Faculty profile: Dr. Nikhil Verma

Dr. Nikhil Verma’s research focuses on machine learning methods for volatility forecasting and predictive analytics. He is the author of multiple technical articles exploring model risk, interpretability, and the use of alternative data sources in financial analytics. His best-known publication addresses the pitfalls of overfitting in real-world volatility models.

Dr. Verma’s experience spans both Canadian financial institutions and international analytics teams, where he has led projects on model implementation and audit. He is particularly interested in developing transparent methods that withstand regulatory and peer scrutiny.