Using a sample of the listed state-owned enterprises (SOEs) in China, this study investigates the impact of the compliance management reform on opportunistic insider trading. The results show that the reform significantly constrains opportunistic insider selling by executives in SOEs, while having insignificant impact on insider purchases. Mechanism analyses suggest that the effect primarily operates through improvements in corporate governance quality and reductions in information asymmetry. Moreover, the inhibitory effect of compliance management is more pronounced among local SOEs, firms subject to weaker external oversight, those located in regions with underdeveloped institutional environments, and it primarily suppresses opportunistic insider selling by directors and senior management. Additional analysis indicates that compliance management significantly mitigates stock price crash risk and contributes to capital market stability. This study contributes to the literature on the determinants of opportunistic insider trading by highlighting the role of compliance management as an external governance mechanism. It also provides practical implications for policymakers aiming to integrate government regulation with internal compliance practices to promote the high-quality development of capital markets. • We examine whether compliance management mitigates opportunistic insider trading. • Compliance management leads to a reduction in opportunistic insider selling only. • This effect is achieved through two mechanisms: corporate governance and information asymmetry. • The impact is pronounced in local SOEs, weaker external oversight, and less developed institutional environments. • Compliance management reduces stock price crash risk and enhances capital market stability.

Political network and muted insider trading

Are machines better predictors of insider trading?

Capital Market in general terms is defined as a business sector of trading securities such as shares, stock certificates, and bonds or securities in general. In practice, not all information can be accessed simultaneously by all people, so this becomes a problem in the capital market or can be said to be a crime, Crime in the capital market is increasingly rampant, one of which is insider trading or insider trading which is a form of crime and violation included in the capital market, Regulations regarding insider trading in Indonesia are regulated in Law Number 8 of 1995 in conjunction with Law No. 4 of 2023. Capital market crimes in the form of insider trading that occur both in Indonesia and in developed countries such as the United States both have detrimental effects on the public as investors, but the accountability carried out is different for insider trading perpetrators in each of these countries, therefore it is necessary to review how the legal regulations of insider trading in Indonesia and the United States relate to these two cases.

This paper examines how the predictive content of insider trading varies across industries. Using U.S. insider transaction data from 2005 to 2025 and firm-month level measures of insider trading and forward returns, we compare technology, banking, and utility firms within a unified framework. The results show that insider purchases in banking firms contain the strongest information about future returns, while the signal is substantially weaker in technology firms and moderate in utilities. We also document a clear asymmetry between buying and selling. Insider purchases are more informative than sales, while sales reflect more heterogeneous motives and are therefore harder to interpret. This buy–sell gap varies across industries and is most pronounced in banking and utilities. Finally, we compare insider-trading informativeness before and after the 2022 amendments to Rule 10b5-1. The results show that sell-side informativeness appears weaker in the post-2023 period, while the predictive content of purchases remains largely unchanged. This evidence is descriptive and does not imply a causal effect of the reform. Overall, the findings highlight the importance of industry-specific information environments and regulatory conditions in shaping the relation between insider trading and future stock returns.

The capital market is vulnerable to violations because it involves various parties. Violations can be administrative, such as failure to submit reports or permits from authorities, or more serious, such as market manipulation, insider trading, and fraud. One of the acts of manipulation in Indonesia occurred at the issuer PT. Sekawan Intipratama who made efforts to circumvent Indonesian regulations by carrying out a series of manipulation practices. Manipulation is a form of pseudo-practice in which transactions are carried out to deceive the market by creating the appearance of trading activity where none actually exists. The aim is to manipulate stock prices to reach a certain level desired by market participants to achieve goals that are not in accordance with actual transactions. As a result of this series, investors in the capital market experienced losses. This research uses normative juridical methods by collecting data from library studies. From the results of this research it can be concluded that: 1) The manipulation actions carried out by PT. Sekawan Intipratama in the Indonesian Capital Market is an act that violates the law. 2) Legal protection for investors for acts committed by PT. Intipratama comradeship can be done preventively or repressively. 3) Repressive protection for unlawful acts committed by PT. Sekawan Intipratama can be carried out in Litigation or Non-Litigation.

