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Financial Engineering and Artificial Intelligence in Python financial engineering



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exploratory data analysis
stock return distributions
alpha and beta
time series analysis
Holt-Winters
ARIMA
EMH (efficient market hypothesis)
random walk hypothesis
stock forecasting
modern portfolio theory
efficient frontier
mean-variance optimization
tangency portfolio
Sharpe ratio
CAPM (capital asset pricing model)
algorithmic trading
trend-following strategy
Q-Learning
Reinforcement Learning .

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6 thoughts on “Financial Engineering and Artificial Intelligence in Python financial engineering”

  1. Still have a whole bunch of your courses to go through, but after taking a few im sure this will be great material as well, will be grabbing VIP version for the future. Keep up the great work!

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