Stock Price Prediction with Time Series Analysis using Machine Learning (with full Code)

🚀 Are you ready to explore the fascinating world of stock market predictions and elevate your Data Science career to new heights? Let’s dive in and start predicting the future! 📊🌟
[with full Code and Video Explainers]
In this project, you’ll harness the ARIMA (AutoRegressive Integrated Moving Average) 📊, a very popular Time Series Analysis model, to predict stock prices 📈📉.
Through this Project, you will learn Machine Learning – Time Series Forecasting through an emulated case of Predicting future Stock Price based on past Statistical Trends of Stock Price Data.
You will solve the Stock price problem by learning and using a famous Time Series algorithm called ARIMA and also use Auto-ARIMA.

Stock Price Prediction with Time Series Analysis using Machine Learning [with full Code and Video Explainers]

Stocks Prices are a fascinating thing for us. We invest in Stocks of companies which we think will increase in value, thereby making us wealtheir. Generally, the Stock Prices of well performing companies go up gradually making us want to invest in these companies.

One of the intriguing things about Stock Prices is that it is difficult to predict their future prices. They change based on a many factors and for lay persons like us, it is very difficult to predict their change over time. Think of a situation that we know if the price of Reliance Industries will increase for the next one week. If we knew, we will put our money before it increases. But we don’t know that.

One of the features of Stock Prices is that is they are Time Series data, i.e. they change over time, they change everyday. The price movement also follow patterns most of the time.

In this project, we will consider and treat Stock price as a Time Series data with statistical patterns underneath. With that assumption, we will train a Time Series model using the ARIMA Algorithm and use that model to predict future stock prices.