AlgoTrading101 – PT101 Practical Python for Finance & Trading Masterclass

Learn Python for Finance & Trading – Practical Ideas and Strategies for Modern Markets

Course Curriculum

Chapter 1 > Here’s What You Are In For!

AT101 or PT101?

Why Code for Trading? The New Mindset – Trading Ideas and Concepts (Part 1) (5:38)

Why Code for Trading? The New Mindset – Trading Ideas and Concepts (Part 2) (5:35)

Why Code for Trading? The New Mindset – Trading Ideas and Concepts (Part 3) (7:24)

The Real Holy Grail of Trading

The First Step – How To  Your Journey?

Simple vs Complex – Overview and Approach to Strategies in this Course

Teaser Strategy: 1+3-3+1 Bond Futures Calendar Spread

Chapter 2 > Python Basics 1 – The First Step

Why Python over other Programming Languages

AlgoTrading101 Partners with Holistic Coding and Algo-Hunter

Get the Snake – Installing Anaconda (1:45)

Using the Command Line (13:37)

Overview of our Research and Execution Tool – Jupyter Notebook (12:03)

What Snakes are these? Anaconda vs Python

Fastest Way to Open Your Jupyter Notebook

Download Code for Chapter 2

The Basic Building Blocks – Variables and Expressions (6:55)

Know what You Can Do – Jupyter Notebook & Python Superpower List

Copy Others’ Code – Python Libraries and Packages

Chapter 3 > No Data No Trading – Getting Some Basic Data In

Download Code for Chapter 3

Get Data from Quandl – Let’s Get Apple’s Stock Prices (8:22)

Quandl WIKI Database Limitations – Yahoo Finance to the Rescue

Installing Library for Yahoo Finance API (0:35)

Retrieving Data from Yahoo Finance API – Just a One-Liner (6:14)

Chapter 4 > Volatility Pairs Trading – Our First Strategy (A Teaser into Practical Pair Trading)

2 Behaviours – Correlation vs Cointegration (4:25)

Pair Trading – The Basic Cointegration Strategy (Part 1) (6:05)

Pair Trading – The Basic Cointegration Strategy (Part 2) (5:59)

Volatility Pairs Trading – Our Teaser Strategy (Intro)

Volatility Pairs Trading – Check it with our Eyes! (Visual Backtesting) – Part 1 (4:59)

Volatility Pairs Trading – Check it with our Eyes! (Visual Backtesting) – Part 2 (5:12)

Longing, Shorting and Spreads

Download Code for Chapter 4

Volatility Pairs Trading – Preparing for the Statistical Backtest

Volatility Pairs Trading – The Real Test! Running our Statistical Backtest (Part 1) (9:24)

Volatility Pairs Trading – The Real Test! Running our Statistical Backtest (Part 2) (8:31)

Volatility Pairs Trading – The Real Test! Running our Statistical Backtest (Part 3) (7:52)

Volatility Pairs Trading – The Real Test! Running our Statistical Backtest (Part 4) (8:53)

Volatility Pairs Trading – 10 Ideas to Level Up. Adapting to the Real-World

Chapter 5 > Python Basics 2 – Foundations

Just so you don’t feel lost

Running all Cells

Download Code for Chapter 5

Counting stuff in Python (8:51)

Variables contain different Types of Info – Data Types (6:57)

The Simplest Table (Lists of Values) + Datetime Management (6:15)

The Simplest Tables with Unchangeable Values – Tuples (4:16)

If A happens, do B – Conditional Statements (17:11)

Printing stuff – Formatting your texts and numbers (7:56)

Meaning behind String Symbols

Do Something Many Times Using Code – For Loops (10:26)

Loops Practice 1 – Basic For Loops

Do Something Many Times in a Different Way – While Loops (10:04)

Loops Practice 2 – Basic While Loops

Looping Twice – Nested Loops (4:52)

Loops Practice 3 – Nested Loops

If A then B, Many Times – Loops with Conditionals (6:54)

Loops Practice 4 – Conditional + Nested Loops

Answers to Loops Practice 1 to 4 (11:19)

Loops with some Control (Continue, Break and Pass) (4:34)

Loops Practice 5 – Calculating Stock Metrics

Answers to Loops Practice 5 (12:30)

For Loops without the Range Method

When to use For vs While Loops

Get Data from CSV and TXT (10:32)

Exporting dataframe to CSV

Stuck at Programming? Self-Learning and Getting Help Guide

Elegant Code vs Learning Trading

Chapter 6 > Strategy Design I – Differentiating Luck and Skill

The Most Important Concept – Market Prudence

Market Inefficiency Discovery vs Exploitation

David vs Goliath – Can we outwit the Big Funds?

Us vs Hedge Funds: Why We Dislike Trading on Lower Timeframes

Outwitting the Masses – Second-Order Thinking

How to Choose What Markets/Strategies to Trade

Does this course suck? Or is it adding value to you?

Chapter 7 > Practical Statistics 101 – Making Sense of Key Figures

Calculating Long Term Expected Payout of a Robot (6:40)

Statistical Significance and Law of Large Numbers – More is better (6:58)

What is an Abnormal Move – Understanding Standard Deviations

Stock Returns Behaviour – Understanding Normal Distributions

Minimum Sample Size and Application to Trading (10:59)

Cointegration Simplified

Optional Readings on Statistics

What are Correlation and Sensitivity/Regression

The Real Role of Statistics in our Trading

Chapter 8 > A Library for Data Analysis – Pandas (Not the lazy animal!)

Generating Random Numbers

What is Pandas and Why Do We Need It?

