DUCKQUANT / THE QUANT & AI DIRECTORY
1,177 resources, ranked by in-directory PageRank
Factor analysis for mutual funds
Comprehensive NLP techniques for accounting research
Risk measures and factors for alternative and responsible investments
Stanford Advanced Financial Technologies Laboratory
Identify social/historical cues for short term stock movement. Sklearn SVM model is used and good visualization coded in matplotlib
Finance risk engagement course resources
Riskiness of portfolios and assets
CEU python for finance course material
Efficient financial risk estimation via computer experiment design (regression variance-reduced sampling)
Valuation of Vanilla and Exotic option strategies (Butterfly, Risk Reversal etc.) with widget animations
Courant Institute of Mathematical Sciences, New York University
Mixture models and stock trading
Mixture models to predict market bottoms and regime changes based on a seminar given to quantinsti in 2017 and summary and video is .…
Analysis of luxury watch data to classify whether a certain model is likely to be over-or undervalued
Deep Reinforcement Learning for Trading.
Experiment-tracking platform for logging, comparing and sweeping machine-learning research runs.
Predict operation stocks points (buy-sell) with past technical patterns, and powerful machine-learning libraries such as: Sklearn.RandomForest.
Accompanying source codes for my book 'Mastering Python for Finance'.
Mean-Variance Optimization using DL (pytorch).
Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019.
From-scratch reimplementation of Google TimesFM (time-series foundation model) plus the full pretraining pipeline Google never open-sourced. Trained and.
Starter kit and resources for ACM ICAIF 2023 FinRL Contest. Website: https://open-finance-lab.github.io/finrl-contest.github.io/.
This repository collects awesome representative papers and resources for "From Pre-training to Post-training: A Survey on Time Series Foundation Models".
A deep learning method for event driven stock market prediction. Deep learning is useful for event-driven stock price movement prediction by proposing a novel.
A unified framework for machine learning with time series.
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models.
Python package that scrapes Korean Exchange (KRX) stock price, index and fundamental data.
Merlion: A Machine Learning Framework for Time Series Intelligence.
Quantitative research and educational materials.
The goal of this project was to create a deep-learning trading agent that can be paired with a trading platform to effectively trade equities…
Alpha Factors and Trading Algorithms on Quantopian created by Philip Kiely, Richard Greenbaum, Rudolph Hernandez, and Alex Foster for our Data Mining final
Algorithmic Trading project that examines the Fama-French 3-Factor Model and the Fama-French 5-Factor Model in predicting portfolio returns. The respective
This course, taught by Prof.Jerzy in NYU, applies the R programming language to momentum trading, statistical arbitrage (pairs trading), and other active
Credit Risk Model on Machine learning and prediction
Credit Risk Modelling Calculation of PD, LGD, EDA and EL with Machine Learning in Python
Reinforcement Learning Portfolio Optimization Framework
