Abstract Advantages and limitations of the existing models for practical forecasting of stock market volatility have been identified. Support vector machine (SVM) have been proposed as a complimentary volatility model that is capable to extract i

Including the least squares method, the SVM, neural networks, 1 _k neighbor method, ECG data and includes source code written in MATLAB, It can be directly calculated multi-fractal spectrum.