Exploratory Data Analysis Of Trading Strategy And Stocks Price
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.
- 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.
- Future Work
Install and Import required libraries.
!pip install plotly --upgrade --quiet
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