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.
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This module includes data visualization and basic analysis of stock price data.
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This module is used to categorize the different stocks using Regression Analysis.
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In this module a Trade Call Classifier is built using different type of bands.
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In this module Optimal Capital Allocation is done using Efficient Frontier Method after study of Mordern Portfolio Theory.
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In this module Clusterring of Stocks is shown using KNN Clustering Method.
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Requirements to Run this Project:
- Python 3
- Numpy
- Matplotlib
- Pandas
- scikit-learn