DUCKQUANT / THE QUANT & AI DIRECTORY
1,177 resources, ranked by in-directory PageRank
My Financial Industry ML Applications and Credit Risk models for my final project in the Financial Engineering masters program
This repository is for the demonstration of our work, "Market Making with Deep Reinforcement Learning from Limit Order Books"
Limit Order Book data analysis and modeling using LSTM network
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading
Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al
A stock market simulator that generate best trading strategy using machine learning tools
TensorTrade-NG is an open source Python framework for building, training, evaluating, and deploying robust trading algorithms using reinforcement learning
Reinforcement Learning for Automated Trading
This is the code implementation of the paper "Financial Trading as a Game: A Deep Reinforcement Learning Approach"
Tries to predict if a stock will rise or fall with a certain percentage through giving probabilities of what events it thinks will happen
Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and dynamic stock…
The work aims to explore Value based, Deep Reinforcment Learning (Deep Q-Learning and Double Deep Q-Learning) for the problem of Optimal Trade Execution. The
Developed a deep learning model that allows trading firms to analyze large patterns of stock market data and look for possible permutations to increase…
Another attempt to use Deep-Learning in the financial markets
Deep Q-Learning Applied to Algorithmic Trading
Attempt to replicate: A deep learning framework for financial time series using stacked autoencoders and long- short term memory
Financial Time Series Forecasting using Deep Learning Techniques and Innovative Image Encoding Approaches
PhD Thesis: "Data Science in the Modeling and Forecasting of Financial Timeseries: from Classic methodologies to Deep Learning"
Option Pricing, Volatility Prediction, Machine Learning, Black Scholas, Web Crawling
A financial market analysis pipeline with technical indicators, machine learning, and charts
Machine learning-driven financial trading strategy: momentum prediction, regime detection, and enhanced trading decisions
Mlfin.py is an advance Machine Learning toolbox for financial applications in Python
The random forest, FFNN, CNN and RNN models are developed to predict the movement of future trading price of Netflix (NFLX) stock using transaction…
Robust Market Making via Adversarial Reinforcement Learning
This repository contains the main code used in the paper "Deep Reinforcement Learning for Market Making Under a Hawkes Process-Based Limit Order Book Model"
Optimal control of risk aversion in Avellaneda Stoikov high frequency market making model with Soft Actor Critic reinforcement learning
Training an Agent to make automated trading decisions in a simulated stochastic market environment using Reinforcement Learning or Deep Q-Learning
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading
S&P100 stocks analysis via Graph Neural Networks (Forecasting, Clustering, Trend classification, Stocks ranking for optimal stock picking)
1. First we fetch data of stocks in realtime from nse India website, perform basis data visualizations using python to analyze the stock. 2.…
Deep Learning methods to solve path-dependent PDEs / to price path-dependent derivatives like exotic options
The project focused on the use of public data to assess the economic situation in the country based on the state of the stock…
MBATS is a docker based platform for developing, testing and deploying Algorthmic Trading strategies with a focus on Machine Learning based algorithms. This
Official implementation for the paper: Deep Learning under Continuous Distribution Shift: The Non-Stationary NTK and Spectral Tracking SDE for Quantitative
Quantitative portfolio construction and optimization platform built on skfolio and scikit-learn
(Work In Progress) Implementation of "Financial Time Series Prediction Using Deep Learning"
