Algorithmic Python Trading

Automated Stock Analysis and Trading Tool Using Python and Jupyter Notebooks

📋 Table of Contents

1. 🤖 Introduction
2. ⚙️ Tech Stack
3. 🔋 Features
4. 🤸 Quick Start
5. 🚀 More

🤖 Introduction

This project is a Python-based algorithmic trading tool leveraging the Jupyter environment. Using data from the S&P 500 stocks and the IEX Cloud API, it assists in making investment decisions by providing insights into stock prices, market capitalization, and suggesting the number of shares to buy based on a user-defined portfolio size. The tool generates a comprehensive report in an Excel format for easy analysis and decision-making.

⚙️ Tech Stack

• Jupyter Notebook
• Python

🔋 Features

👉 Real-Time Stock Data Analysis: Utilize up-to-date stock data from the IEX Cloud API for informed investment decisions.

👉 Portfolio Optimization: Determine the optimal allocation of funds across a diversified portfolio of stocks to maximize returns and minimize risk.

👉 Automated Trading Strategies: Implement algorithmic trading strategies to execute buy and sell orders based on predefined criteria, removing the need for manual intervention.

👉 Customizable Investment Parameters: Tailor trading algorithms to specific investment goals and risk tolerance levels with adjustable parameters and thresholds.

👉 Backtesting Capabilities: Evaluate the performance of trading strategies using historical stock data to refine and improve algorithmic models.

👉 Risk Management Tools: Incorporate risk management techniques such as stop-loss orders and position sizing algorithms to protect against significant losses.

👉 Interactive Visualizations: Visualize portfolio performance, market trends, and trade executions through interactive charts and graphs for better decision-making.

👉 Portfolio Monitoring Alerts: Receive real-time alerts and notifications for significant market events or changes in portfolio performance to stay informed and responsive.

👉 Exportable Reports: Generate comprehensive reports summarizing portfolio holdings, performance metrics, and trade history for analysis and record-keeping purposes.

🤸 Quick Start

Follow these steps to set up the project locally on your machine.

Prerequisites

Make sure you have the following installed on your machine:

• Git
• Python

Cloning the Repository

git clone https://github.com/kingdomOfIT/Algorithmic-Python-Trading.git
cd Algorithmic-Python-Trading

Acquiring API Token

1. Obtain an API token from IEX Cloud.
2. Store your API token securely in a file named secret.py within a folder named secret.

Installation

Install the project dependencies using pip or pip3:

pip install pandas requests xlsxwriter

Running the Project

Follow the steps inside the project and eneter the value of your portfolio

🚀 More

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