Dr. Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph.D from Cornell University in the areas of computer science & applied mathematics.
At Bloomberg, Mr. Verma's work initially focused on Stochastic Volatility Models for Derivatives and Exotics pricing, e.g. Arbitrage free Volatility interpolation, Variance Swaps & VIX pricing and Cross Currency Volatility Surface construction.
More recently, he has enjoyed working at the intersection of areas such 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 using tools such as predictive analytics & machine learning.
He has spoken at various industry and academic events, recent ones include the Thalesians Seminar, Risk's Quant Europe conference, Derivatives & Risk Management conference, International conference on computational science etc.