Search Results for "open-shell"
Sort By:
Showing 26 open source projects for "open-shell"
View related business solutions-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
-
1
NautilusTrader
A high-performance algorithmic trading platform
NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. -
2
Flowsurface
A native desktop charting platform for crypto markets
Flowsurface is a powerful open-source desktop charting platform tailored for crypto markets, built primarily in Rust with a focus on real-time data visualization and market microstructure analysis. Instead of traditional price charts alone, Flowsurface emphasizes order flow and liquidity visualization through advanced chart types like historical DOM heatmaps, footprint charts, and depth ladder displays. -
3
PyBroker
Algorithmic Trading in Python with Machine Learning
Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance. -
4
Kalshi Trading Bot CLI
AI-native CLI for trading Kalshi prediction markets
Kalshi Trading Bot CLI is an AI-driven command-line tool designed to automate trading strategies on Kalshi prediction markets by combining quantitative modeling with real-time market data. It operates by conducting deep research on events, generating independent probability estimates, and comparing those estimates against current market prices to identify trading opportunities. The system incorporates advanced decision-making logic, including Kelly criterion-based position sizing and a... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
-
5
GoCryptoTrader
Trading bot and framework supporting multiple exchanges
GoCryptoTrader is a full framework / bot for cryptocurrency trading, written in Go (Golang). It supports multiple exchanges, real-time and historic data, backtesting, handling order books, portfolio management, scripting, and many exchange integration features. It is a trading engine that can be run by users to automate strategies across many exchanges. Licensed under MIT. Support for all exchange fiat and digital currencies, with the ability to individually toggle them on/off. Customisation... -
6
Optopsy
A nimble options backtesting library for Python
Optopsy is a Python-based, nimble backtesting and statistics library focused on evaluating options trading strategies like calls, puts, straddles, spreads, and more, using pandas-driven analysis. The csv_data() function is a convenience function. Under the hood it uses Panda's read_csv() function to do the import. There are other parameters that can help with loading the csv data, consult the code/future documentation to see how to use them. Optopsy is a small simple library that offloads... -
7
Roboquant
User-friendly and completely free algorithmic trading platform
Roboquant is an open-source algorithmic trading platform written in Kotlin. It is flexible, user-friendly and completely free to use. It is designed for anyone serious about algo-trading. So whether you are a beginning retail trader or an established trading firm, Roboquant can help you to quickly develop robust and fully automated trading strategies. -
8
AIQuant
AI-powered platform for quantitative trading
ai_quant_trade is an AI-powered, one-stop open-source platform for quantitative trading—ranging from learning and simulation to actual trading. It consolidates stock trading knowledge, strategy examples, factor discovery, traditional rules-based strategies, various machine learning and deep learning methods, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Jupyter Notebook examples for practical hands-on use. -
9
Superalgos
Free, open-source crypto trading bot, automated bitcoin trading
Free, open-source crypto trading bot, automated bitcoin/cryptocurrency trading software, algorithmic trading bots. Visually design your crypto trading bot, leveraging an integrated charting system, data-mining, backtesting, paper trading, and multi-server crypto bot deployments. Superalgos is not just another open-source project. We are an open and welcoming community nurtured and incentivized with the project's native Superalgos (SA) Token, building an open trading intelligence network. ... -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
10
TradingGoose Studio
Technical analysis + LLM powered trading workflows
TradingGoose Studio is an open-source AI workflow platform designed to enable advanced financial trading analysis and automation through a visual, modular interface powered by large language models. It combines traditional technical analysis with modern AI-driven decision-making by allowing users to build workflows where multiple specialized agents collaborate to interpret market signals and execute actions. -
11
Barter
Open-source Rust framework for building event-driven systems
Barter is an open-source, Rust-based ecosystem of libraries for building high-performance, event-driven algorithmic trading systems—covering live trading, paper trading, and backtesting. It is designed for safety, speed, and flexibility in quantitative finance workflows. Use mock MarketStream or Execution components to enable back-testing on a near-identical trading system as live-trading. -