Insider trading is considered an eminent problem for the proper functioning of the securities market, as it enables people to trade with the help of unpublished price sensitive information (UPSI). The purpose of this research paper is to critically assess the measures taken by the Securities and Exchange Board of India (SEBI) to regulate insider trading in India. For this, the legal instruments provided under the SEBI Act of 1992 and the SEBI Prohibition of Insider Trading Regulations of 2015 are analysed. The paper examines the enforcement regime of SEBI, covering aspects related to surveillance, investigation process, and the penalty system. Some important problems faced by the enforcement regime include the challenge of establishing cases of insider trading using circumstantial evidence, the delay in procedures, ineffective deterrent provided by penalties, and complexity of transactions. The comparison of the enforcement process withthat of the United States reveals the shortcomings in the regime, especially concerning stronger penalties and quick investigations. The paper finally comes to the conclusion that although the regime in India has developed an effective and evolving regime for the regulation of markets, it is moderately effective in enforcing the laws against insider trading. The necessary steps in improving the regime include stronger penalties, use of advanced technological tools, faster process of adjudication, and provision for whistleblower protection.

• Novel Mapper-Based Topological Data Analysis Approach : Proposes a Mapper-based approach with expert knowledge to identify agents likely to be exposed to and influenced by information spread while minimizing false positives. • Validated on Synthetic & Empirical Data : Validates the approach using synthetic data with ground truth and empirical data with the statistical analysis using topological features of the data. • Superior Performance in Market Surveillance : Outperforms traditional anomaly detection and clustering methods in identifying information-driven trading behaviors. • Broad Applicability : Extends beyond finance to disease spreading and misinformation analysis, offering a versatile tool for contagion detection. Building on topological data analysis and expert knowledge, this study introduces a Mapper-based approach to cluster agents based on their tendency to be influenced by information spread. The context of our paper is financial markets with an aim to identify agents trading opportunistically on insider information while minimizing false positives, a critical challenge in financial market surveillance. We verify and demonstrate our methods using both synthetic and empirical data on insider networks and investor-level transactions in a stock market. Recognizing the sensitive nature of insider trading cases, we design a conservative approach to minimize false positives, ensuring that innocent agents are not wrongfully implicated. We find that the mapper-based method systematically outperforms other methods on synthetic data with ground truth. We also apply the method to empirical data and verify the results using a statistical validation method based on persistence homology. Our findings indicate that the proposed Mapper-based technique effectively identifies a subset of agents who tend to take advantage of inside information they have received. This method is highly adaptable to various applications involving the spread of information or diseases, where agents exhibit only indirect evidence of their carrier status (symptoms) through their behavior.

• We investigate illegal insider trading in China’s stock market. • Cross-provincial variation in legal quality affects insider-trading profitability and risk. • Stronger legal environments raise regulatory risk and enhance pricing efficiency. • Results show evidence consistent with deterrence in the form of fewer low-return trades. • Lower information efficiency enhances the positive impact of legal quality on insider-trading profitability. This study examines how provincial legal environments shape the profitability of illegal insider trading in China. Using 521 adjudicated insider-trading cases from 2006 to 2018, we hand-collect detailed information from court judgments and CSRC sanction documents to reconstruct holding-period returns and illicit gains. We combine these data with established provincial indices of legal development and firm-level measures of ex ante litigation risk to test whether legal risk is priced in illegal insider trades. We find that stronger provincial legal environments are associated with significantly higher per-trade profitability among illegal trades that insiders execute after accounting for enforcement risk. This pattern is consistent with a risk-compensation mechanism rather than a failure of enforcement, as stricter legal environments deter low-return trades and leave only trades with sufficiently high expected gains. Firm-level litigation exposure further strengthens this effect. The results remain robust to sample-selection corrections, alternative return measures and a range of heterogeneity tests. Overall, our findings show how institutional variation in enforcement shapes insider incentives and the risk–return trade-off of illegal trading.

Market professional performance under insider information leakage

This paper analyzes market manipulation and insider trading as phenomena that violate the principles of fair competition. These forms of unlawful conduct not only distort market pricing mechanisms, but also create unjustified advantages for certain market participants, which affects the competitive environment. Thus, these violations have a dual legal nature and require a comprehensive legal analysis.

This article discusses the financial and legal issues of forming an institution to counteract illegal financial transactions within the subsector of state financial control. The author identifies several sub-institutions within the proposed institution, including financial monitoring in the field of AML/CFT/EA/PWMD, the misuse of insider information, market manipulation, and countering fraudulent and corrupt transactions. The article highlights a number of applied legal issues, including, but not limited to, the regulation of the use of various automated systems for identifying illegal activities, the fragmentation of legal norms in terms of countering financial transactions with a corruption component. The author also identifies the problem of excessive regulatory pressure as a separate legal issue, which can negate the positive effects of procedures for countering illegal activities.

