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Applying machine learning and textual analysis on macro and micro determinants to predict stock returns

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Stock-Returns-Prediction-ML-Textual-Analysis

Applying machine learning and textual analysis on macro and micro determinants to predict stock returns

Getting Started

  1. Make sure your python is configured properly
    • In the .ipynb file, make sure the top right python library is the same as where you install your python libraries

There are 4 main folders : Data , Data-Processed , Data-Collection , Data-Model and Data-Report


1. Data

Contains Stock and Global data. These unstructured data are extracted and preprocessed from investing.com and scraped using BeautifulSoup. Each csv file contains 3 columns : Date, Title and Text

Stock

Name Rows
Apple 2289
Meta 2465
Tesla 1776

Global

Name Rows
World
Politics
Coronavirus

2. Data-Processed

Vader Analysis is performed on both stock and global data

Date Title Text Processed Title Processed Text Sentiment Title Sentiment Text Positive Title Positive Text

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Applying machine learning and textual analysis on macro and micro determinants to predict stock returns

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