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10 Commits
data
data
 
 
testcases_mc2p1
testcases_mc2p1
 
 
.gitignore
.gitignore
 
 
01-01 Reading and plotting stock data.ipynb
01-01 Reading and plotting stock data.ipynb
 
 
01-02 Working with multiple stocks.ipynb
01-02 Working with multiple stocks.ipynb
 
 
01-03 The power of NumPy.ipynb
01-03 The power of NumPy.ipynb
 
 
01-04 Statistical analysis of time series.ipynb
01-04 Statistical analysis of time series.ipynb
 
 
01-05 Incomplete data.ipynb
01-05 Incomplete data.ipynb
 
 
01-06 Histograms and scatter plots.ipynb
01-06 Histograms and scatter plots.ipynb
 
 
01-07 Sharpe ratio and other portfolio statistics.ipynb
01-07 Sharpe ratio and other portfolio statistics.ipynb
 
 
01-08 Optimizers Building a parameterized model.ipynb
01-08 Optimizers Building a parameterized model.ipynb
 
 
01-09 Optimizers How to optimize a portfolio.ipynb
01-09 Optimizers How to optimize a portfolio.ipynb
 
 
02-01 So you want to be a hedge fund manager.ipynb
02-01 So you want to be a hedge fund manager.ipynb
 
 
02-02 Market Mechanics.ipynb
02-02 Market Mechanics.ipynb
 
 
02-03 What is a company worth.ipynb
02-03 What is a company worth.ipynb
 
 
02-04 CAPM Capital Asset Pricing Model.ipynb
02-04 CAPM Capital Asset Pricing Model.ipynb
 
 
02-05 How hedge funds use the CAPM.ipynb
02-05 How hedge funds use the CAPM.ipynb
 
 
02-06 Technical Analysis.ipynb
02-06 Technical Analysis.ipynb
 
 
02-07 Dealing with Data.ipynb
02-07 Dealing with Data.ipynb
 
 
02-08 Efficient Markets Hypothesis.ipynb
02-08 Efficient Markets Hypothesis.ipynb
 
 
02-09 The Fundamental Law of Active Portfolio Management.ipynb
02-09 The Fundamental Law of Active Portfolio Management.ipynb
 
 
02-10 Portfolio Optimization and The Efficient Frontier.ipynb
02-10 Portfolio Optimization and The Efficient Frontier.ipynb
 
 
03-01 How Machine Learning is used at a hedge fund.ipynb
03-01 How Machine Learning is used at a hedge fund.ipynb
 
 
03-02 Regression.ipynb
03-02 Regression.ipynb
 
 
03-03 Assessing a learning algorithm.ipynb
03-03 Assessing a learning algorithm.ipynb
 
 
03-04 Ensemble learners, bagging and boosting.ipynb
03-04 Ensemble learners, bagging and boosting.ipynb
 
 
03-05 Reinforcement Learning.ipynb
03-05 Reinforcement Learning.ipynb
 
 
03-06 Q-Learning.ipynb
03-06 Q-Learning.ipynb
 
 
DataHelper.py
DataHelper.py
 
 
MC2-Project-1 Build a Market Simulator.ipynb
MC2-Project-1 Build a Market Simulator.ipynb
 
 
MC3-Project-1 Learners.ipynb
MC3-Project-1 Learners.ipynb
 
 
README.md
README.md
 
 

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