Abstract: In this report we get to learn the existing and the new developing methods of stock market prediction. To understand this, we learn about three different approaches: Fundamental analysis, Technical Analysis, and the application of Machine Learning. We find evidence in support of the weak form of the Efficient Market Hypothesis, that the useful information is not present in the historic price but out of sample data may be having an event or result. We show that Fundamental Analysis and Machine Learning can be used as a guide to affect the investor’s decisions. We demonstrate that thereis common problem in Technical Analysis methodology and show that it produces limited useful information. As we get various information based on it, development of algorithmic trading programs areto be done and simulated using Quantopian.

Keywords: Stock Prediction, Data Analysis, Natural Language Processing, Machine Learning.

PDF | DOI: 10.17148/IJARCCE.2023.124208

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