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Quantitative Finance & Algorithmic Trading in Python


Professional Python for Finance Training Classes by The Python Quants. ... data science, algorithmic trading, artificial intelligence, computational finance, Excel ...
 Quantitative Finance & Algorithmic Trading in Python
4.3 (495 ratings)
4,503 students enrolled
Created by Holczer Balazs
 
What you'll learn
  • Understand stock market fundamentals
  • Understand the Modern Portfolio Theory
  • Understand the CAPM
  • Understand stochastic processes and the famous Black-Scholes mode
  • Understand Monte-Carlo simulations
  • Understand Value-at-Risk (VaR)
Requirements
  • You should have an interest in quantitative finance as well as in mathematics and programming!

Description

This course is about the fundamental basics of 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 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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