Quantitative Trading Like a Pro: Essential Python Course
Buy now
Learn more
1. Welcome to the course!
Introduction
Course overview
Getting started with Python
Installing Anaconda on Windows
Installing Anaconda on macOS
Using Jupyter Notebook
2. Getting Financial Data
Welcome to Chapter 2!
Downloading data using APIs
Getting Financial Data
Reading data from files
Reading a csv file
Working with data files
Data types
Chapter 2 Python notebook
Chapter 2 exercises and solutions
3. Data preparation and visualisation
Welcome to Chapter 3!
Building VWAP from a text file
Pandas for financial data
Plotting time series data
Chapter3 Python notebook
Chapter3 exercises and solutions
4. Building blocks for financial analysis
Welcome to Chapter 4!
Handling date and time
Converting timezones
Calculating returns
Calculating volatility
Correlation in the market
Linear regression analysis
Chapter 4 Python notebook
Chapter 4 exercises and solutions
5. Python information superhighway
Welcome to Chapter 5!
Data structures
Functions
More functions
Map and lambda
Powerful loops
Chapter 5 Python notebook
Chapter 5 exercises and solutions
6. Building a trading strategy
Welcome to Chapter 6!
Fundamentals of trading strategies
A simple backtest
Cointegration
Formulating the pairs trading strategy
Constructing the pairs trading backtest
Strategy analysis (1)
Strategy analysis (2)
Chapter 6 Python notebook
Chapter 6 exercises and solutions
7. Conclusion
Final remarks
Bonus section
Dealing with NaNs in Financial Time Series
Dealing With NaNs notebook
Parameter Optimisation part 1
Parameter Optimisation part 2
Parameter optimisation notebook
Products
Course
Section
Lesson
Downloading data using APIs
Downloading data using APIs
Quantitative Trading Like a Pro: Essential Python Course
Buy now
Learn more
1. Welcome to the course!
Introduction
Course overview
Getting started with Python
Installing Anaconda on Windows
Installing Anaconda on macOS
Using Jupyter Notebook
2. Getting Financial Data
Welcome to Chapter 2!
Downloading data using APIs
Getting Financial Data
Reading data from files
Reading a csv file
Working with data files
Data types
Chapter 2 Python notebook
Chapter 2 exercises and solutions
3. Data preparation and visualisation
Welcome to Chapter 3!
Building VWAP from a text file
Pandas for financial data
Plotting time series data
Chapter3 Python notebook
Chapter3 exercises and solutions
4. Building blocks for financial analysis
Welcome to Chapter 4!
Handling date and time
Converting timezones
Calculating returns
Calculating volatility
Correlation in the market
Linear regression analysis
Chapter 4 Python notebook
Chapter 4 exercises and solutions
5. Python information superhighway
Welcome to Chapter 5!
Data structures
Functions
More functions
Map and lambda
Powerful loops
Chapter 5 Python notebook
Chapter 5 exercises and solutions
6. Building a trading strategy
Welcome to Chapter 6!
Fundamentals of trading strategies
A simple backtest
Cointegration
Formulating the pairs trading strategy
Constructing the pairs trading backtest
Strategy analysis (1)
Strategy analysis (2)
Chapter 6 Python notebook
Chapter 6 exercises and solutions
7. Conclusion
Final remarks
Bonus section
Dealing with NaNs in Financial Time Series
Dealing With NaNs notebook
Parameter Optimisation part 1
Parameter Optimisation part 2
Parameter optimisation notebook