Stock Market Analysis we analyzing the current and historical trends in the stock market to make future buying and selling decisions, and modeling time-series data to make future decisions.
Stock Market Analysis using Python
Stock Market Analysis means analyzing the current and historical trends in the stock market to make future buying and selling decisions. Stock market analysis is one of the best use cases of Data Science in finance. So, if you want to learn to analyze the stock market, this article is for you. In this article, I will take you through the task of Stock Market Analysis using Python.
Time Series Forecasting with ARIMA
Time Series Forecasting means analyzing and modeling time-series data to make future decisions. Some of the applications of Time Series Forecasting are weather forecasting, sales forecasting, business forecasting, stock price forecasting, etc. The ARIMA model is a popular statistical technique used for Time Series Forecasting. If you want to learn Time Series Forecasting with ARIMA, this article is for you. In this article, I will take you through the task of Time Series Forecasting with ARIMA using the Python programming language.
What is ARIMA? ARIMA stands for Autoregressive Integrated Moving Average. It is an algorithm used for forecasting Time Series Data. ARIMA models have three parameters like ARIMA(p, d, q). Here p, d, and q are defined as:
p is the number of lagged values that need to be added or subtracted from the values (label column). It captures the autoregressive part of ARIMA. d represents the number of times the data needs to differentiate to produce a stationary signal. If it’s stationary data, the value of d should be 0, and if it’s seasonal data, the value of d should be 1. d captures the integrated part of ARIMA. q is the number of lagged values for the error term added or subtracted from the values (label column). It captures the moving average part of ARIMA. I hope you have now understood the ARIMA model. In the section below, I will take you through the task of Time Series Forecasting of stock prices with ARIMA using the Python programming language.