Quantitative Finance & Algorithmic Trading In Python

[0dayddl]

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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2.88 GB | 11min 43s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

1 Introduction.mp4 (5.46 MB)
2 Why to use Python.mp4 (5.06 MB)
3 Financial models.mp4 (12.05 MB)
1 Installing Python.mp4 (14.7 MB)
2 Installing PyCharm.mp4 (22.79 MB)
1 Present value and future value of money.mp4 (26.56 MB)
2 Time value of money implementation.mp4 (43.05 MB)
4 Standard investment asset classes.mp4 (24.94 MB)
5 Stocks and shares.mp4 (43.05 MB)
6 How stock exchanges work.mp4 (21.67 MB)
8 Commodities.mp4 (12.9 MB)
9 Currencies and the FOREX.mp4 (60.05 MB)
11 Short and long positions.mp4 (18.3 MB)
1 What are bonds.mp4 (15.05 MB)
2 Yields and yield to maturity.mp4 (18.83 MB)
3 Interest rates and bonds.mp4 (14.77 MB)
4 Macaulay duration.mp4 (9.67 MB)
5 Risks with bonds.mp4 (4.27 MB)
6 Bonds and monetary policy.mp4 (23.05 MB)
7 Stocks and bonds.mp4 (3.88 MB)
1 Bonds pricing implementation I.mp4 (29.89 MB)
2 Bonds pricing implementation II.mp4 (35.89 MB)
1 What are mean, variance and correlation.mp4 (18.74 MB)
3 The main idea - diverzification.mp4 (14.51 MB)
5 Mathematical formulation.mp4 (14.39 MB)
6 Expected return of the portfolio.mp4 (22.6 MB)
7 Expected variance (risk) of the portfolio.mp4 (25.99 MB)
8 Efficient frontier.mp4 (19.91 MB)
9 Sharpe ratio.mp4 (10.08 MB)
10 Capital allocation line.mp4 (18.99 MB)
1 Markowitz model implementation I.mp4 (25.18 MB)
2 Markowitz model implementation II.mp4 (60.4 MB)
3 Markowitz model implementation III.mp4 (46.36 MB)
4 Markowitz model implementation IV.mp4 (79.85 MB)
5 Markowitz model implementation V.mp4 (18.53 MB)
1 Systematic and unsystematic risk.mp4 (7.88 MB)
2 Capital asset pricing model formula.mp4 (17.91 MB)
3 The beta value.mp4 (21.33 MB)
4 What is linear regression.mp4 (36.52 MB)
5 Capital asset pricing model and linear regression.mp4 (9.47 MB)
1 Capital asset pricing model implementation I.mp4 (15.01 MB)
2 Capital asset pricing model implementation II.mp4 (59.73 MB)
3 Capital asset pricing model implementation III.mp4 (40.1 MB)
5 Solution - normal distribution of returns.mp4 (11.83 MB)
1 Introduction to derivatives.mp4 (40.45 MB)
3 Understanding leverage and margin.mp4 (45.97 MB)
5 Forward and future contracts.mp4 (6.57 MB)
6 Swaps and interest rate swaps.mp4 (16.94 MB)
7 Credit default swap (CDS).mp4 (7.04 MB)
8 Options basics.mp4 (8.83 MB)
9 Call option.mp4 (11.89 MB)
10 Put option.mp4 (6.13 MB)
11 American and european options.mp4 (2.7 MB)
1 Forward contracts introduction.mp4 (26.24 MB)
2 Currency forwards.mp4 (40.63 MB)
3 Interest rate forwards (a k a FRA).mp4 (42.33 MB)
1 Future contracts introduction.mp4 (20.24 MB)
2 Delivery types.mp4 (18.8 MB)
1 Types of analysis.mp4 (14.12 MB)
2 Random behavior of returns.mp4 (12.43 MB)
3 Wiener-processes and random walks.mp4 (52.43 MB)
4 Wiener-process implementation.mp4 (37.45 MB)
5 Stochastic calculus introduction.mp4 (18.47 MB)
6 Ito's lemma in higher dimensions.mp4 (24.69 MB)
7 Solving the geometric random walk equation.mp4 (10.1 MB)
8 Geometric brownian motion implementation.mp4 (29.13 MB)
1 Black-Scholes model introduction - the portfolio.mp4 (34.04 MB)
2 Black-Scholes model introduction - dynamic delta hedge.mp4 (29.49 MB)
3 Black-Scholes model introduction - no arbitrage principle.mp4 (10.38 MB)
4 Solution to Black-Scholes equation.mp4 (8.38 MB)
5 The greeks.mp4 (9.49 MB)
6 How to make money with Black-Scholes model.mp4 (8.9 MB)
7 Long Term Capital Management (LTCM).mp4 (34.09 MB)
1 Black-Scholes model implementation.mp4 (30.76 MB)
2 What is Monte-Carlo simulation.mp4 (17.73 MB)
3 Predicting stock prices with Monte-Carlo simulation.mp4 (53.99 MB)
4 Black-Scholes model implementation with Monte-Carlo simulation I.mp4 (10.32 MB)
5 Black-Scholes model implementation with Monte-Carlo simulation II.mp4 (23.09 MB)
