Curriculum For This Course

Introduction to programming with Python

6Lectures

Time 00:27:36

Python Variables and Data Types

3Lectures

Time 00:12:29

Basic Python Syntax

7Lectures

Time 00:11:20

Python Operators Continued

2Lectures

Time 00:07:45

Conditional Statements

4Lectures

Time 00:13:29

Python Functions

6Lectures

Time 00:15:25

Python Sequences

5Lectures

Time 00:19:11

Using Iterations in Python

6Lectures

Time 00:15:53

Advanced Python tools

10Lectures

Time 00:41:53

PART II FINANCE: Calculating and Comparing Rates of Return in Python

10Lectures

Time 00:42:55

PART II Finance: Measuring Investment Risk

10Lectures

Time 00:41:24

PART II Finance - Using Regressions for Financial Analysis

4Lectures

Time 00:21:39

PART II Finance - Markowitz Portfolio Optimization

4Lectures

Time 00:19:34

Part II Finance - The Capital Asset Pricing Model

8Lectures

Time 00:27:08

Part II Finance: Multivariate regression analysis

2Lectures

Time 00:12:02

PART II Finance - Monte Carlo simulations as a decision-making tool

13Lectures

Time 00:56:54

Introduction to programming with Python
	1. Programming Explained in 5 Minutes	05:04
	2. Why Python?	05:11
	3. Why Jupyter?	03:29
	4. Installing Python and Jupyter	04:22
	5. Jupyter's Interface - the Dashboard	03:15
	6. Jupyter's Interface - Prerequisites for Coding	06:15

Python Variables and Data Types
	1. Variables	03:41
	2. Numbers and Boolean Values	03:05
	3. Strings	05:43

Basic Python Syntax
	1. Arithmetic Operators	03:23
	2. The Double Equality Sign	01:33
	3. Reassign Values	01:08
	4. Add Comments	01:25
	5. Line Continuation	00:50
	6. Indexing Elements	01:18
	7. Structure Your Code with Indentation	01:45

Python Operators Continued
	1. Comparison Operators	02:10
	2. Logical and Identity Operators	05:36

Conditional Statements
	1. Introduction to the IF statement	03:04
	2. Add an ELSE statement	02:39
	3. Else if, for Brief - ELIF	05:33
	4. A Note on Boolean values	02:13

Python Functions
	1. Defining a Function in Python	02:03
	2. Creating a Function with a Parameter	03:49
	3. Another Way to Define a Function	02:35
	4. Using a Function in another Function	01:49
	5. Creating Functions Containing a Few Arguments	01:13
	6. Notable Built-in Functions in Python	03:56

Python Sequences
	1. Lists	04:02
	2. Using Methods	03:22
	3. List Slicing	04:31
	4. Tuples	03:13
	5. Dictionaries	04:04

Using Iterations in Python
	1. For Loops	02:26
	2. While Loops and Incrementing	02:26
	3. Create Lists with the range() Function	02:22
	4. Use Conditional Statements and Loops Together	03:05
	5. All In - Conditional Statements, Functions, and Loops	02:27
	6. Iterating over Dictionaries	03:07

Advanced Python tools
	1. Object Oriented Programming	05:00
	2. Modules and Packages	01:05
	3. The Standard Library	02:47
	4. Importing Modules	04:10
	5. Must-have packages for Finance and Data Science	04:53
	6. Working with arrays	06:02
	7. Generating Random Numbers	02:52
	8. Importing and Organizing Data in Python - part I	03:44
	9. Importing and Organizing Data in Python - part II	07:01
	10. Importing and Organizing Data in Python - part III	04:19

PART II FINANCE: Calculating and Comparing Rates of Return in Python
	1. Considering both risk and return	02:19
	2. What are we going to see next	02:34
	3. Calculating a security's rate of return	05:31
	4. Calculating a Security's Rate of Return in Python - Simple Returns - Part I	05:23
	5. Calculating a Security's Rate of Return in Python - Simple Returns - Part II	03:28
	6. Calculating a Security's Return in Python - Logarithmic Returns	03:39
	7. What is a portfolio of securities and how to calculate its rate of return	02:39
	8. Calculating the Rate of Return of a Portfolio of Securities	08:34
	9. Popular stock indices that can help us understand financial markets	03:31
	10. Calculating the Rate of Return of Indices	05:03

