Analysis on systematic trading strategies (e.g., trend-following, carry and mean-reversion). The result is regularly updated.
-
Updated
May 29, 2024 - Jupyter Notebook
Analysis on systematic trading strategies (e.g., trend-following, carry and mean-reversion). The result is regularly updated.
Collection of notebooks and scripts related to financial engineering, quant-research and algo-trading.
hjalgos_notebooks
Utilizing reinforcement learning, this project implements a dynamic algorithmic trading strategy based on Q-learning with a deep Q-network. The Jupyter Notebook explores agent decisions on buying, selling, or holding Nasdaq stocks over a ten-year period (2014-2023).
Jupyter notebooks implementing Finance projects
Python notebook for simulating algorithmic stock trading
A 3 part series of Jupyter notebooks to help one find alpha in the stock market with AI
It is a Jupyter notebook that compares different trading strategies using technical analysis, machine learning, and deep learning methods.
Deep Neural Network Trading collection of Tensorflow Jupyter notebooks
Jupyter Notebooks to Help Discover New Crypto Currency Trading Strategies
Demo Notebooks for Quantitative Financee Using AlgoSeek
NodeJS Notebook for building algo trading strategies 💦
Explore OpenBB SDK without having to install anything on your local machine. You just need a GitHub and a GitPod account.
Machine Learning Bot is a Jupyter Notebook based application prototype to perform algorithmic trading using a Machine Learning algorithm.
An example of aggregating OHLC stock data using Data-Forge Notebook
zipline-broker Examples. Full notebooks plus python code for long term investment strategies using zipline based tools.
Some notebooks with powerful trading strategies.
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
Jupyter Notebooks Collection for Learning Time Series Models
Technical Analysis of Financial Data.
Add a description, image, and links to the algorithmic-trading topic page so that developers can more easily learn about it.
To associate your repository with the algorithmic-trading topic, visit your repo's landing page and select "manage topics."