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The purpose of this study is to review and evaluate the salient features of stock market manipulation in Malaysia. The research questions used are: Who was involved? How it happened? What were the consequences?

This study has been conducted using content and thematic analysis. This study includes multiple sources of information to help establish the stylized facts and it uses cases that have been prosecuted in Malaysia for 2005-2015.

This study presents arguments and empirical data supporting the view that the stock market manipulation was conducted by those in a privileged position and with access to information. Ethical failure, involving greed, self-interest, dishonesty and a preoccupation with a quick profit, could explain why stock market manipulation happened. Manipulation harms legitimate investors, as share prices and earnings of companies are affected.

A better understanding about the prevalence, characteristics and consequences of the market manipulation problems will be useful for stakeholders, investors and policymakers in the financial industry for promoting and maintaining a fair, efficient and transparent stock market.

The originality of this paper lies in examining and presenting interpretations based on contemporary phenomenon within the real-life context of Malaysia. There is little study or literature that focuses on Malaysia, especially in examining stock market manipulation by integrating finance and management perspectives to form a comprehensive understanding of the issue.

This paper attempts to develop a hybrid model using advanced data mining techniques for the detection of Stock Price Manipulation. The hybrid model detailed in this article elucidates the application of a Genetic Algorithm based Artificial Neural Network to classify stocks witnessing activities that are suggestive of potential manipulation.

Price, volume and volatility are used as the variables for this model to capture the characteristics of stocks. An empirical analysis of this model is carried out to evaluate its ability to predict stock price manipulation in one of the largest emerging markets – India, which has a large number of securities and significant trading volumes. Further, the article compares the performance of this hybrid model with a conventional standalone model based on Quadratic Discreminant Function (QDF).

Based on the results obtained, the superiority of the hybrid model over the conventional model in its ability to predict manipulation in stock prices has been established.

The classification by the proposed model is agnostic of the type of manipulation – action‐based, information‐based or trade‐based.

The market regulators can use these techniques to ensure that sufficient deterrents are in place to identify a manipulator in their market. This helps them carry out their primary function, namely, investor protection. These models will help effective monitoring for abnormal market activities and detect market manipulation.

Implementing this model at a regulator or SRO helps in strengthening the integrity and safety of the market. This strengthens investor confidence and hence participation, as the investors are made aware that the regulators implementing market manipulation detection techniques ensure that the markets they monitor are secure and protects investor interest.

This is the first time a hybrid model has been used to detect market manipulation.

This study aims to diagnose the global key contributors in the stock market manipulation studies during the past four decades.

The database search is based on the terms used in the existing body of knowledge. Using the bibliometric tools and techniques on the Scopus database, the study assessed and analysed the productivity of research studies, as well as the influence of the authors, publications, journals, affiliated institutions and countries.

This paper finds the USA as the leading country investigating this area, almost capturing 40% of the research studies in finance, moreover, a huge number of co-authors. Financial crises in the late 1990s and 2008 is observed as one of the main reasons for this intriguing research. The Journal of Finance is spotted as the most persuasive journal with the highest cite score and an unprecedented number of citations. The analysis of keywords engendered that most of the stock market manipulation studies are event-based studies. Seminally unique scientometric analysis revealed that the significance of stock market manipulation was mainly captured by event-based studies, insider trading and pump and dump schemes studies. However, much remained untapped to articulate the bridging scope of technology and media with stock market behaviour and manipulations.

The research only includes the Scopus database, however, incorporates 81% relevant study.

This study reckons that technology-based manipulations are emerging themes in this research field which invites the applied research to have productive outcomes.

The intriguing study incorporates a maximum number of the relevant literature and used a comprehensive technique for the selection of dataset in Scopus.

The purpose of this paper is to examine the influence of major non-economic events, such as the announcement of Greek national parliamentary elections during the period 2000-2009, and search for stock manipulation and methods to detect and recover ill gotten assets. The Financial Sector in Greece is one of the most important and fast growing sectors during recent years and accounts to about 16.17-17.74 per cent of gross domestic product. The ten largest Greek banks listed in the Athens Stock Exchange, accounted to 38.34 per cent of the whole capitalisation of the Athens Stock Exchange during year end 2009.

