Analyzing the Impact of Economic Indicators on Stock Prices Using Python
In this comprehensive tutorial, we will delve into the fascinating world of financial data analysis using Python. Our focus will be on understanding how various economic indicators impact stock prices. We will leverage real-world data, object-oriented programming concepts, and stunning visualizations to build a complete project. By the end of this tutorial, you will have a solid understanding of how to analyze stock prices in relation to economic indicators using Python.
Introduction
Stock prices are influenced by a myriad of factors, including economic indicators such as inflation rates, unemployment rates, and GDP growth. Understanding these relationships can provide valuable insights for investors and analysts. In this tutorial, we will use Python to analyze the impact of selected economic indicators on stock prices. We will download real financial data using the yfinance library and create visually appealing plots to illustrate our findings.
Setting Up the Environment
Before we begin, let’s set up our Python environment. We need to install the necessary libraries. Open your terminal and run the following command:
pip install yfinance numpy pandas matplotlib plotly mplfinance