A neural network approach to understanding implied volatility movements
Presentation by John Hull, Maple Financial Professor Of Derivatives & Risk Management, Joseph L. Rotman School of Management at University Of Toronto, from QuantMinds International 2019
“Implied volatility change is negatively correlated with asset prices”, John Hull said, kicking off the presentation of his recent work on volatility surface movements, co-authored by Jay Cao and Jacky Chen.
Understanding volatility surface movements can test whether a stochastic volatility model is consistent with the market; it can help traders adjust prices; and it can help improve delta hedging. In his work, Hull attempts to use machine learning – artificial neural networks, in particular – to improve on previous models.