"DEEP LEARNING PROJECT"

Ever wondered about stock market prediction using deep learning!

An SVM-based approach is proposed for stock market trend prediction. The proposed approach consists of two parts: feature selection and prediction model. In the feature selection part, a correlation-based SVM filter is applied to dates and select a good subset of financial indexes . And the stock indicators are evaluated based on the dates. In the prediction model part, we use all models rbf,poly,linear regression techinques to get optimal prediction. I trained my model on BHARTI Airtel BSE stock,India based on two years of data Our classifier will take date as feature_test to predict future price It will plot graph based on three model so we look at the graph and make educated prediction.

Platform required: Python Libraries required: numpy , sckit-learn , matplot

This is sample project based on only one stock BHARTI AIRTEL

""FUTURE MODEL"" In Future Model our idea is to make an SVM-based approach is proposed for stock market trend prediction with slight changes.

The proposed approach also consists of two parts: feature selection and prediction model. In the feature selection part, a correlation-based SVM filter is applied to rank and select a good subset of financial indexes. And the stock indicators are evaluated based on the ranking.

In the prediction model part, a so called quasi-linear SVM is applied to predict stock market movement direction in term of historical data series by using the selected subset of financial indexes as the weighted inputs. The quasi-linear SVM is an SVM with a composite quasi-linear kernel function, which approximates a nonlinear separating boundary by multi-local linear classifiers with interpolation.

Experimental results on BSE(Nifty) Indian stock market datasets demonstrate that the proposed SVM-based stock market trend prediction method produces better generalization performance over the conventional methods in terms of the hit ratio. Moreover, the experimental results also show that the proposed SVM-based stock market trend prediction system can find out a good subset and evaluate stock indicators which provide useful information for investors.

We will also try to make an graphical oriented user interface in android.