Udemy – Quantitative Finance & Algorithmic Trading in Python (11.2023)

Udemy – Quantitative Finance & Algorithmic Trading in Python (11.2023)
English | Tutorial | Size: 2.43 GB


Stock Market, Bonds, Markowitz-Portfolio Theory, CAPM, Black-Scholes Model, Value at Risk and Monte-Carlo Simulations

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.

First of all we have to consider bonds and bond pricing. Markowitz-model is the second step. Then Capital Asset Pricing Model (CAPM). One of the most elegant scientific discoveries in the 20th century is the Black-Scholes model and how to eliminate risk with hedging.

IMPORTANT: only take this course, if you are interested in statistics and mathematics !!!

Section 1 – Introduction

installing Python

why to use Python programming language

the problem with financial models and historical data

Section 2 – Stock Market Basics

present value and future value of money

stocks and shares

commodities and the FOREX

what are short and long positions?

Section 3 – Bond Theory and Implementation

what are bonds

yields and yield to maturity

Macaulay duration

bond pricing theory and implementation

Section 4 – Modern Portfolio Theory (Markowitz Model)

what is diverzification in finance?

mean and variance

efficient frontier and the Sharpe ratio

capital allocation line (CAL)

Section 5 – Capital Asset Pricing Model (CAPM)

systematic and unsystematic risks

beta and alpha parameters

linear regression and market risk

why market risk is the only relevant risk?

Section 6 – Derivatives Basics

derivatives basics

options (put and call options)

forward and future contracts

credit default swaps (CDS)

interest rate swaps

Section 7 – Random Behavior in Finance

random behavior

Wiener processes

stochastic calculus and Ito’s lemma

brownian motion theory and implementation

Section 8 – Black-Scholes Model

Black-Scholes model theory and implementation

Monte-Carlo simulations for option pricing

the greeks

Section 9 – Value-at-Risk (VaR)

what is value at risk (VaR)

Monte-Carlo simulation to calculate risks

Section 10 – Collateralized Debt Obligation (CDO)

what are CDOs?

the financial crisis in 2008

Section 11 – Interest Rate Models

mean reverting stochastic processes

the Ornstein-Uhlenbeck process

the Vasicek model

using Monte-Carlo simulation to price bonds

Section 12 – Value Investing

long term investing

efficient market hypothesis

APPENDIX – PYTHON CRASH COURSE

basics – variables, strings, loops and logical operators

functions

data structures in Python (lists, arrays, tuples and dictionaries)

object oriented programming (OOP)

NumPy

Thanks for joining my course, let’s get started!

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