A detailed study of Machine Learning, Data Wrangling, Data Visualization and other techniques for Portfolio Management of Stocks.
- Data cleaning and processing of Stock Price Data using Pandas.
- Data visualization for stock price data.
- Analysis and categorization of different stocks.
- Building a Trade Call Classifier.
- Study of Mordern Portfolio Theory for optimization and allocation of capital to different stocks in a portfolio.
To study about Machine Learning for Trading refer to this free lecture series on Quantopian.
This module is used for cleaning, sorting and processing of stock data using Pandas Dataframe.
This module includes data visualization and basic analysis of stock price data.
This module is used to categorize the different stocks using Regression Analysis.
In this module a Trade Call Classifier is built using different type of bands.
In this module Optimal Capital Allocation is done using Efficient Frontier Method after study of Mordern Portfolio Theory.
In this module Clusterring of Stocks is shown using KNN Clustering Method.
Requirements to Run this Project:
- Python 3
- Numpy
- Matplotlib
- Pandas
- scikit-learn