Quantitative Trading Like a Pro: Essential Python Course
What you'll learn
- The foundation for building successful/profitable quantitative trading systems.
- Apply the state-of-the-art best practices for Algorithmic trading or algo trading.
- Essential Python, specifically for quantitative trading and financial markets.
- Take your financial skills to the next level.
- How to acquire financial data for quant trading.
- Perform financial analysis in Python.
- Develop your own multi-asset strategies.
- Analyse your strategies and feel confident about deploying your ideas in the market.
Requirements
- Motivated to make systematic, profitable trading/investment systems.
- Open minded and motivated to apply new methods.
- No prior programming experience is required.
- You’ll need to install Anaconda and Python. We will show you how to do that step by step.
Description
**Programming and quantitative trading course taught by in-the-industry algorithmic traders**
Whether you are an experienced trader or financial market novice, this course is for you! With both qualification and experience in quantitative subjects and financial markets, we bring you a practical approach to quantitative trading.
We won’t make you grind through a lengthy Python crash course. Instead, we will teach you the most essential and relevant Python programming for financial markets in small and focussed steps, with real data and plenty of real-world examples. By the end of the course, you’ll be able to expand your trading edge by constructing your own ideas quickly and put them to test in the real world.
In this quantitative trading course you will learn:
How to access and use financial data;
How to process and visualise the data, so that you can spot any trends and/or patterns and work them into your trading strategies;
Fundamental building blocks for financial analysis, including how to handle date and time, calculating returns and volatility, probing the market with correlation analysis and linear regression analysis---tricks used by the professionals;
How to speed up your programs, we will take you on the Python information superhighway;
How to build a trading strategy and backtest from scratch and run in-depth analysis of the results.
… and much, much more!
We will walk you through advanced strategy concepts beyond retail level. For the price of two cups of coffee, you have the power to supercharge your trading and gain a competitive edge to beat the market.
Enrol today and enjoy:
High-quality, up-to-date video lectures
Python Jupyter Notebooks
Exercises to sharpen your skills
30 day, no questions asked, money back guarantee
Make a great step towards quantitative trading, all in a fun and practical way!
See you in the course!
Who this course is for:
- Anyone who wants to grow their trading/investment capital.
- Anyone interested in quantitative trading.
- Traders and investors who are new to programming, and want to focus on the most relevant skills and produce results quickly and efficiently, to boost your career in trading.
- The course is also suitable for beginners, as it starts from the fundamentals and gradually builds up your skills.
Instructors
![Tom Starke](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.3 Instructor Rating
- 254 Reviews
- 2,065 Students
- 2 Courses
Dr Tom Starke is the CEO of AAAQuants, an algorithmic trading and consulting firm. He has a PhD in Physics and previously held positions as a senior scientist at Oxford University and principal engineer at Rolls-Royce. Tom has since worked in the financial industry with hedge funds and proprietary trading firms such as Vivienne Court and Genesis with a special focus on data analytics and AI. He is the author of over 20 scientific papers, presents at conferences around the world and is a lecturer and faculty member for Quantopian and Quantinsti.
- 4.3 Instructor Rating
- 254 Reviews
- 2,065 Students
- 2 Courses
Dr Zhu has a PhD in Microwave Engineering. She has worked at the National Measurement Institute of Australia conducting research projects on high frequency precision measurement techniques. She was also part of a global telecommunications R&D team at CommScope, conducted extensive numerical simulation and optimisation works. Over the recent years, Dr Zhu is passionate about solving challenging financial/FinTech problems using advanced analytics, especially machine learning and AI. Her most recent specialised areas at AAA Quants and Foresight Analytics revolve around credit risk modelling and predictive modelling in Finance.