
Implement a master configuration file to manage portfolio settings and run the long biased momentum strategy via the brokerage configuration, avoiding code changes by adjusting the file.
Complete the service class API implementation and create an order config by finalizing the Orlando Savage class API.
Test the Python client connection to an open MT4 terminal via a TCP socket using the zero and two connector, ensuring the antifraud terminal message is received before printing.
Continue writing the Darwin X configuration files to align with contract specifications for the Darwinex wrapper API and configs.
Integrate darwinex strategy configs to test strategy performance by net assets on the loan by instrument and functional medicine, while finishing market setup for client-focused events.
Multi-Strategy Quant Systems in Python from Scratch - A First Course in Algorithmic Trading by HangukQuant.
As this is not a Python tutorial, we get right down to business and adopt a no-nonsense coding approach. It is advised that you slow down the pace of the course to your own needs. Even though only 7 hours of lectures have been distilled, the material within is fairly heavy. It is a walkthrough without the introductory explanations - since there are no explanations within the lecture walkthroughs, all students are expected to be hands-on and actively participate by asking questions; which we will compile in the Questions Section. Code is downloadable in Checkpoint Lectures.
Watch a (sped-up) live recording of a quant implementing a shoestring trading system for non-HFT in Python, from data pipelines to order management. Build robust and flexible modular systems + take home a professional setup to adapt and improve.
HangukQuant is the author of the quant trading blog on Substack- Mathematics, Finance and Their Babies, with many years of experience in quant trading.
Implement a Multi Strategy Quantitative System in Python from Scratch, while learning how to build robust frameworks for implementation of alpha signals and capital allocation. Learn industry standards in risk management, such as volatility targeting schemes and technical diversification. Code along an algorithmic trading system with modular approaches to integrate with multiple brokerages and switch between them in a matter of seconds, all with the same code.
Build diagnostic tools to analyse your trading system.
Integrate with multiple brokerages in a single code base.
Learn industry standards in risk management, such as volatility targeting schemes and technical diversification.
Take back with you the final product - Your Very Own, Robust Quant Systems to hone and develop!
Build quantitative strategies implementing factor premia and be given guidance for serious students of the market.
This course is not a beginner course; financial literacy, and programming methodology is expected. Students are expected to be able to understand code without being prompted, or at least learn how to comprehend medium-sized code systems of thousands of lines of code.
The course was first recorded and then sped up and voiced over chosen sections to meet Udemy course requirements. You may also choose to code along without the audio as the textual explanations should be primarily useful. As the course is an Advanced-Intermediate level, do note that you may face some difficulties along the way. It is expected that you would need to rewatch some of the lectures, and please do ask away in the Questions Section.
Those without programming experience are encouraged to first undergo courses in Python / Programming Methodology / Data Science for Finance courses.
Note that this course is not part of the Udemy Deals program, and no Udemy promotions are available. We believe that the material within is highly valuable and the cost price is cost de minimis in your quant journey.