Trading environment IB API - QT C++ - Flask - RL Model. Complete working example.
This video contains example of the trading environment wich uses Interactive Brokers API (TWS or IB Gateway), QT C++ client and reinforcement learning agent policy for action prediction. For policy (model) deployment, Flask is used. Also I'm using REST Api for communication between C++ client and RL policy model.
If you want to support this channel:
https://commerce.coinbase.com/checkou...
QT C++ client is currently in stagnation, but I think about renewing this project.
https://github.com/CloseToAlgoTrading...
Code from this video:
https://github.com/CloseToAlgoTrading...
Visual Studio Flask Tutorial:
https://code.visualstudio.com/docs/py...
Visual Studio Flask in a docker container
https://code.visualstudio.com/docs/co...
Presentation:
https://prezi.com/view/VOLEIzqZo1ihLz...
Content:
00:00 Intro
00:30 About IbTradeQt
00:48 Content overview
01:16 Changes in RL Model Overview
03:08 Model deployment with Flask
06:52 QT + REST API
10:50 Running all together