Identification of market abuse is an extremely complicated activity that requires the analysis of large and complex datasets. We propose an unsupervised machine learning method for contextual anomaly detection, which allows us to support market surveillance aimed at identifying potential insider trading activities. This method lies in the reconstruction-based paradigm and employs principal component analysis and autoencoders as dimensionality reduction techniques. The only input of this method is the trading position of each investor active on the asset for which we have a price sensitive event (PSE). After determining reconstruction errors related to the trading profiles, several conditions are imposed in order to identify investors whose behavior could be suspicious of insider trading related to the PSE. As a case study, we apply our method to investor resolved data of Italian stocks around takeover bids.

Purpose To investigate how the facial trustworthiness of financial analysts affects their ability to privately gather information from corporate insiders. The channels are hypothesized to be managerial features, information environment and legal enforcement. Design/methodology/approach The study employs a quantitative research design using a comprehensive sample of Chinese financial analyst reports. Machine learning techniques for facial analysis are applied to assess the trustworthiness of analysts, and the relationship between facial trustworthiness and the informativeness of the analysts' reports is analyzed. Findings We first find that more trustful-looking analysts can produce more informative reports upon their visits to the corporate insiders. The effect of analysts’ facial trustworthiness is driven by the gender difference and the level of professional competency of the visited insiders. Moreover, when information disclosure of the reported firm is lower, the trust effects become more pronounced. Finally, the trust effect disappears after a legal action against an insider trading activity related to one of the analysts’ visits. Originality/value We find that more trustful-looking analysts can gain more material information during their visits to the firms, particularly when interacting with managers who have lower professional competency and a greater tendency to trust others. This trust-based informational advantage is also amplified in firms with poorer information environments. Furthermore, this trust effect disappears after a legal action against an insider trading activity related to one of the analyst visits. Our results are robust after controlling for analysts’ competency, facial attractiveness and industrial concentration.

Purpose Audit regulations suggest that auditors consider insider trading as part of their assessment of and response to the risk of material misstatement as insider trading provides information about audit-relevant outcomes such as weak internal controls and fraud. The authors investigate whether audit fees reflect the increased risk revealed and more audit effort induced by insider selling. Design/methodology/approach This study uses empirical analysis with OLS. Findings The authors find that relative to companies with net insider buying, audit fees are higher among companies with net insider selling, especially when the insiders are officers. In addition, the authors find more audit effort is needed when a large, accelerated filer changes to a net insider seller. We further find that the value of total insider purchase is negatively related to audit fees among companies of net insider buying. Originality/value Collectively, the findings suggest that auditors’ risk assessments and effort are sensitive to information reflected in insider trading, consistent with regulatory recommendations for auditors to consider nontraditional risk characteristics.

This paper investigates how cyberattacks affect the market valuation of European financial institutions. Using an event study methodology on a sample of 31 cyber incidents affecting European financial firms between 2016 and 2024, we document a clear and statistically significant negative market reaction concentrated on the announcement day. Importantly, we find no evidence of abnormal price movements prior to disclosure, which is inconsistent with systematic insider trading. In contrast to prior studies that report pre-announcement abnormal returns (ARs) around cyber incident disclosures, our findings suggest that information leakages and insider trading may be less of a concern in the European financial sector. A time-trend analysis reveals diverging patterns: while the impact of non-confidential attacks has intensified, the market response to confidentiality breaches has weakened, consistent with improved disclosure and crisis management practices.

Is insider trading politically informative?

The Veracity of Insider Trading Signals in Financially Distressed Firms

Does CSR compensate for global institutional voids? Corporate insider trading as a test of transaction ethics

. We investigate the Stackelberg reinsurance-investment game between an insurer and a reinsurer with smooth ambiguity under inside information. The insurer is fully believes in the number of claims and the number of price jumps, and seeks to determine the optimal claim risk sharing strategy and the optimal investment strategy under inside information. The reinsurer does not fully believe in number of claims and the number of price jumps, he is ambiguous about the distribution of intensity and seeks to determine the optimal reinsurance pricing strategy and the optimal investment strategy under the average performance. Both the optimal claim risk sharing strategy and the optimal reinsurance pricing strategy form an optimal reinsurance contract. By using the stochastic optimal control technique, we derive analytically the optimal reinsurance contract and the optimal investment strategy under mean-variance utility. Finally, the influences of model parameters on the optimal reinsurance contract and the optimal investment strategy are examined through numerical experiments.