Data mining solutions: methods and tools for solving real-world problems
Data mining solutions: methods and tools for solving real-world problems
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Early detection of insider trading in option markets
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Marking the Close analysis in Thai Bond Market Surveillance using association rules
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A neuro-evolutionary approach to intraday financial modeling
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Hi-index | 12.05 |
This paper addresses challenges relating to applying data mining techniques to detect stock price manipulations and extends previous results by incorporating the analysis of intraday trade prices in addition to closing prices for the investigation of trade-based manipulations. In particular, this work extends previous results on the topic by analysing empirical evidence in normal and manipulated hourly data and the particular characteristics of intraday trades within suspicious hours. Furthermore, the analytical models described in this paper reinforce the results of previous market manipulation studies that are based on traditional statistical and econometrical methods providing an alternative portfolio of methods and techniques originating from the data mining and knowledge discovery areas. With the application of the analytical approach described in this paper, it is possible to identify new fraud manipulation pattern characteristics encoded as decision trees which can be readily employed in fraud detection systems. The paper also proposes a number of policy recommendations towards increasing the effectiveness of the operational processes executed by stock exchange fraud departments and regulatory authorities.