Insider Trading Research Articles

Manipulating stock prices based on insider information

Purpose This paper aims to investigate the trading behavior of insider investors before and after information releases, identifying information-based manipulation in the stock market and the characteristics of companies whose stock prices are manipulated. Design/methodology/approach This paper employs logit regression method and an event study approach, utilizing hand-collected data from 2010 to 2022, with information categorized into negative and positive types. Findings The results show no evidence of insider trading or negative information-based manipulation in both high and low transparency firms. However, in highly transparent companies, the Board of Directors (BOD) avoids direct manipulation by using relatives to evade market supervisors. In low transparency companies, both the BOD and family members (FM) exploit positive information to benefit personally by buying shares before releasing favorable news, causing a sharp stock increase, and selling afterward. Continued buying by the BOD and FM also suggests likely positive news announcements. Practical implications The characteristics of information-based manipulation in companies, as provided by this study, help individual investors avoid investing in stocks that are highly susceptible to manipulation. Originality/value Empirical research on information-based manipulation is scarce due to limited secondary data. Our study uses transaction data from insider investors in a frontier market with low transparency and high information asymmetry. This enables us to analyze information-based stock price manipulation. We identify manipulation by comparing insiders' trading behavior with their market information releases, resulting in stock price fluctuations greater than 5%.

Political burden of local government and land insider trading in major Chinese cities

ABSTRACT Chinese local governments transfer political burdens through land trading. One key example of this practice is the requirement for for-profit organizations to bid on land when undertaking public welfare projects. By analysing comprehensive data on public welfare project development in major Chinese cities, we conducted regression analyses and endogeneity tests to explore whether there is a causal relationship between the political burdens faced by for-profit organizations and their land trading priorities, with a focus on insider trading characteristics. Our findings reveal that, even in marketized transactions, the land designated for public welfare projects tends to have lower prices and bidding premiums, reflecting key insider trading traits. Price priority is more apparent among private developers, indicating higher compensation for political burdens, while premium priority is more evident among government-controlled enterprises due to increased paternalism.

Corruption and insider trading

We investigate firm corruption in China by extracting a measure of corruption from published financial statements and use this to demonstrate that corruption impacts the trading decisions of insiders. Specifically, we show that insiders in firms that are more corrupt trade more aggressively, and they are more willing to trade on their private information as evidenced by the increased informativeness of their trades, in respect of both purchases and sales. This link between firm corruption and trade informativeness is robust to the inclusion of a number of factors that are known to influence the informativeness of such trades, including trade characteristics, insider characteristics and the firm's information environment. We also consider the effect of the appointment of a new CEO or Chair. Overall, corruption related trade informativeness holds consistently for both purchases and sales. Finally, we show that this measure of corruption is robust to the inclusion of several alternative indicators of corporate misconduct.

Voting for insider trading regulation. An experimental study of informed and uninformed traders’ preferences

Capital markets often regulate insider trading, but whether such regulation aligns with traders’ preferences is an open question. This study examined traders’ regulation preferences conditional on their prospects of becoming informed. Of 64 referenda, traders decided 41 (64%) against regulation. Moreover, traders’ prospects of becoming informed significantly impacted the outcomes of the referenda. In markets in which a group of traders has no chance of receiving inside information, 47% of the referenda are decided against regulation. When all traders could get such information, 81% are. Individual votes reveal that traders who know they will remain uninformed support regulation in 69.27% of the cases, while informed traders do so only 8.33% of the time. Traders who may or may not become informed support regulation 33.33% of the time.

Actively managed equity mutual funds in emerging markets

In this study, we analyze the performance of mutual fund managers who operate in emerging markets. Emerging stock markets differ from mature markets in significant ways, such as weak prosecution for insider trading, poor corporate governance practices, and a lack of liquidity, which create market inefficiencies that active investment strategies can exploit. We evaluate conditional alphas and multiple measures of liquidity, with a focus on equity funds that invest in emerging markets to achieve abnormal returns. Our analysis shows that smaller funds are significantly impacted by liquidity and that conditioning for public information has a significant effect on the distribution of returns. We find evidence of positive abnormal returns, which suggests that active management in emerging markets can be profitable.

