Search Results for "as built"
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Showing 9 open source projects for "as built"
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Qbot
AI-powered Quantitative Investment Research Platform
Qbot is an open source quantitative research and trading platform that provides a full pipeline from data ingestion and strategy development to backtesting, simulation, and (optionally) live trading. It bundles a lightweight GUI client (built with wxPython) and a modular backend so researchers can iterate on strategies, run batch backtests, and validate ideas in a near-real simulated environment that models latency and slippage. The project places special emphasis on AI-driven strategies — including supervised learning, reinforcement learning and multi-factor models — and offers a “model zoo” and example strategies to help users get started. ... -
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Kalshi Trading Bot CLI
AI-native CLI for trading Kalshi prediction markets
...The system incorporates advanced decision-making logic, including Kelly criterion-based position sizing and a structured multi-step risk evaluation process before executing trades. Built as a CLI application, it allows traders to interact programmatically with markets, making it suitable for automation and integration into larger trading pipelines. The tool emphasizes disciplined trading through its risk engine, ensuring that decisions are filtered through multiple validation layers before capital is committed. -
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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. This enables traders and analysts to understand actual executed trades, liquidity distribution, and tempo changes that often precede significant market movements. ... -
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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. -
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Kalshi-Quant-TeleBot
Kalshi Advanced Quantitative Trading Bot is an enterprise-grade
Built with a modular architecture, the system combines Python-based trading algorithms with a JavaScript Telegram bot interface for dynamic monitoring and interaction. The bot is designed to operate continuously, making data-driven decisions based on news sentiment analysis, statistical arbitrage opportunities -
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Peatio
Open-source crypto currency exchange software
Peatio is an open-source, Ruby on Rails–based core engine for building cryptocurrency exchange platforms. It serves as the accounting and trading backbone of the OpenDAX stack, designed around microservices. Peatio is a free and open-source cryptocurrency exchange implementation with the Rails framework. This is a fork of Peatio designed for microservices architecture. We have simplified the code in order to use only the Peatio API with external frontend and server components. Our mission is... -
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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. ... -
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PandoraTrader
C++ Trade Platform for quant developer
PandoraTrader is a high-frequency quantitative trading platform implemented in C++. It interfaces with real-world futures trading desks using Trade APIs and MarketData APIs and includes support for backtesting via simulated market components. We design such a trading platform with various skills given by the designer, but we do not carry wisdom; this wisdom belongs to the strategy designer. We hope that the strategy designer will design excellent strategies to give the trading software... -
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LEAN
Lean algorithmic trading engine by QuantConnect
...LEAN's highly modular foundation can easily be extended for your fund focus. Use combinations of margin, fill, and slippage models to simulate a liquidity endpoint. 100+ popular technical indicators built, tested, and ready for use. Applicable to any data source. -
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