fractal power laws and scaling will be explained. The main part focuses on the estimation of the tail index as a scaling …

three market regimes. A consistent parametric framework of stochastic volatility is used. All empirical market utility …

The volatility implied by observed market prices as a function of the strike and time to maturity form an Implied … Volatility Surface (IVS). Practical applications require reducing the dimension and characterize its dynamics through a small … investigating long range dependence in the factor loadings series. Our result reveals that shocks to volatility persist for a very …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …

financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … to forecast financial markets volatility. The real data in this study uses British Pound-US Dollar (GBP) daily exchange … examined to the free parameters. Keywords: recurrent support vector regression ; GARCH model ; volatility forecasting …

, especially on the BS implied volatility. Implied binomial trees (IBT) models capture the variations of the implied volatility … known as "volatility smile". They provide a discrete approximation to the continuous risk neutral process for the underlying … Barle and Cakici (BC). After the formation of IBT we can estimate the implied local volatility and the state price density …