The role of artificial intelligence in preventing corporate crime

This article explores the novel and transformative role AI plays in enhancing corporate compliance and monitoring to mitigate corporate crime. It delves into how AI technologies, through advanced data analysis and predictive analytics, are revolutionizing the detection and prevention of financial fraud, insider trading, and non-compliance with environmental regulations. The integration of AI into the financial sector is emphasized as pivotal for developing robust fraud prevention algorithms, which analyze vast data volumes to identify malicious activities and prevent financial losses. Moreover, the article probes into the ethical and privacy concerns surrounding the deployment of AI, highlighting the balance needed between efficient crime prevention and safeguarding individual privacy rights. Garcia-Segura's analysis also underscores the need for international cooperation and legal adaptation to uphold ethical standards in AI’s application, ensuring it promotes fairness and justice in combating corporate crime.

Legal Protection of Investors against Insider Trading Practices Capital Market

Legal Protection of Investors against Insider Trading Practices Capital Market

Solving Investors’ Problems with Access to Evidence in Damages Litigation: Suggestions for a Future Issuer Liability Regime

AbstractPrivate enforcement’s role in the European secondary securities market is narrow. Issuer companies’ civil liability for violations of the inside information disclosure obligation is no exception. While trying to avoid the shadow of the US class action institution, European scholarship has long explored ways to increase the role of private enforcement in the securities market. Harmonising issuer liability is one of the suggestions to create a more prominent role for private enforcement. Even though harmonising issuer liability would be a welcome option for legal certainty and investor protection, it seems unlikely to happen in the near future. As an initial step towards potential harmonisation, this article analyses credit rating agencies’ (CRAs) liability and liability for competition law violations from the viewpoint of information asymmetry in litigation. It evaluates whether the legislative solutions in the CRA III Regulation and the Competition Damages Directive regarding plaintiffs’ access to evidence could be used as models for a potential issuer liability regime. The article finds that the choices made in the Competition Damages Directive could serve as viable models for issuer liability. The provisions in that Directive solve the information asymmetry between the plaintiff and the defendant by granting the plaintiff access to evidence in litigation through a court order.

Insider trading and climate disasters

Climate disasters are increasing in frequency and severity. While a large body of research has shown that extreme climate affects various economic decisions, how climate events influence investment decisions remains largely under-investigated. This paper examines whether, and to what extent, climate disasters influence insider transactions, which are important investment decisions that attract increasing attention from both corporate management and policymakers. We find that the monthly value of insider trades increases markedly in firms headquartered in counties with a climate disaster. Climate-induced insider trading holds in general but is stronger when investors are distracted and less prevalent when insiders face higher litigation risk. Climate disasters trigger uncertainty about short-term firm fundamentals, and insiders benefit by selling prior to this being priced. Insiders living in disaster counties do not trade more than those in unaffected counties, which does not support a personal liquidity motivation. Our paper documents a new way through which climate impacts investor behavior and financial markets.

Insider trading restriction enforcement, investor protection, and innovation

Insider trading restriction enforcement, investor protection, and innovation

Staggered boards, agency costs and stock price crash risk: Evidence from China

In this study, we leverage unique, hand-collected data to explore the impact of staggered boards on the likelihood of future stock price crashes. Our analysis shows that companies with staggered boards are at a higher risk of future stock price crashes compared to their counterparts with non-staggered boards, particularly in firms with elevated agency costs and those not state-owned. Additionally, we find that staggered boards exacerbate this risk by failing in their monitoring and advisory capacities. Evidence of this failure emerges through various indicators of diminished oversight, including managerial opportunism, financial reporting manipulation, insider trading, and a rise in both investment and operational inefficiencies. This study not only contributes to the ongoing debate about the implications of staggered boards but also sheds new light on the associated agency costs.

Dynamic equilibrium with insider information and general uninformed agent utility

Dynamic equilibrium with insider information and general uninformed agent utility

Why cartel participation leads to financial statement fraud and market abuse

ABSTRACT In an attempt to hide from the competition authorities colluding firms risk committing financial statement fraud and market abuse. When colluding managers set the conditions for their cartel the resulting increase in profitability and ability to pay outstanding debt enables the firms to attract more investors, get access to larger loans and at a lower interest rate. The natural reluctance to disclose the firm’s cartel participation creates financial reports with misleading content, increases the likelihood of insider dealing and the ability to attract more funds diverts needed capital from otherwise more eligible firms and will endanger the integrity and efficient functioning of the financial markets. The conclusion is that firms and individuals involved in cartel offences should be investigated for financial statement fraud and market abuse although when persons may be subject to criminal sanctions it will decrease the attractiveness for individuals to use the leniency framework.

