tsxgithub01

PaddleOCR

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

FinGPT

FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.

ocropy

Python-based tools for document analysis and OCR

bayesian_changepoint_detection

Methods to get the probability of a changepoint in a time series.

AlphaTrading

An workflow in factor-based equity trading, including factor analysis and factor modeling. For well-established factor models, I implement APT model, BARRA's risk model and dynamic multi-factor model in this project.

trading-backtest

A stock backtesting engine written in Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model

slow-momentum-fast-reversion

This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (https://arxiv.org/pdf/2105.13727.pdf).

bitcoin_volatility_forecasting

GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management

LearnRustEasy

本书在线阅读地址

STOCK-RETURN-PREDICTION-USING-KNN-SVM-GUASSIAN-PROCESS-ADABOOST-TREE-REGRESSION-AND-QDA

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Select Tradeable Stocks

IB-Trading-Models-And-Backtester

Modular trading models with Interactive Brokers and backtester in Python

CNN-TA

Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach: A novel algorithmic trading model CNN-TA using a 2-D convolutional neural network based on image processing properties.

winpcapy

A Modern Python wrapper for WinPcap

value-based-deep-reinforcement-learning-trading-model-in-pytorch

This is a repo for deep reinforcement learning in trading. I used value based double DQN variant for single stock trading. The agent learn to make decision between selling, holding and buying stock with fixed amount based on the reward returned from the environment.

binance-modest-trader

基于币安k线量化策略设计、简单回测、手动实盘

Nasdaq-HFT-FPGA

RTL design for a nasdaq compatible high frequency trading low level. Supports itch on moldudp64.

algo-trading-models-practice

repository for practicing and experimenting with new algorithmic trading models. Sharpen your skills, explore innovative strategies, and contribute to the world of algorithmic trading.

DMDstocks_python

Using dynamic mode decomposition to predict stock prices and execute a daily trading algorithm.

QuantitativeTrading

Quantitative trading Implement a portfolio management system and create investment models

XGBoost-model-applied-to-CBOT-Soybean-oil-closing-prices

CBOT Soybean oil closing price prediction using an XGBoost ML model applied to the 2014-2016 period. This the El Niño weather period. This model aims specifically at the soybean oil price performance & its forecasting vs the exchange listed contracts used hedging risk strategies & speculative bets traded at CBOT.

A-to-Z-Stock-Trading-Model

Stock trading model project

Financial-NLP-Models

Different NLP models from the book "Stefan Jensen, Machine Learning for Trading, 2020" implemented using Julia programming language.

ML-Model

The stock prediction system has data collection, preprocessing, feature selection, model training and evaluation modules. It generates real-time trading signals based on trained models.

Price_Prediction_Using_Machine_Learning

Price prediction: The use of machine learning to predict future prices of goods or services. Approach: Uses historical data and statistical models to identify patterns and trends. Potential applications: Financial trading, product pricing, and inventory management.

fuzzy-volatility-modeling

Modeling of volatility of publicly traded financial instruments using fuzzy logic theory

High-Frequency-Trading-using-ML

Q_learning_FOREX

Attempt to train a Q-learning model to FOREX trade.

Volatility-Forecast-LSTM

Forecasting High Frequency Volatility based on Long Short-Term Memory（LSTM） model and price information—An example of Shanghai Composite Index

Technical-Trading-Strategies-Using-Machine-Learning-and-Deep-Learning-Models

Improve Technical Trading Strategies Using Machine Learning Models

Quantitative-Finance-Model-Visualizer-Using-High-Frequency-Trading-Algorithms

Quantitative Finance Model Visualizer Using High-Frequency Trading Algorithms