Quantitative Finance & Algorithmic Trading in Python
This course is about the fundamental basics of Finance & Algorithmic Trading in Python financial engineering. First of all you will learn about stocks, bonds and other derivatives. The main reason of this course is to get a better understanding of mathematical models concerning the finance in the main. Markowitz-model is the first step. Then Capital Asset Pricing Model (CAPM). One of the most elegant scientific discoveries in the 20th century is the Black-Scholes model: how to eliminate risk with hedging. Nowadays machine learning techniques are becoming Finance & Algorithmic Trading in Python more and more popular. So you will learn about regression, SVM and tree based approaches.
IMPORTANT: only take this course, if you are interested in statistics and mathematics !!!
Section 1:
- installing Python
- stock market basics
Section 2:
- what are bonds
- how to calculate the price of a bond
Section 3:
- what is modern portfolio theory (Markowitz-model)
- efficient frontier and capital allocation line
- sharpe ratio
Section 4:
- what is capital asset pricing model (CAPM)
- beta value and market risk
Section 5:
- derivatives basics
- options (put and call options)
- random behaviour
- stochastic calculus and Ito’s lemma
- brownian motion
- Black-Scholes model
Section 6:
- what is value at risk (VaR)
- Monte-Carlo simulation
Section 7:
- machine learning in finance
- how to forecast future stock prices
- SVM, k-nearest neighbor classifier and logistic regression
Section 8:
- long term investing (the Warren Buffer way)
- efficient market hypothesis
Thanks for joining my course, let’s get started!
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