12
Awesome-Quant
A curated list of insanely awesome libraries, packages and resources
...It includes tools, frameworks, research papers, blogs, datasets, etc. It aims to help people working in algorithmic trading, quant investing, financial engineering, etc., find useful open source or educational resources. Licensed under typical “awesome” list standards. -
13
AutoTrader
A Python-based development platform for automated trading systems
AutoTrader is a Python-based platform—now archived—designed to facilitate the full lifecycle of automated trading systems. It provides tools for backtesting, strategy optimization, visualization, and live trading integration. A feature-rich trading simulator, supporting backtesting and paper trading. The 'virtual broker' allows you to test your strategies in a risk-free, simulated environment before going live. Capable of simulating multiple order types, stop-losse,s and take-profits,... -
14
roboquant
roboquant is a very fast algo-trading platform
Roboquant is an open source algorithmic trading platform written in Kotlin. It is very fast, flexible, user-friendly and completely free to use. It is designed for anyone serious about algo-trading. So whether you are a beginning retail trader or an established trading firm, roboquant can help you to quickly develop fully automated trading strategies. -
15
AnyTrading
The most simple, flexible, and comprehensive OpenAI Gym trading
gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex. -
16
TradingGym
Trading backtesting environment for training reinforcement learning
TradingGym is a toolkit (in Python) for creating trading and backtesting environments, especially for reinforcement learning agents, but also for simpler rule-based algorithms. It follows a design inspired by OpenAI Gym, offering various environments, data formats (tick data and OHLC), and tools to simulate trading with costs, position limits, observation windows etc. Licensed under MIT. This training environment was originally designed for tickdata, but also supports OHLC data format. WIP.... -
17
Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. Installing Zipline is slightly more involved than the average Python... -
18
AlphaPy
Python AutoML for Trading Systems and Sports Betting
AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow.... -
19
EliteQuant
A list of online resources for quantitative modeling, trading, etc.
EliteQuant is a curated directory of online resources for quantitative finance: trading, portfolio management, quantitative modeling, data sources, libraries, platforms, and communities. It is not a software library per se, but a “list of things” - i.e., an aggregator of open source projects, blogs, tools etc., intended to help practitioners find useful resources. It is licensed under Apache-2.0, and maintained by volunteers. A list of online resources for quantitative modeling, trading, and portfolio management. Has criteria for recommending projects/resources to help keep quality up. -
20
StockSharp
Algorithmic trading and quantitative trading open source platform
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).StockSharp (shortly S#) – are free programs for trading at any markets of the world (American, European, Asian, Russian, stocks, futures, options, Bitcoins, forex, etc.). You will be able to trade manually or automated trading (algorithmic trading robots, conventional or HFT). -
21
LEAN
Lean algorithmic trading engine by QuantConnect
Automated accounting for splits, dividends, and corporate events like delistings and mergers. Avoid selection bias with dynamically generated assets. Create and select asset universes on proprietary data and indicators. Automatically track portfolio performance, profit and loss, and holdings across multiple asset classes and margin models in the same strategy. Trigger regular functions to occur at desired times, during market hours, on certain days of the week, or at specific times of day.... -
22
QuantComponents
Free Java components for Quantitative Finance and Algorithmic Trading
An open-source framework for financial time-series analysis and algorithmic trading, based on Java and OSGi, with an Eclipse front-end. * Highly modular: usable as plain java API, OSGi components, or integrated into Eclipse * Standalone or client-server architecture, depending on performance and reliability needs * Integrated with Interactive Brokers through IB Java API * Generic broker API, it can easily be extended to work with other brokers * It works with historical and/or realtime market data * Backtesting facility * Extensible SWT charting library -
23
Open Exchange (OpEx)
The open source Algorithmic Trading System
OpEx is an application suite that includes the main building blocks of commercial electronic trading systems. All OpEx applications run on distributed system architectures. -
24
A suite of libraries and applications using genetic algorithms and AI for financial analysis and simulation. Currently the focus is to route FIX messages to an exchange simulator and use genetic algorithms to explore algorithmic trading strategies.
-
25
