DUCKQUANT / THE QUANT & AI DIRECTORY
14,444 resources, ranked by in-directory PageRank
Showing 5,365–5,400 of 14,444 resources
High frequency trading (HFT) framework built for futures using machine learning and deep learning techniques
Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting
This solution presents an accessible, non-trivial example of machine learning (Deep learning) with financial time series using TensorFlow
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
Democratizing Internet-scale financial data.
Scalable and user friendly neural :brain: forecasting algorithms.
Experimental code supporting the results presented in the scientific research paper entitled "An Application of Deep Reinforcement Learning to Algorithmic…
A Deep Reinforcement Learning Framework for Stock Market Trading
Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
HFTFramework utilized for research on " A reinforcement learning approach to improve the performance of the Avellaneda-Stoikov market-making algorithm "
Open tool for retrieving corporate and financial data from SEC EDGAR filings.
Python library for downloading standardized financial statements and share prices from SimFin.
A tutorial for algorithmic trading bot using machine learning.
Public repository by Luchkata. Primary language: Jupyter Notebook.
BERT for Finance : UC Berkeley MIDS w266 Final Project
FinSight - Financial Insights at Your Fingertip: FinSight is a cutting-edge AI assistant tailored for portfolio managers, investors, and finance enthusiasts.…
Technical and sentiment analysis to predict the stock market with machine learning models based on historical time series data and news article sentiment…
A customized gym environment for developing and comparing reinforcement learning algorithms in crypto trading.
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of…
This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (
An environment to high-frequency trading agents under reinforcement learning
Acquiring data from Alpha Vantage and predicting stock prices with PyTorch's LSTM
Trying to create Reinforcement Learning powered Bitcoin trading bot
Trading with recurrent actor-critic reinforcement learning
Project analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple…
Compute fractional differentiation super-fast. Processes time-series to be stationary while preserving memory. cf. "Advances in Financial Machine Learning" by…
Team Kinetiz AutonomousRacing League Find Out More Eneron Magnus AI-Powered Armoured Beast Find Out More Redefining Robotics for a Smarter Future Find Out More…
docker based platfrom for developing algo trading strategies. Very interesting combinations of open source components were used including for backtest…
dataflow programming framework. Similar and probably replaceable by sklearn.pipeline module. Uses for visiualization though not maintained with last commit…
Deep learning framework for HFT algorithmic trading strategy development
We introduce the first end-to-end Deep Reinforcement Learning based framework for active high frequency trading.
Built a trading algorithm in Python for the Tesla stocks returning in 39% higher returns than a simple buy and hold strategy, over a…
Course Material for the machine learning in financial context bootcamp
This is my github repository where I post trading strategies, tutorials and research on quantitative finance with R, C++ and Python. Some of the…
unofficial repo based on . It's incomplete and not updated
Hard fork of and form the trading strategy as a classification problem with -1 (sell) 0 (hold) 1 (buy). Models used are…
