Developing Options Trading Strategies using Technical Indicators and Quantitative Methods
-
Updated
Apr 22, 2024 - Python
Developing Options Trading Strategies using Technical Indicators and Quantitative Methods
Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.
Python library for portfolio optimization built on top of scikit-learn
Noba not only backtrader as a quantitative investment platform, but also visualized using bokeh, which can get richer plot effects. Additionally, Noba also provide 'Ioc Container', 'Event System', 'Database Abstraction Layer', 'Pipeline System' and more.
A Single Index Model shiny app for Australian ETFs
Use bokeh as the backend, you will get richer plot effects for backtrader
Investment comparison tool using Python
Q-finance approaches..
💰 HALM: A Highly Adaptive Learning Model for Portfolio Decision Making(投资组合决策的高度自适应学习模型)
This projects aims at creating a trading bot which can buy and sell equities in a given time frame based on certain benchmarks
Transformer-Based Multi-Factor Stock Selection
Collection of publicly available quant resouces.
Add a description, image, and links to the quantitative-investment topic page so that developers can more easily learn about it.
To associate your repository with the quantitative-investment topic, visit your repo's landing page and select "manage topics."