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Quantitative Finance & Algorithmic Trading In Python

Category: Tutorials



Quantitative Finance & Algorithmic Trading In Python
Quantitative Finance & Algorithmic Trading In Python
Last updated 11/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.50 GB | Duration: 15h 3m


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

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

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 - Introductioninstalling Pythonwhy to use Python programming languagethe problem with financial models and historical dataSection 2 - Stock Market Basicspresent value and future value of moneystocks and sharescommodities and the FOREXwhat are short and long positions?Section 3 - Bond Theory and Implementationwhat are bondsyields and yield to maturityMacaulay durationbond pricing theory and implementationSection 4 - Modern Portfolio Theory (Markowitz Model)what is diverzification in finance?mean and varianceefficient frontier and the Sharpe ratiocapital allocation line (CAL)Section 5 - Capital Asset Pricing Model (CAPM)systematic and unsystematic risksbeta and alpha parameterslinear regression and market riskwhy market risk is the only relevant risk?Section 6 - Derivatives Basicsderivatives basicsoptions (put and call options)forward and future contractscredit default swaps (CDS)interest rate swapsSection 7 - Random Behavior in Financerandom behaviorWiener processesstochastic calculus and Ito's lemmabrownian motion theory and implementationSection 8 - Black-Scholes ModelBlack-Scholes model theory and implementationMonte-Carlo simulations for option pricingthe greeksSection 9 - Value-at-Risk (VaR)what is value at risk (VaR)Monte-Carlo simulation to calculate risksSection 10 - Collateralized Debt Obligation (CDO)what are CDOs?the financial crisis in 2008Section 11 - Interest Rate Modelsmean reverting stochastic processesthe Ornstein-Uhlenbeck processthe Vasicek modelusing Monte-Carlo simulation to price bondsSection 12 - Value Investinglong term investingefficient market hypothesisAPPENDIX - PYTHON CRASH COURSEbasics - variables, strings, loops and logical operatorsfunctionsdata structures in Python (lists, arrays, tuples and dictionaries)object oriented programming (OOP)NumPyThanks for joining my course, let's get started!

Anyone who wants to learn the basics of financial engineering!




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