Exploratory Data Analysis(EDA) of Trading Strategy and Stocks Price

Exploratory Data Analysis is a method of understanding given data set and finding out insigts with help of statistical graphs and data analysis tools. Purpose of EDA is to get a relationship, patterns between different variables of datasets which will help us draw big picture out of complex datasets.

To perform EDA,It requires knowldge of statistics, visualization techniques and data-analysis tools like numpy, pandas, seaborn, plotly, matplotlib. Also it important to present it in a intersting way for better understanding of insights to the viewers.

Introduction:

• In this project we will perform Exploratory Data Analysis on Stocks Close Price and Stock Trading Strategy Performance. Trading strategy is based on MACD and Stochastic Oscillator indicator.
• Backtesting of strategy is performed on Stock Close data for given period of time and returns for each stock will be calculated.
• Calculated strategy return then analysed and visualized to answer the questions.

Steps to follow:

• Install and Import required libraries.
• Access Google drive to get stocks data csv files.
• Data processing & creating stocks data dataframe using pandas.
• Trading Strategy Explained.
• Technical Analysis / Indicators.
• Key Performance Indicators.
• Asking and answering interesting questions.
• Summary
• Future Work
• References

Install and Import required libraries.