Big data in finance

This submission has been added to the schedule

Submitted Jun 13, 2014

Section: Full talk Technical level: Intermediate

The talk will cover a case study of solving a research problem in algorithmic trading using high frequency data from a stock exchange.

Outline

This talk presents the methodology in a research paper which our group is working on. Link to the release page: http://ifrogs.org/releases/ThomasAggarwal2014_algorithmicTradingImpact.html

The talk will present a case study of how high frequency data was used to analyse the impact of algorithmic trading on (stock) market quality. It will cover the problem statement, issues with finding a solution, the methodology, and the research design which was used to come to a conclusion. The methodology includes statistical techniques such as matching, difference-in-difference regression, and market quality measures.

Speaker bio

I am a Research Programmer in the Finance Research Group at the Indira Gandhi Institute of Development Research, Mumbai. My experience includes working with a startup, a corporate and research groups in Delhi and Mumbai. My areas of interest include high performance computing, high frequency trading, and financial data management.