Option Model Calibration Using a Bacterial Foraging Optimization Algorithm

The Bacterial Foraging Optimization (BFO) algorithm is a biologically inspired computation technique which is based on mimicking the foraging behavior of E.coli bacteria. This paper illustrates how a BFO algorithm can be constructed and applied to solve parameter estimation of a EGARCH-M model which is then used for calibration of a volatility option pricing model. The results from the algorithm are shown to be robust and extendable, suggesting the potential of applying the BFO for financial modeling.

• Type: Conference
• Year: 2008
• Where: EVOW
• Authors: Jing Dang, Anthony Brabazon, Michael O'Neill, David Edelman
• Keywords: Artificial Intelligence, Bacterial Foraging Optimization, BFO Algorithm, EVOW 2008, Volatility Option Pricing