• Harjit Singh

Stock market prediction has always been an interesting and very important multi-disciplinary research field combining finance and computer science. From the many decades the prediction in stock market is being done based on the fundamental analysis and technical analysis which utilizes the historical financial data for prediction. In the recent years machine learning techniques are innovated which can prove to be very robust method for predicting stock market. Both the traditional and modern methods can be combined together to get best of the both for more accurate prediction in stock market. This will be a hybrid approach for stock market prediction where the benefits of both the approaches will be taken into consideration. This paper discusses about advantages of using these hybrid models and reviews the latest research in this approach including challenges faced to the approach.

Machine Learning Models, Statistical Models, Hybrid Models, Stock Market, Prediction, CNN, SVM, Multi-Model Methods, Stock Market and Computers.

"Combining Machine Learning and Statistical Models: The Hybrid Models for Stock Market Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 2, page no.463-466, February-2018, Available :http://www.jetir.org/papers/JETIR1802365.pdf

"Combining Machine Learning and Statistical Models: The Hybrid Models for Stock Market Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 2, page no. pp463-466, February-2018, Available at : http://www.jetir.org/papers/JETIR1802365.pdf