PART II Finance: Measuring Investment Risk
	1. How do we measure a security's risk	06:05
	2. Calculating a Security's Risk in Python	05:56
	3. The benefits of portfolio diversification	03:28
	4. Calculating the covariance between securities	03:35
	5. Measuring the correlation between stocks	03:59
	6. Calculating Covariance and Correlation	05:00
	7. Considering the risk of multiple securities in a portfolio	03:19
	8. Calculating Portfolio Risk	02:39
	9. Understanding Systematic vs. Idiosyncratic risk	02:58
	10. Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio	04:28

PART II Finance - Using Regressions for Financial Analysis
	1. The fundamentals of simple regression analysis	03:55
	2. Running a Regression in Python	06:35
	3. Are all regressions created equal? Learning how to distinguish good regressions	04:55
	4. Computing Alpha, Beta, and R Squared in Python	06:14

PART II Finance - Markowitz Portfolio Optimization
	1. Markowitz Portfolio Theory - One of the main pillars of modern Finance	06:34
	2. Obtaining the Efficient Frontier in Python - Part I	05:35
	3. Obtaining the Efficient Frontier in Python - Part II	05:18
	4. Obtaining the Efficient Frontier in Python - Part III	02:07

Part II Finance - The Capital Asset Pricing Model
	1. The intuition behind the Capital Asset Pricing Model (CAPM)	04:45
	2. Understanding and calculating a security's Beta	04:14
	3. Calculating the Beta of a Stock	03:38
	4. The CAPM formula	04:20
	5. Calculating the Expected Return of a Stock (CAPM)	02:16
	6. Introducing the Sharpe ratio and the way it can be applied in practice	02:21
	7. Obtaining the Sharpe ratio in Python	01:23
	8. Measuring alpha and verifying how good (or bad) a portfolio manager is doing	04:13

Part II Finance: Multivariate regression analysis
	1. Multivariate regression analysis - a valuable tool for finance practitioners	05:42
	2. Running a multivariate regression in Python	06:20

PART II Finance - Monte Carlo simulations as a decision-making tool
	1. The essence of Monte Carlo simulations	02:32
	2. Monte Carlo applied in a Corporate Finance context	02:30
	3. Monte Carlo: Predicting Gross Profit - Part I	06:03
	4. Monte Carlo: Predicting Gross Profit - Part II	02:57
	5. Forecasting Stock Prices with a Monte Carlo Simulation	04:27
	6. Monte Carlo: Forecasting Stock Prices - Part I	03:39
	7. Monte Carlo: Forecasting Stock Prices - Part II	04:38
	8. Monte Carlo: Forecasting Stock Prices - Part III	04:17
	9. An Introduction to Derivative Contracts	06:32
	10. The Black Scholes Formula for Option Pricing	04:51
	11. Monte Carlo: Black-Scholes-Merton	06:00
	12. Monte Carlo: Euler Discretization - Part I	06:21
	13. Monte Carlo: Euler Discretization - Part II	02:09

About This Course

Before you enter such a complicated sphere as financial analysis, we strongly recommend you to take the Financial Analysis in Python video course! This thorough, but at the same time simple guide will explain all aspects of using Python in financial operations.

As you will see, this tutorial contains two main modules: one of them is dedicated to programming in Python, and the second one is focused on using Python to perform and improve financial processes. Below you will find a list of topics covered by the course:

How to code in Python
- Introduction to programming with Python
- Python variables and data types
- Basic Python syntax
- Python operators continued
- Conditional statements
- Python functions
- Python sequences
- Using iterations in Python
- Advanced Python tools
Finance
- Comparing and calculating return rates in Python
- Measuring investment risk
- Using regressions for financial analysis
- Markowitz portfolio optimization
- Capital asset pricing model
- Multivariate regression analysis
- Monte Carlo simulations as a decision-making tool

While the first block is concentrated on Python basics and teaches you how to use this programming language to your advantage, the second block is dedicated to the instruments of financial analysis that you can use in your day-to-day working practice.

Join this course today, and you will learn everything you need to know about regression analysis, Monte Carlo simulations, Alpha and Beta coefficients, covariance, and risk of stocks. All materials in the tutorial are simply presented and digestible even for newbies, so you will be able to benefit from this course even if you have zero experience in the financial field!

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The Financial Analysis in Python

Curriculum For This Course

About This Course

Pass Finance Courses The Financial Analysis in Python Exam in First Attempt Guaranteed!

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