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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