From c60089f12174ac972477ae8bce90c829c54fb4bc Mon Sep 17 00:00:00 2001 From: Dagmawi Teferi Date: Sun, 15 Dec 2024 22:15:27 -0500 Subject: [PATCH] start task-3 --- README.md | 45 ++++++++++++++++++++------------------------- scripts/task2.py | 22 ---------------------- 2 files changed, 20 insertions(+), 47 deletions(-) delete mode 100644 scripts/task2.py diff --git a/README.md b/README.md index b08b217..8f813b0 100644 --- a/README.md +++ b/README.md @@ -1,28 +1,26 @@ -<<<<<<< HEAD # Financial News Sentiment and Stock Market Correlation Analysis -This project focuses on the detailed analysis of financial news sentiment and its correlation with stock market movements. By leveraging natural language processing (NLP) techniques, sentiment analysis, and advanced financial analytics, this analysis aims to uncover meaningful insights that can enhance financial forecasting accuracy. The ultimate goal is to develop innovative strategies that utilize news sentiment as a predictive tool for stock market trends. -======= +# This project focuses on the detailed analysis of financial news sentiment and its correlation with stock market movements. By leveraging natural language processing (NLP) techniques, sentiment analysis, and advanced financial analytics, this analysis aims to uncover meaningful insights that can enhance financial forecasting accuracy. The ultimate goal is to develop innovative strategies that utilize news sentiment as a predictive tool for stock market trends. + # Financial News Sentiment and Stock Market Correlation Analysis - Task 1 This branch focuses on **Task 1: Exploratory Data Analysis (EDA)**, where we perform initial analysis on the financial news dataset to uncover insights and set the foundation for further analysis. ->>>>>>> task-1 + +> > > > > > > task-1 ## Table of Contents 1. [Project Overview](#project-overview) 2. [Business Objective](#business-objective) 3. [Dataset Overview](#dataset-overview) -<<<<<<< HEAD + <<<<<<< HEAD 4. [Tasks and Deliverables](#tasks-and-deliverables) 5. [Installation](#installation) 6. [Usage](#usage) 7. [Contributing](#contributing) -8. [License](#license) -======= -4. [Task 1 Overview](#task-1-overview) ->>>>>>> task-1 - +8. # [License](#license) +9. [Task 1 Overview](#task-1-overview) + > > > > > > > task-1 ## Project Overview @@ -31,6 +29,7 @@ This project focuses on analyzing a large corpus of financial news data to disco ## Business Objective Nova Financial Solutions aims to enhance its predictive analytics capabilities to significantly boost its financial forecasting accuracy and operational efficiency through advanced data analysis. This involves: + - Performing sentiment analysis on financial news headlines. - Establishing statistical correlations between sentiment scores and stock price movements. - Providing actionable insights and investment strategies based on the analysis. @@ -38,6 +37,7 @@ Nova Financial Solutions aims to enhance its predictive analytics capabilities t ## Dataset Overview The Financial News and Stock Price Integration Dataset (FNSPID) contains: + - **headline**: Title of the news article. - **url**: Direct link to the full news article. - **publisher**: Author/creator of the article. @@ -45,17 +45,20 @@ The Financial News and Stock Price Integration Dataset (FNSPID) contains: - **stock**: Stock ticker symbol. <<<<<<< HEAD + ## Tasks and Deliverables ### Week 1: - **Task 1: Exploratory Data Analysis (EDA)** + - Descriptive Statistics - Text Analysis (Sentiment Analysis & Topic Modeling) - Time Series Analysis - Publisher Analysis - **Task 2: Quantitative Analysis using PyNance and TA-Lib** + - Load and prepare stock price data - Apply technical analysis indicators - Visualize the data @@ -66,20 +69,26 @@ The Financial News and Stock Price Integration Dataset (FNSPID) contains: - Calculate daily stock returns and correlation with sentiment scores ### Deliverables: + - **Interim Report**: Summary of initial findings and partial progress (max 3 pages). - **Final Report**: Detailed analysis and insights (up to 10 pages). ## Installation 1. **Clone the Repository**: + ```bash git clone https://github.com/dagiteferi/Financial-News-Sentiment-Stock-Market-Correlation-Analysis.git cd Financial-News-Sentiment-Stock-Market-Correlation-Analysis + ``` + 2. **Install Dependencies**: + ```bash pip install -r requirements.txt ``` + ** Contributing** Contributions are welcome! Please fork the repository and use a feature branch. Pull requests are warmly welcomed. @@ -106,22 +115,11 @@ Contributions are welcome! Please fork the repository and use a feature branch. ``` 7. **Create a Pull Request**: Go to the repository on GitHub, switch to your branch, and click the `New Pull Request` button. Provide a detailed description of your changes and submit the pull request. - - **License** Distributed under the MIT License. See LICENSE for more information. - - - - - - - - - - ======= + ## Task 1 Overview ### Task 1: Exploratory Data Analysis (EDA) @@ -134,6 +132,3 @@ Distributed under the MIT License. See LICENSE for more information. ### Deliverables for Task 1: - **EDA Report**: Summary of initial findings and insights from the exploratory data analysis. - - - diff --git a/scripts/task2.py b/scripts/task2.py deleted file mode 100644 index c851874..0000000 --- a/scripts/task2.py +++ /dev/null @@ -1,22 +0,0 @@ -import sys -import os - -# Add src directory to the Python path -src_path = os.path.abspath(os.path.join(os.path.dirname(__file__), '../src')) -sys.path.append(src_path) - -import data_preprocessing as dp -import indicators as ind -import visualization as vis - -# Example usage -def main(): - file_path = '../data/amazon.csv' - data = dp.load_data(file_path) - data = ind.calculate_indicators(data) - vis.plot_moving_averages(data, 'Stock_price_moving_average.png') - vis.plot_rsi(data, 'relative_strength_index.png') - vis.plot_macd(data, 'macd_signals.png') - -if __name__ == '__main__': - main() \ No newline at end of file