Estimation of option’s volatility based on particle swarm optimization algorithm

Abstract:

Firstly, Black-Scholes option pricing formula is introduced, and the importance of volatility in option pricing is analyzed. Volatility is a critical parameter for option pricing, and option prices are very sensitive to volatility's fluctuation. Then when computing particle's position and velocity, the particle swarm optimization algorithm with the adjustment of global best position is proposed according to these history data of global best positions and mutation operation. Finally, the adjusted particle swarm optimization algorithm is used to look for the approximate value of volatility in European call option on a futures contract in numerical experiments. And compared with related experiment results, the modified algorithm displays better in convergence.