By using event study methodology and Market Model and analyzing data of all Greek bank stocks prices listed in Athens Stock Exchange, before and after the announcement of four Greek national parliamentary elections during period 2000-2009, we find interesting results about stock market manipulation.

Using daily data from the Athens Stock Exchange, the results of this paper claim that the four Greek national parliamentary elections during the period 2000-2009, had no statistically significant effect on the Greek banks stocks. The results show that Cumulative Average Abnormal Returns (CAARs) were slightly positive or negative for Greek banks’ stocks, but not statistically significant in 5 and 10 per cent confidence levels. Results show no manipulation effect in banks’ stocks even if single-party governments in Greece caused elections early, sudden or even opportunistic timing, having an incentive to attempt to manipulate stocks to increase their chances of re-election.

Results show that CAARs were slightly positive or negative for Greek banks stocks, but not statistically significant in 5 and 10 per cent confidence levels, but when illicit funds or assets have been acquired from stock manipulation, as small as can be, then one fact remains constant. Proceeds from illicit activities must be disguised in some way to avoid being discovered and then being recovered. Especially, during current the financial crisis, debt crisis and the extraordinary liquidity support measures taken by the European Central Bank (ECB), International Monetary Fund (IMF) and European Commission to support Greek economy, using methods to detect and recover ill gotten assets are extremely important. Indirect methods such as net worth analysis, bank deposit analysis, expenditure method or sources and application of funds analysis, to detect ill gotten assets, and then when ill gotten income and assets from bank stock manipulation are found, a restraining order or court order will help to recovery assets by freezing and finally confiscating them by two types of forfeiture – criminal and civil forfeitures. Establishing a code of conduct informing employees of the risks and consequences of insider trading, creating a culture of honesty and high ethics and implementing Controlled Foreign Corporation legislation to cope with off-shore companies trading, can help to recover ill gotten assets.

The paper examines if there is banks stocks manipulation around announcement of Greek national parliamentary elections during the period 2000-2009; suggesting methods to detect and recover ill gotten assets and improving the current position of the Greek economy. Findings offer important positive implications for investors, political analysts and society as a whole, as Greek banks stocks show that they are not subject to political risk and manipulation and that there are methods to detect and recover ill gotten assets. A stable bank sector is prerequisite for economy growth.

The purpose of this paper is to investigate the July 2007 introduction of a pre‐close call auction on the New Zealand stock market and its effect on share pricing quality and market manipulation.

Market quality was tested using the methodology of Pagano and Schwartz, which is based on changes in market model R²s. Closing price manipulation is detected by comparing mean bid‐ask spread characteristics of the periods before and after the introduction of the pre‐close call auction.

The closing call auction improves the quality of share pricing and reduces the incidence of market manipulation.

The paper confirms the effectiveness of the changes made to the method of closing the market for all firms in the market.

The paper extends knowledge of the effectiveness of closing call‐auctions. It is the first study in a low‐liquidity market and of shares with very low liquidities. Such markets have lower pricing quality and are more vulnerable to market manipulation. The study establishes the effectiveness of closing auctions in this environment.

The paper aims to investigate order-based manipulation that consists of order-placing strategies.

Using the bid and ask record provided by Hong Kong Exchanges and Clearing Limited, a Level II dataset, the paper develops a methodology to obtain cancelled orders during regular trading hours. The paper examines the cancelled orders and potential order-based manipulation activities, as well as the corresponding behavior of different groups of stocks.

Empirical results show that the relationship between order cancellation and order-based manipulation is strong and deserves more attention.

The methodology can also be used by regulators and authorities to monitor suspicious activities in the market. This paper also suggests that analysis on high-frequency data does improve the understanding of trading activities in the stock market.

Although the financial markets are regulated by robust systems and rules that control their efficiency and try to protect investors from various manipulation schemes, markets still suffer from frequent attempts to mislead or misinform investors in order to generate illegal profits. The impetus to effectively and systematically address such schemes presents many challenges to academia, industry and relevant authorities. This paper aims to discuss these issues.

