Free Getting Started with the Quantopian Pipeline API course
Making use of the Quantopian Pipeline API to select security dynamically for your algo
Make use of Pipeline to dynamically select assets for trading
Understand the difference between Factors, Filters and Classifiers and how to combine them
Develop your own Custom Factors
Start creating your own trading algorithm
Utilize institutional strength platform to develop your own algorithm
Quickly prototype and back test your ideas
In this course you will learn how to utilise the Quantopian Pipeline API to create your own algorithm.
The course will cover the basics and purpose of Quantopian Pipeline, and how you can make use of it to dynamically select specific sets of assets to trade. The Quantopian Pipeline works seamlessly between the research platform and IDE, the course will highlight the similarities and differences of the working of Pipeline in each platform.
Starting with the steps needed to run a Pipeline to the different computations that can be expressed in Pipeline, the course will demonstrate how one can create and run a Pipeline and identify the main components in order for Pipeline to run successfully. Factors, filters, and classifiers will be covered.
Quantopian provides a diverse range of datasets to break down the traditional barriers to assist algorithm writers to develop institutional strengths algorithm. The Quantopian Pipeline also allows writers to develop their own Custom Factors.
Please note that this course will not teach you how to use Python. It assumed a certain level of competency with Python and in particular Jupyter Notebook. The course teaches you how to make use of the Quantopian Pipeline API to develop algo. It does NOT cover trading strategies nor does it teach you how to make money. This course is provided for educational purpose.
Course Published By Anthony NG (Average rating- 4.8/5, Total Ratings- 8 )
Short Biography of Instructor:
Anthony Ng has spent the last seven years as a Senior Lecturer at Nanyang Polytechnic teaching algorithmic trading, financial data analysis, banking, finance, investment and portfolio management. His students, whom he coached, went on doubling their equity in 10 days and won the 2016 CME Group Trading Challenge beating 400 other university teams.
He assists Quantopian, a Boston-based Hedge Fund, to conduct Algorithmic Trading Workshops in Singapore and has presented in the recent QuantCon Singapore 2016. You can find a lot of his Algorithmic Trading tutorials by visiting his YouTube channel. Just click the YouTube icon to visit his channel.
Passionate with finance, data science and python, Anthony enjoyed researching, teaching and sharing on these topics. Anthony studied Masters of Science in Financial Engineering at NUS Singapore.