Spoofing and Liquidity in Financial Markets

Student: Boreyko Natalia

Faculty: Faculty of World Economy and International Affairs

Educational Programme: World Economy (Bachelor)

Year of Graduation: 2020

The research aims to detect traders who might use spoofing strategies on the foreign exchange market of the Moscow Stock Exchange. The study will follow a multi-method research design to achieve the purpose including a quantitative analysis of the data provided by the Moscow Stock Exchange and cluster analysis of the data using machine learning algorithms in Python. The quantitative analysis includes computation of realized spread, effective spread, and price impact. The results of the research show that spoofing strategies may be present on the foreign exchange market of the Moscow Stock Exchange. The perceived results might be valuable for further research on spoofing strategies and the improvement of spoofing monitoring systems.

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