Sonam Srivastava

Quant Analyst

How Machine Learning is transforming Finance

Machine learning is slowly but surely transforming the way we trade, in this presentation I want to highlight how this transformation is taking place citing examples from personal experiences and beyond. I would then like to highlight the deep learning techniques and research I think are most relevant to training a model based on financial data and their significance. I would like to share some insight into understanding financial data and the value added by understanding the features. I would also talk about the thrill of using ML in finance – how a small optimization can bring about significant alpha! I would conclude by envisioning the trading rooms of the future based on the transformation.

Sonam works as a Quant Analyst for the HSBC Central Risk Book desk. She does short term stock return prediction and quantitative portfolio construction research for building optimal systematic trading strategies. Her work involves feature exploration and supervised learning using econometric time series models. Prior to this Sonam worked at the Algorithmic Trading Desk at Edelweiss for 4 years where she built high frequency execution and arbitrage algorithms for the brokerage house that traded a significant percentage to India’s total traded volume. Sonam has been involved in deep learning research since her graduation years in IIT Kanpur, which she graduated from in 2010.



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