Quantitative Finance & Algorithmic Trading in Python by Tyler Aaron

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 11 lectures (1h 11m) | Size: 1.12 GB

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

What you’ll learn:
Understand the Modern Portfolio Theory and Markowitz model
Understand stock market fundamentals
Understand derivatives (futures and options)
Understand stochastic processes and the famous Black-Scholes model
Understand Value-at-Risk (VaR)
Understand Value-at-Risk (VaR)
Understand bonds and bond pricing
Understand the Capital Asset Pricing Model (CAPM)
Understand credit derivatives (credit default swaps)
Understand Monte-Carlo simulations

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.

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

Who this course is for
Anyone who wants to learn the basics of financial engineering!