A Talk by Dr. Arun Verma
To explore the value embedded in News & Social Sentiment data, we build three types of equity trading strategies based on sentiment data and show that strategies based on sentiment outperform the corresponding benchmark indexes significantly.
Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph.D from Cornell University in the computer science & applied mathematics.
At Bloomberg, Dr. Verma's work initially focused on Stochastic Volatility Models for Equity/FX Derivatives and Exotics pricing, e.g. Arbitrage free Volatility interpolation, Variance Swaps and VIX Futures/Options pricing and Cross Currency Volatility Surface construction. More recently, he has enjoyed working at the intersection of such areas as data science, innovative quantitative techniques and interactive visualizations for help reveal embedded signals in financial data, e.g., building quant trading strategies for statistical arbitrage.
About the Series
The IAQF's Thalesians Seminar Series is a joint effort on the part of the IAQF (www.iaqf.org) and the Thalesians (www.thalesians.com). The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion.