement drift is stronger, indicating that bots lead to less efficient prices. Bot accounts promoting stocks generate sharp positive returns followed by partial reversals and retail order imbalances likely exacerbating trading frenzies. Overall, bots create information frictions that distort market prices. Our evidence reinforces regulators’ concerns about AI-driven stock manipulation.

Bradley, Daniel, Hanousek Jr., Jan and Svoboda, Dominik, Bot-Induced Social Media Manipulation and Stock Market Distortion (December 12, 2025). Available at SSRN: https://ssrn.com/abstract=5912222 or http://dx.doi.org/10.2139/ssrn.5912222