[02487] Asset Forecasting Using Geometric Brownian Motion and Variance Gamma Models
Session Time & Room : 3E (Aug.23, 17:40-19:20) @E505
Type : Contributed Talk
Abstract : The basic assumption in the Black-Scholes-Merton model is log returns assets normally distributed. In reality, asset price movements are so fluctuating that the data is not normally distributed. This paper proposes a way to forecast using the variance gamma (VG) model. The VG model has three parameters to control volatility, skewness, and kurtosis. We compare results with the geometric Brownian motion (GBM) model. The accuracy of the model used the mean absolute percentage error (MAPE).
