Analyse and Predict Indian Stock Market
In this project, I utilized the powerful forecasting library FBProphet to analyze and predict trends in the Indian stock market. By leveraging FBProphet’s advanced time series analysis capabilities, I aimed to uncover valuable insights and make informed predictions.
To streamline the usage of FBProphet for other analysts and researchers, I developed a Python package and published it on the Python Package Index (PIP). This package provides a convenient interface for accessing FBProphet’s functionality and enables smooth integration into existing analysis workflows.
Throughout my analysis, I leveraged a comprehensive dataset consisting of historical stock market data sourced from reputable financial databases. This dataset allowed me to capture the intricacies of the Indian stock market and explore various factors influencing stock prices.
By applying FBProphet’s forecasting techniques to this dataset, I was able to uncover patterns, trends, and potential future movements in the Indian stock market. These insights can be valuable for investors, traders, and financial analysts seeking to make data-driven decisions and optimize their strategies.