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Share Market Prediction by using ML

Kajal Pande, Sejal Kankariya, Rujvi Patani, Dipali Bachhav, S. B. Ambhore

Abstract


In this project we analyze existing and new methods of share market prediction. We use three unique approaches at the problem: Fundamental analysis, Technical Analysis, and the application of Machine Learning. We get corroboration in support of the weak form of the coherent Market Hypothesis, that the historic price does not contain useful information but out of sample data may be predictive. The Main Aim behind this project is to guide an investor’s determination by Fundamental Analysis and Machine Learning. We use the Fundamental Analysis methodology that produces only useful information from the given dataset. Based on our Algorithmic analysis trading programs are developed.

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References


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