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Python for Finance: Investment Fundamentals and Data Analytics
Welcome! Course Introduction
What Does the Course Cover? (5:10)
Download Useful Resources
Introduction to Programming with Python
Programming Explained in 5 Minutes (5:04)
Why Python? (5:11)
Why Jupyter? (3:29)
Installing Python and Jupyter (4:22)
Jupyter's Interface - the Dashboard (3:15)
Jupyter's Interface - Prerequisites for Coding (6:15)
Python Variables and Data Types
Variables (3:41)
Numbers and Boolean Values (3:05)
Strings (5:43)
Basic Python Syntax
Arithmetic Operators (3:23)
The Double Equality Sign (1:33)
Reassign Values (1:08)
Add Comments (1:25)
Line Continuation (0:49)
Indexing Elements (1:18)
Structure Your Code with Indentation (1:45)
Python Operators Continued
Comparison Operators (2:10)
Logical and Identity Operators (5:36)
Conditional Statements
Introduction to the IF statement (3:04)
Add an ELSE statement (2:39)
Else, if, for Brief - ELIF (5:33)
A Note on Boolean Values (2:13)
Python Functions
Defining a Function in Python (2:03)
Creating a Function with a Parameter (3:49)
Another Way to Define a Function (2:35)
Using a Function in another Function (1:49)
Combining Conditional Statements and Functions (3:06)
Creating Functions Containing a Few Arguments (1:13)
Notable Built-In Functions in Python (3:56)
Sequences
Lists (4:02)
Using Methods (3:22)
List Slicing (4:31)
Tuples (3:13)
Dictionaries (4:04)
Using Iterations in Python
For Loops (2:26)
While Loops and Incrementing (2:26)
Create Lists with the range() Function (2:22)
Use Conditional Statements and Loops Together (3:05)
All In - Conditional Statements, Functions, and Loops (2:27)
Iterating over Dictionaries (3:07)
Useful Tools
Object-Oriented Programming (5:00)
Modules and Packages (1:05)
The Standard Library (2:47)
Importing Modules (4:10)
Must-Have Packages for Finance and Data Science (4:53)
Working with Arrays (6:02)
Generating Random Numbers (2:52)
Importing and Organizing Data in Python - Part I (3:44)
Importing and Organizing Data in Python - Part II (7:01)
Importing and Organizing Data in Python - Part III (4:19)
PART II Finance: Calculating and Comparing Rates of Return in Python
Considering Both Risk and Return (2:33)
What Are We Going to See Next (2:34)
Calculating a Security's Rate of Return (5:31)
Calculating a Security's Rate of Return in Python - Simple Returns - Part I (5:23)
Calculating a Security's Rate of Return in Python - Simple Returns - Part II (3:28)
Calculating a Security's Rate of Return in Python - Logarithmic Returns (3:39)
What Is a Portfolio of Securities and How to Calculate Its Rate of Return (2:39)
Using 'Loc' and 'Iloc' - Note
Calculating the Rate of Return of a Portfolio of Securities (8:34)
Popular Stock Indices that Can Help us Understand Financial Markets (3:31)
Calculating the Rate of Return of Indices (5:03)
PART II Finance: Measuring Investment Risk
How Do We Measure a Security's Risk (6:05)
Calculating a Security's Risk in Python (5:56)
The Benefits of Portfolio Diversification (3:28)
Calculating the Covariance Between Securities (3:34)
Measuring the Correlation between Stocks (3:59)
Calculating Covariance and Correlation (5:00)
Considering the Risk of Multiple Securities in a Portfolio (3:19)
Calculating Portfolio Risk (2:39)
Understanding Systematic vs. Idiosyncratic Risk (2:58)
Calculating Diversifiable and Non-Diversifiable Risk of a Portfolio (4:28)
PART II Finance: Using Regressions for Financial Analysis
The Fundamentals of Simple Regression Analysis (3:55)
Running a Regression in Python (6:35)
Are All Regressions Created Equal? Learning How to Distinguish Good Regressions (4:55)
Computing Alpha, Beta, and R Squared in Python (6:14)
PART II Finance: Markowitz Portfolio Optimization
Markowitz Portfolio Theory - One of the main Pillars of Modern Finance (6:34)
Obtaining the Efficient Frontier in Python - Part I (5:35)
Obtaining the Efficient Frontier in Python - Part II (5:18)
Obtaining the Efficient Frontier in Python - Part III (2:07)
PART II Finance: The Capital Asset Pricing Model
The Intuition behind the Capital Asset Pricing Model (CAPM) (4:44)
Understanding and Calculating a Security's Beta (4:14)
Calculating the Beta of a Stock (3:38)
The CAPM Formula (4:20)
Calculating the Expected Return of a Stock (CAPM) (2:16)
Introducing the Sharpe Ratio and the Way It Can Be Applied in Practice (2:21)
Obtaining the Sharpe Ratio in Python (1:22)
Measuring Alpha and Verifying How Good (or Bad) a Portfolio Manager Is Doing (4:13)
PART II Finance: Multivariate Regression Analysis
Multivariate Regression Analysis - a Valuable Tool for Finance Practitioners (5:42)
Running a Multivariate Regression in Python (6:20)
PART II Finance: Monte Carlo Simulations as a Decision-Making Tool
The Essence of Monte Carlo Simulations (2:31)
What Is a Normal Distribution? - Note
Monte Carlo Applied in a Corporate Finance Context (2:30)
Monte Carlo: Predicting Gross Profit - Part I (6:03)
Monte Carlo: Predicting Gross Profit - Part II (2:57)
Forecasting Stock Prices with a Monte Carlo Simulation (4:27)
Another Way to Calculate Simple and Log Returns - Note
Monte Carlo: Forecasting Stock Prices - Part I (3:39)
Monte Carlo: Forecasting Stock Prices - Part II (4:38)
Monte Carlo: Forecasting Stock Prices - Part III (4:17)
An Introduction to Derivative Contracts (6:32)
The Black-Scholes Formula for Option Pricing (4:51)
Monte Carlo: Black-Scholes-Merton (6:00)
Monte Carlo: Euler Discretization - Part I (6:21)
Monte Carlo: Euler Discretization - Part II (2:09)
Using 'Loc' and 'Iloc' - Note
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