Kaveesha Dilshani

University: University of Technology Sydney  

Academic supervisors: 

Distinguished Professor Fang Chen

Dr. Ting Andy Guo

Industry partner: Nasdaq

Thesis Topic


Anomaly Detection in Stock Market data using Deep Learning Models

My thesis topic is Anomaly detection in stock market data using deep learning models. It deals with various anomalies in the stock market data, specifically insider trading. Insider trading is crucial to maintain the market integrity and fairness of trading to all. Detecting this has been done in isolation considering the securities as independent units with no correlation. In my research we are trying to improve the performance of the existing methods by taking into consideration the correlation of data.


About Nasdaq

Nasdaq is a global technology company that delivers world-leading platforms that improve the integrity, transparency and liquidity of the global economy.


What part of the business is the researcher involved in?

Anti-Financial Crime Technology


What questions/problems is the researcher helping to answer/solve?

Improve the performance of the existing system to detect insider trading.