6 Black-Scholes model implementation with Monte-Carlo simulation III.mp4 (15.65 MB)
1 What is Value-at-Risk.mp4 (25.82 MB)
2 Value-at-Risk introduction.mp4 (20.82 MB)
3 Value at risk implementation.mp4 (30.8 MB)
4 Value at risk implementation with Monte-Carlo simulation I.mp4 (54.65 MB)
5 Value at risk implementation with Monte-Carlo simulation II.mp4 (9.26 MB)
1 What are CDOs.mp4 (9.02 MB)
2 CDOs and diverzification.mp4 (11.14 MB)
3 CDO tranches.mp4 (4.93 MB)
4 The financial crisis of 2007-2008.mp4 (20.84 MB)
1 Why to use interest rate models.mp4 (7.27 MB)
2 The Ornstein-Uhlenbeck process introduction.mp4 (19.6 MB)
3 The Ornstein-Uhlenbeck process implementation.mp4 (14 MB)
4 Vasicek model introduction.mp4 (12.37 MB)
5 Vasicek model implementation.mp4 (11.28 MB)
1 Bond pricing with the Vasicek model I.mp4 (14.72 MB)
2 Bond pricing with the Vasicek model II.mp4 (20.84 MB)
3 Bond pricing with the Vasicek model III.mp4 (14.54 MB)
1 Value investing.mp4 (21.83 MB)
2 Efficient market hypothesis.mp4 (9.39 MB)
1 Python crash course introduction.mp4 (3.96 MB)
1 First steps in Python.mp4 (7.37 MB)
2 What are the basic data types.mp4 (7.7 MB)
3 Booleans.mp4 (3.52 MB)
4 Strings.mp4 (14.57 MB)
5 String slicing.mp4 (12.66 MB)
6 Type casting.mp4 (8.18 MB)
7 Operators.mp4 (10.69 MB)
8 Conditional statements.mp4 (8.57 MB)
9 How to use multiple conditions.mp4 (15.96 MB)
12 Logical operators.mp4 (8.05 MB)
13 Loops - for loop.mp4 (9.55 MB)
14 Loops - while loop.mp4 (7.55 MB)
17 What are nested loops.mp4 (5.95 MB)
18 Enumerate.mp4 (7.69 MB)
19 Break and continue.mp4 (9.91 MB)
20 Calculating Fibonacci-numbers.mp4 (4.02 MB)
1 What are functions.mp4 (8.1 MB)
2 Defining functions.mp4 (9.6 MB)
3 Positional arguments and keyword arguments.mp4 (22.2 MB)
4 Returning values.mp4 (8.77 MB)
5 Returning multiple values.mp4 (6 MB)
8 Yield operator.mp4 (9.15 MB)
9 Local and global variables.mp4 (4.25 MB)
10 What are the most relevant built-in functions.mp4 (7.63 MB)
11 What is recursion.mp4 (17.39 MB)
14 Local vs global variables.mp4 (7.83 MB)
15 The main function.mp4 (7.33 MB)
1 How to measure the running time of algorithms.mp4 (18.3 MB)
2 Data structures introduction.mp4 (6.72 MB)
3 What are array data structures I.mp4 (12.28 MB)
4 What are array data structures II.mp4 (12.31 MB)
5 Lists in Python.mp4 (10.52 MB)
6 Lists in Python - advanced operations.mp4 (18.6 MB)
7 Lists in Python - list comprehension.mp4 (24.69 MB)
12 What are tuples.mp4 (7.52 MB)
13 Mutability and immutability.mp4 (8.7 MB)
14 What are linked list data structures.mp4 (20.76 MB)
15 Doubly linked list implementation in Python.mp4 (11.43 MB)
16 Hashing and O(1) running time complexity.mp4 (23.13 MB)
17 Dictionaries in Python.mp4 (19.43 MB)
18 Sets in Python.mp4 (26.05 MB)
21 Sorting.mp4 (23.76 MB)
1 What is object oriented programming (OOP).mp4 (5.24 MB)
2 Class and objects basics.mp4 (5.38 MB)
3 Using the constructor.mp4 (17.82 MB)
4 Class variables and instance variables.mp4 (14.67 MB)
7 Private variables and name mangling.mp4 (12.18 MB)
8 What is inheritance in OOP.mp4 (8.13 MB)
9 The super keyword.mp4 (9.14 MB)
10 Function (method) override.mp4 (6.46 MB)
11 What is polymorphism.mp4 (16.18 MB)
12 Polymorphism and abstraction example.mp4 (13.71 MB)
15 Modules.mp4 (11.04 MB)
16 The str function.mp4 (7.66 MB)
17 Comparing objects - overriding functions.mp4 (17.12 MB)
1 What is the key advantage of NumPy.mp4 (8.15 MB)
2 Creating and updating arrays.mp4 (16.76 MB)
3 Dimension of arrays.mp4 (18.44 MB)
4 Indexes and slicing.mp4 (16.72 MB)
5 Types.mp4 (9.92 MB)
6 Reshape.mp4 (16.97 MB)
9 Stacking and merging arrays.mp4 (17.22 MB)
10 Filter.mp4 (7.65 MB)

]
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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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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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