Price manipulation fraud detection by Intelligent Visual Fraud surveillance system

Kasgari, Abbas Bagherian; Taghavifard, Mohammad Taghi; Kharazi, Saeideh Golchin

doi:10.1109/codit.2019.8820499

Cited by 5 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By using a data division of (60:15:25) between (training:validation:testing), the ensemble ANN produced 96% accuracy, followed by kNN, which is the second best classifier with only 88% accuracy. The same ensemble approach was used in [65], in which multiple models were designed for each manipulation case. Some of the models were dedicated to different tasks, including price change, bilateral trade, and trade basket ratio, which were then combined to produce anomaly detection to sift out the early candidates for manipulation cases.…”

Section: Stock Market Manipulation Detection: Supervised Conventional...mentioning

confidence: 99%

A Survey on Stock Market Manipulation Detectors Using Artificial Intelligence

Zulkifley¹,

Munir²,

Sukor³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

A well-managed financial market of stocks, commodities, derivatives, and bonds is crucial to a country's economic growth. It provides confidence to investors, which encourages the inflow of cash to ensure good market liquidity. However, there will always be a group of traders that aims to manipulate market pricing to negatively influence stock values in their favor. These illegal trading activities are surely prohibited according to the rules and regulations of every country's stock market. It is the role of regulators to detect and prevent any manipulation cases in order to provide a trading platform that is fair and efficient. However, the complexity of manipulation cases has increased significantly, coupled with high trading volumes, which makes the manual observations of such cases by human operators no longer feasible. As a result, many intelligent systems have been developed by researchers all over the world to automatically detect various types of manipulation cases. Therefore, this review paper aims to comprehensively discuss the state-of-theart methods that have been developed to detect and recognize stock market manipulation cases. It also provides a concise definition of manipulation taxonomy, including manipulation types and categories, as well as some of the output of early experimental research. In summary, this paper provides a thorough review of the automated methods for detecting stock market manipulation cases.

show abstract

Section: Stock Market Manipulation Detection: Supervised Conventional...mentioning

confidence: 99%

A Survey on Stock Market Manipulation Detectors Using Artificial Intelligence

Zulkifley¹,

Munir²,

Sukor³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Therefore, many of the financial crimes in the stock market has been designated as a criminal offense rather civil offense. A vast literature is available on stock market returns, volatility, determinants (Chitenderu et al , 2014; Ghufran et al , 2016; Farias Nazário et al , 2017; Danışoğlu and Güner, 2018); abuses in the market (Withanawasam et al , 2013; Huang and Cheng, 2015; Neupane et al , 2017; Riyanto and Arifin, 2018); its detection (Cao et al , 2013; Golmohammadi et al , 2014; Golmohammadi and Zaiane, 2015; Martínez-Miranda et al , 2016; Zhai et al , 2017; Kasgari et al , 2019; Leangarun et al , 2019; Shi et al , 2019) and the stock market enforcement and regulations (Comerton-Forde and Putniņš, 2014; Plachouras and Leidner, 2015; Shi et al , 2018; Jordan and Rand, 2019; Kwabi et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Assessing four decades of global research studies on stock market manipulations: a sceintometric analysis

Akram

Ramakrishnan

Naveed

2021

JFC

View full text Add to dashboard Cite

Purpose This study aims to diagnose the global key contributors in the stock market manipulation studies during the past four decades. Design/methodology/approach 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. Findings 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. Research limitations/implications The research only includes the Scopus database, however, incorporates 81% relevant study. Practical implications This study reckons that technology-based manipulations are emerging themes in this research field which invites the applied research to have productive outcomes. Originality/value The intriguing study incorporates a maximum number of the relevant literature and used a comprehensive technique for the selection of dataset in Scopus.

show abstract

A comprehensive review on insider trading detection using artificial intelligence

Priyadarshi,

Kumar

2024

J Comput Soc Sc

View full text Add to dashboard Cite

Price manipulation fraud detection by Intelligent Visual Fraud surveillance system

Cited by 5 publications

References 11 publications

A Survey on Stock Market Manipulation Detectors Using Artificial Intelligence

A Survey on Stock Market Manipulation Detectors Using Artificial Intelligence

Assessing four decades of global research studies on stock market manipulations: a sceintometric analysis

A comprehensive review on insider trading detection using artificial intelligence

Contact Info

Product

Resources

About