An Outlier Detection Method Based on Voronoi Diagram for Financial Surveillance

Outlier detection has wide application for financial surveillance. The traditional outlier detection method is based on statistical models, such as ARMA and ARCH, which require special hypotheses. The statistical models are inappropriate to apply to complex financial data, such as high frequency data. This paper introduces a new data mining method to detect outliers for financial surveillance. Based on the Voronoi diagram, we propose a novel outlier detection method, which called Voronoi based outlier detection (VOD), to provide efficient and effective outlier detection in financial data.