A Hybrid Forecasting Model for Option Price Prediction using Machine Learning Technique

A hybrid model is presented in this paper that is aiming to forecast the option prices that are analyzed in the data set of different banks. A new move is proposed by this paper that is forecasting the option price with the use of ANN model which is optimizing the hybrid swarm optimization. The data set of the NSE India banking sector has been utilized for the calculation of an effective algorithm for forecasting the option price with the help of this ANN model. For forecasting the option price, the methods which are used in this paper are SOM (self organization map), RBF (Radial Basis Function) and the Hybrid Swarm Optimization system. The hybrid swarm intelligence algorithm reduces the variation of prices and proceeds the data for the prediction and used cascaded neural network-based classifier for the purification of data. Two results are combined so that the option price prediction can be achieved. A comprehensive description of the option price is offered with a combined forecasting model that is developing the accuracy of the option price forecasting, also the reflection of the stock market trends are seen in this investigation and the model also has the capacity to offer advices to the investors that are connected with the productive speculation.