The paper describes a case study on fraud detection using data mining techniques that help analysts to identify possible instances of touting based on spam e‐mails. Different data mining techniques such as decision trees, neural networks and linear regression are shown to offer great potential for this emerging domain. The application of these techniques is demonstrated using data from the Pink Sheets market.

Results strongly suggest the cumulative effect of “stock touting” spam e‐mails is key to understanding the patterns of manipulations associated with touting e‐mail campaigns, and that data mining techniques can be used to facilitate fraud investigations of spam e‐mails.

The approach proposed and the paper's findings could be used retroactively to help the relevant authorities and organisations identify abnormal behaviours in the stock market. It could also be used proactively to warn analysts and stockbrokers of possible cases of market abuse.

This research studies the relationships between the cumulative volume of spam touts and a number of financial indicators using different supervised classification techniques. The paper aims to contribute to a better understanding of the market manipulation problem and provide part of a unified framework for the design and analysis of market manipulation systems.

The purpose of this paper is to analyze a data set from a brokerage firm to find possible spoofing cases in ten stocks from the Ibovespa index. The studies proposed concerned the parameters used in the search for the practice, the frequency of occurrences during the negotiation period, the impact on the price caused by the size of the spoofing order and the correlation between the stock's liquidity and the number of occurrences.

By using intraday orders flows, the authors are able to reassemble the order book and perform an analysis of potential market manipulation.

The authors found six possible cases, all of them happened in the beginning or end of the negotiation period, confirming that there is a window of opportunity for the practice when there is greater uncertainty related to the stock's price. Moreover, they found that in the less liquid stocks, it was necessary to place greater spoofing orders aiming to narrow the wider spread.

A methodology for spoofing detection that can be replicated by brokerage firms and other researchers was developed.

The study contributes to the literature of capital market regulation by suggesting best practices for regulators and self-regulatory entities to avoid a predatory market practice.

The authors present an algorithm and parameters for detecting spoofing; other papers are not practical orientated.

The purpose of this paper is to empirically examine the impact of closing mechanism changes on market quality, investor trading behavior and market manipulation in the Shanghai stock market.

A dummy variable is constructed indicating whether the closing mechanism is call auction or continuous auction. Market quality is measured from aspects of liquidity, volatility and price continuity; investor trading behavior is scaled by order timing and order aggressiveness, and a price deviation indicator is the proxy of manipulation. Using panel regression, this study examines the impact of closing mechanism changes based on intraday transaction data from the Shanghai stock market.

The conclusions are as follows: First, market quality improves after the closing mechanism is reformed in terms of liquidity, volatility and price continuity. Second, order strategy changes significantly in the closing call market, and investors trade more aggressively in the continuous trading period before closing. Third, the closing call mechanism restrains the closing price manipulation and thus prompts an efficient closing price.

This paper examines the policy effects of closing mechanism changes from aspects of market quality, trading behavior and price manipulation, providing pieces of evidence for trading mechanism design and market supervision in emerging markets.

The purpose of this study is to empirically test the role of heterogeneous investor’s, i.e. institutional investors, individuals and insiders in deteriorating market integrity.

The research is conducted by examining the participants of 244 market manipulation cases of East Asian emerging and developed financial markets for the period of 2001–2016. The empirical analysis is conducted using panel logistic regression.

The results show that firms with higher institutional ownership are most likely to be manipulated in both markets. Insiders are potential manipulators in developed markets and deteriorate market integrity. In contrast, individual investors behave differently in both markets. In developed markets, firms with high individual ownership are less likely to be manipulated while in emerging markets, firms with individual ownership are more prone to manipulation because of substantial participation by individual investors which invites manipulative practices. Additionally, the authors found that firms with a higher proportion of passive institutional investors are less likely to be manipulated in emerging markets.

This study contributes to the existing literature by identifying the potential manipulators in the financial markets who deteriorate market integrity with the additional focus of subdivision of institutional investors as active institutional investors and passive institutional investor. The findings are helpful for regulators in designing policies to ensure market integrity and to enforce the role of institutional investors and insiders.