Download Code for Chapter 8

Two Column Tables of Data – Dataframe (This one is important) (14:35)

Managing Dataframes – Editing our Tables (7:24)

Managing Dataframes 2 – Changing the Shape of our Dataframes (7:55)

Datetime Management – Adding Dates to Dataframes (7:54)

Pandas Exercise 1 – All You Need for Managing Dataframes

Changing Dataframe’s Data Type

Not-a-Number? Dealing with NaN and NaT

Pandas Exercise 2 – Managing Non Numbers in your Data

What is a Pandas Series? (8:34)

Chapter 9 > Strategy Design II – Creating Alpha Out of Thin Air: The Magic of Synthetic Assets

Introduction to Synthetic Assets – Why Does It Produce Alpha (9:30)

Types of Synthetic Assets – Hedging in Different Ways (Part 1) (8:06)

Types of Synthetic Assets – Hedging in Different Ways (Part 2) (5:25)

Moving Beyond Spreads – Spread^2 and Others

Download Code for the Chapter

Practice 1 (Questions) – Dollar-Hedged Structure

Practice 1 (Answers) – Dollar-Hedged Structure (Part 1) (9:18)

Practice 1 (Answers) – Dollar-Hedged Structure (Part 2) (8:04)

Manipulating the Shapes of Structures using Multipliers (10:22)

Effect of Multipliers – Summary

An Impossible Structure – One Ranging and One Trending

Normalising the first value to 1

Market-Hedging and Other Hedges

Chapter 10 > Practical Cointegration Trading Ideas

3 Cointegration Trading Ideas that we can Implement

No-Code Trading Research Tools – Do Quick Research before Committing

Chapter 11 (Strategy) > Bond Futures Synthetic Structures – The Calendar Spreads I

Bond Futures Calendar Spreads (Part 1) – One of the Most Stable Synthetic Asset – Introduction

Bond Yields and Prices – They are Inverse!

Bond Futures Calendar Spreads (Part 2) – Understanding the Fundamental Idea

Finding Alpha in STIR Futures

Download code for this chapter

Code to download BAX data + 2 Coding tasks for you

Downloading and Cleaning BAX Data (10:46)

Calculating and Plotting a Double Butterfly in Python (Part 1) (6:06)

Calculating and Plotting a Double Butterfly in Python (Part 2) (6:53)

The Easy Way – Charting STIR Futures Structures on Tradingview

List of STIR Futures – Common and Less Common STIRs

Opening a Interactive Brokers Demo account to Trade STIR Futures

Using Interactive Brokers’ Booktrader (aka price ladder)

Bond Futures Calendar Spreads (Part 3) – The Essence of the Strategy: Execution

Bond Futures Calendar Spreads (Part 4) – The Source of Alpha: Level Up Your Execution

Prepare for Battle – Set up your Interactive Brokers Layout (Part 1) (6:39)

Prepare for Battle – Set up your Interactive Brokers Layout (Part 2) (7:59)

Finding Your Asset in Interactive Brokers

Mental Sums – Calculating Price of Double Butterfly from Booktraders

Time for Battle! Demonstrating How to Execute a D.Butterfly (Part 1) (8:44)

Time for Battle! Demonstrating How to Execute a D.Butterfly (Part 2) (8:48)

Chapter 12 (Strategy) > Bond Futures Synthetic Structures – The Calendar Spreads II

New Weapon – Combination Order

Demonstrating the new weapon – The Combination Order (7:33)

Understanding the Combination Order

Bond Futures Calendar Spreads (Part 5) – Multi-Quarter Structures and Structures Equivalence

A New Weapon – Finding Opportunities in the Term Structure (Part 1) (6:07)

A New Weapon – Finding Opportunities in the Term Structure (Part 2) (7:05)

Term Structure and STIR Pricing

Bond Futures Calendar Spreads (Part 6) – Trading with the Drift

Bond Futures Calendar Spreads (Part 7) – Strategy Difficulties and Risks

Downloading and Storing BAX data in Bulk

How much $ do you need for this strategy – Capital Requirements

Bond Futures Calendar Spreads (Part 8) – Backtesting and other Considerations

STIR Trade Sizing and Non-Entry/Exit System

BAX End Note

Chapter 13 > Python Basics 3 – Functions and OOP

Those who are good at Python can skip this chapter

What are Functions – Our Little Factories

Download Code

User-Defined Functions – Learn to Code Your Own Factories! (20:29)

Functions Practice 1 – Questions

Functions Practice 1 – Solutions (Part 1) (9:02)

Functions Practice 1 – Solutions (Part 2) (10:56)

What are Scripts – Simple Python file (Also: How to import your own code) (10:18)

Uses of Python Scripts vs Jupyter Notebooks

Modules vs Libraries vs Packages – Understanding the Terminologies

OOP Series – Object-Oriented Programming (OOP) Simplified. Objects store values and/or does stuff (5:06)

OOP Series – Difference between Classes and Objects (2:40)

OOP Series – Why do we need to learn OOP? Ans: We have no choice

OOP Series – Object Variables: Storing Values (Part 1) (9:12)

OOP Series – Object Variables: Storing Values (Part 2) (11:40)

OOP Series – Object Functions: Doing stuff (11:18)

Objects Practice 1 – Object Variables (Questions + Solutions)

Objects Practice 2 – Object Functions (Questions)

Objects Practice 2 – Object Functions (Solutions) Part 1 (5:34)

Objects Practice 2 – Object Functions (Solutions) Part 2 (8:55)

Naming Conventions – How to name your classes, variables etc

Chapter 14 > Backtesting Theories – Our Aim and the Mistakes to Avoid

What is Backtesting – Simplified

The Aim of Backtesting – We are NOT trying to build the Ultimate Strategy

3 Big Mistakes of Backtesting – 1) Overfitting 2) Look-Ahead Bias 3) P-Hacking

Solution to the 3 Big Mistakes in Backtesting