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Big data in finance
Submitted by Chirag Anand (@chiraganand) on Friday, 13 June 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.
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.
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.