Find big moving stocks before they move using machine learning and anomaly detection
The AMLSim project is intended to provide a multi-agent based simulator that generates synthetic banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing machine learning models and graph algorithms. We welcome you to enhance this effort since the data set related to money laundering is …
🚜 🌾 A DeFi app, which provides staking & farming functions are deploy-able with a website, for yield farming.
This repository contains the customized trading algorithms that I have created using the Quantopian IDE.
A vectorized implementation of py_vollib, that supports numpy arrays and pandas Series and DataFrames.
Projeto de interface grafica, Programa Desktop, para gestor de Finanças Pessoais
GnuCash Pocket – a mobile companion app for Gnucash desktop application (https://github.com/Gnucash/gnucash). Developed independently of GnuCash.
Projeto financeiro usando domain driven design, tdd, arquitetura hexagonal e solid
iOS 14 Widget for Banking application built with SwiftUI
A personal budgeting app that helps you figure out where your money went, plan your budget ahead of time and analyze past expenditures.
Track expenses effortlessly with zer0 - an open-source, lightweight app. No servers, no cloud - your data stays on your device using MongoDB Realm. Choose themes, manage categories, and sync seamlessly. Features: account creation, expense tracking, category modification, insightful analytics, debt tracking.
Fingrom -- open-source platform-agnostic financial accounting application
💲💰 Personal Finance Manager API
Heliosfinance is designed to assist finance developers by providing free access to data, a structured project setup for using Jupyter Notebooks with various tools. Share and gain knowledge!
Codes and dashboards for 4th place solution for Kaggle's Home Credit Default Risk competition
Laravel Powered Finance Tracker and CRM
stock portfolio management system built with Django and deployed on Heroku
Algorithmic trading using heterogeneous graph neural network and reinforcement learning, pre-alpha
Fast, Multi threaded and Efficient Trade Matching Engine
Low latency Limit Order Book and Matching Engine created in C++, able to handle over 1.4 million transactions per second.
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