Cuckoo optimized SVM for stock market prediction

K. Nirmala Devi · V. Murali Bhaskaran · G.P.Ramesh Kumar

42 citations0/0 files storedInternational Conference on Innovations in Information, Embedded and Communication Systems

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Stock Market Forecasting Methods Metaheuristic Optimization Algorithms Research Hydrological Forecasting Using AI

Abstract

Nowadays stock market is the one of the major sources of raising resources for India and is act as a key driver for economic growth of a country. The stock market forecasting is a very difficult and highly complicated task because it is affected by many factors such as economic conditions, investor's sentiments and political events etc. The stock market series are generally dynamic, nonparametric, noisy and chaotic by nature. Although many soft computing techniques have been widely used, Support Vector Machine (SVM) has gained its popularity and it has outperformed Artificial Neural Network (ANN) also. Even though SVM is novel and performs best in many applications, the practicality of SVM is impacted due to the problems of choosing suitable parameters of SVM (C, σ and ε). The Cuckoo Search (CS) is based on the Swarm Intelligence optimization technique and is very simple to tune the parameters of SVM. The proposed hybrid CS-SVM technique has been proven to be able to generate better results when compared to ANN and SVM in the prediction of the stock price movement.

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References

2011Twitter mood predicts the stock market 2010Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange 2010A novel hybridization of artificial neural networks and ARIMA models for time series forecasting 2014A moving-average filter based hybrid ARIMA–ANN model for forecasting time series data 2011A hybrid stock selection model using genetic algorithms and support vector regression 2007A Hybrid Neurogenetic Approach for Stock Forecasting 2009Efficient prediction of stock market indices using adaptive bacterial foraging optimization (ABFO) and BFO based techniques 2012Support Vector Machines for Prediction of Futures Prices in Indian Stock Market

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