Welcome to the Market Profile Analysis project repository! In this project, we have utilized Python along with the yfinance library to perform a Market Profile analysis technique on stock data. This README file will provide you with an overview of the work done in this project and guide you through the project structure and usage.
Market Profile Analysis is a powerful technique used by traders and investors to understand the distribution of trading activity within specific price levels over a given period. It helps in identifying key price levels, potential support and resistance zones, and can be a valuable tool in making informed trading decisions.
Here are the main highlights of this project:
-
Data Retrieval: We used the yfinance library to fetch historical stock data. This allowed us to access a wide range of financial data easily.
-
Data Preprocessing: We employed NumPy and Pandas to clean and preprocess the raw data. This included handling missing values, resampling data if necessary, and ensuring it was in a suitable format for analysis.
-
Market Profile Distribution: The core of this project is the creation of a Market Profile distribution based on the stock data. This distribution helps us visualize the concentration of trading activity at different price levels.
-
Data Visualization: To gain insights and understand trends within the stock data, we utilized Seaborn and Matplotlib libraries for data visualization. These libraries allowed us to create various plots and charts to aid in our analysis.