Do Proprietary Costs Deter Insider Trading?

Do Proprietary Costs Deter Insider Trading?

Internal information asymmetry and power distance

Using the difference in insider trading profitability between top and lower-level managers to proxy for firms’ internal information asymmetry, we show that power distance increases internal information asymmetry in an international sample of 10,103 firms across 22 economies from 2003 to 2018. Furthermore, we find that this positive impact is lessened for firms with less complexity, more female directors on board, or an internal CEO promoted from within the firm. Moreover, we show that a country’s high-quality formal institutions lessen the role that a country’s culture of power distance plays in escalating internal information asymmetry. Our main conclusions remain valid after taking into account robustness and endogeneity issues.

White collar crime identification in India: A Critical study

White-collar crime poses a significant challenge to the economic and social fabric of India, as it involves non-violent financial offenses committed by individuals or organizations in positions of trust and authority. This research paper critically examines the landscape of white-collar crime identification in India, shedding light on the types of offenses prevalent, the mechanisms employed for detection, and the complex challenges faced by law enforcement and regulatory bodies. The study begins with an exploration of the various types of white-collar crimes observed in the Indian context, including fraud, corruption, embezzlement, money laundering, insider trading, and cybercrimes. Real-life case studies are presented to illustrate these offenses and the methods employed by perpetrators. Detection mechanisms are a central focus of this paper, with an in-depth analysis of financial audits, forensic accounting techniques, and digital monitoring tools used to identify and investigate white-collar crimes. The role of technology, particularly artificial intelligence and data analytics, is examined in enhancing detection capabilities.

Using Machine Learning to Unveil the Dynamics of Insider Trading in Financial Markets

Using Machine Learning to Unveil the Dynamics of Insider Trading in Financial Markets

An event study of potential insider trading in the Saudi stock market

An event study of potential insider trading in the Saudi stock market

Insider Trading Analysis of the Indonesian Capital Market

Insider trading is one of the crucial issues in the capital market that can have a significant impact on market integrity and stability. In Indonesia, the practice of insider trading not only causes losses for investors who do not have access to insider information but can also reduce investor confidence in the capital market as a whole. Research This article will analyze and explain Insider Trading in the Indonesian Capital Market. This study uses notative juridical methods or normative law. The results of this study explain that Insider Trading in the Indonesian Capital Market is contained in Articles 95, 96, 97, 98, 99, and Article 104 which explain that insiders from an issuer of public companies that have inside information are prohibited from buying or selling affects, or companies that make transactions with issuers where they work. The prohibition on the use of insider information is more due to unfair actions against others who are completely unaware of the existence of the information. Investor protection is one very important way because if investors do not get enough protection, they are reluctant to make transactions on the exchange. Without a large number of investors, capital market activities will be weak, and the function of the capital market will not develop, the principle of openness as one of the efforts to protect investors. Such protection efforts will be realized if the implementation of information transparency or full disclosure obligations containing material facts in activities that take place in the capital market in accordance with the purpose of the principle of openness itself, namely to create a fair, efficient and orderly market that protects Investors and helps determine accurate market prices which are all intended for the benefit of Investors or potential Investors.

Quantifying the State of the Art of Electric Powertrains in Battery Electric Vehicles: Comprehensive Analysis of the Tesla Model 3 on the Vehicle Level

Data on state-of-the-art battery electric vehicles are crucial to academia; however, these data are not published due to non-disclosure policies in the industry. As a result, simulation models and their analyses are based on assumptions or insider information. To fill this information gap, we present a comprehensive analysis of the electric powertrain of a Tesla Model 3 Standard Range Plus (SR+) from 2020 with lithium iron phosphate (LFP) cells, focusing on the overall range. On the vehicle level, we observe the resulting range in multiple test scenarios, tracing the energy path from source to sink by conducting different test series on the vehicle dynamometer and through alternating current (AC) and direct current (DC) charging measurements. In addition to absolute electric range tests in different operating scenarios and electric and thermal operation strategies on the vehicle level, we analyze the energy density and the power unit’s efficiency on the component level. These tests are performed through procedures on the chassis dynamometer as well as efficiency analysis and electric characterization tests in charge/discharge scenarios. This study includes over 1 GB of attached measurement data on the battery pack and vehicle level from the lab to the real-world environment available as open-source data.