Showing 347 open source projects for "strategy"

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  • 1
    QuantDinger

    QuantDinger

    AI-driven, local-first quantitative trading platform for research

    QuantDinger is a local-first, open-source quantitative trading platform designed to bring AI-assisted analysis, strategy development, backtesting, and live execution into a self-hosted workspace where data and API credentials remain under your control. Unlike cloud-locked quant services, it lets users run the entire trading workflow on their own infrastructure using Docker, with a PostgreSQL database backend, a Python backend API, and a web frontend UI that supports visualization and strategy management. ...
    Downloads: 5 This Week
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  • 2
    Freqtrade

    Freqtrade

    Free, open source crypto trading bot

    ...Write your strategy in python, using pandas. Example strategies to inspire you are available in the strategy repository. Download historical data of the exchange and the markets you may want to trade with. Find the best parameters for your strategy using hyper optimization which employs machining learning methods.
    Downloads: 8 This Week
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  • 3
    OctoBot

    OctoBot

    Cryptocurrency trading bot for TA, arbitrage and social trading

    ...Moreover, when a favorable trend is spotted, it can be difficult to maximize profit from it: trading takes a lot of time, and when it's done automatically how to be sure that the robot will do what it is supposed to? By using OctoBot, you will be able to automate your trades with the strategy you have chosen and the markets you want. Whether you are a beginner or an expert trader, each strategy is testable easily without any limit. You can use an existing setup or try and customize your own until you identify the perfect settings for your trading goals and proceed with real money trading and make real gains.
    Downloads: 3 This Week
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  • 4
    Backtrack Sampler

    Backtrack Sampler

    An easy-to-understand framework for LLM samplers

    Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs.
    Downloads: 0 This Week
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  • 5
    Tauric TradingAgents

    Tauric TradingAgents

    Multi-Agents LLM Financial Trading Framework

    Tauric TradingAgents is a multi-agent AI framework designed for financial analysis, strategy generation, and automated trading workflows. It coordinates multiple specialized agents that collaborate on tasks such as data analysis, signal generation, and risk evaluation. The system enables complex reasoning by distributing responsibilities across agents, improving decision-making quality. It supports integration with market data sources and trading environments for real-world application. ...
    Downloads: 8 This Week
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  • 6
    ThetaGang

    ThetaGang

    ThetaGang is an IBKR bot for collecting money

    ThetaGang is an IBKR trading bot for collecting premiums by selling options using "The Wheel" strategy. The Wheel is a strategy that surfaced on Reddit but has been used by many in the past. This bot implements a slightly modified version of The Wheel, with my own personal tweaks. The strategy, as implemented here, does a few things differently from the one described in the post above. For one, it's intended to be used to augment a typical index-fund-based portfolio with specific asset allocations. ...
    Downloads: 0 This Week
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  • 7
    DeepSeek-V3

    DeepSeek-V3

    Powerful AI language model (MoE) optimized for efficiency/performance

    ...It employs Multi-head Latent Attention (MLA) and the DeepSeekMoE architecture to enhance computational efficiency. The model introduces an auxiliary-loss-free load balancing strategy and a multi-token prediction training objective to boost performance. Trained on 14.8 trillion diverse, high-quality tokens, DeepSeek-V3 underwent supervised fine-tuning and reinforcement learning to fully realize its capabilities. Evaluations indicate that it outperforms other open-source models and rivals leading closed-source models, achieving this with a training duration of 55 days on 2,048 Nvidia H800 GPUs, costing approximately $5.58 million.
    Downloads: 64 This Week
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  • 8
    Heretic

    Heretic

    Fully automatic censorship removal for language models

    Heretic is an open-source Python tool that automatically removes the built-in censorship or “safety alignment” from transformer-based language models so they respond to a broader range of prompts with fewer refusals. It works by applying directional ablation techniques and a parameter optimization strategy to adjust internal model behaviors without expensive post-training or altering the core capabilities. Designed for researchers and advanced users, Heretic makes it possible to study and experiment with uncensored model responses in a reproducible, automated way. The project can decensor many popular dense and some mixture-of-experts (MoE) models, supporting workflows that would otherwise require manual tuning. ...
    Downloads: 73 This Week
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  • 9
    openage

    openage

    Open source clone of the Age of Empires II engine

    openage is a free cross-platform RTS game engine that provides the mechanics of Age of Empires. Using modern technologies as C++17, OpenGL/GLSL, Python, Qt5 and CMake allows people using GNU/Linux, BSD, macOS or Windows to play the game natively. Our aim is to make openage a platform for the original Age of Empires games providing the same look and feel, but with more features for modding and multiplayer. openage uses an open API powered by our human-readable configuration language nyan. We...
    Downloads: 4 This Week
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  • 10
    AIQuant

    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. Stock trading strategies: large models, factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, high-frequency trading, etc. ...
    Downloads: 0 This Week
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  • 11
    PowerTrader_AI

    PowerTrader_AI

    Fully automated crypto trading powered by a custom price prediction AI

    PowerTrader_AI is a fully open-source, automated cryptocurrency trading bot that combines a custom price prediction AI with a structured and tiered dollar-cost averaging (DCA) strategy to make real trading decisions on behalf of users. It continuously analyzes market data to forecast high and low price levels across multiple timeframes, using those predictions to determine when to open, scale into, or close positions automatically, which aims to take emotion out of trading and enforce discipline. The bot integrates with popular exchange APIs so it can execute real buy and sell orders, manage risk, and maintain position sizing without manual intervention, making it suitable for algorithmic traders who want hands-off operations. ...
    Downloads: 3 This Week
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  • 12
    ValueCell

    ValueCell

    Community-driven, multi-agent platform for financial applications

    ValueCell is a community-driven multi-agent AI platform focused on financial research, analysis, and decision-making that lets users leverage multiple specialized AI agents for tasks like data retrieval, investment research, strategy execution, and market tracking. The system brings together a suite of collaborative agents—such as research agents that gather and interpret fundamentals, strategy agents that implement trading logic, and news agents that deliver personalized updates—to help users make more informed financial decisions across stocks, crypto, and other markets. ...
    Downloads: 1 This Week
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  • 13
    easyquant

    easyquant

    Stock quantification framework to support market acquisition

    easyquant is a Python quantitative-trading framework built on top of easytrader for execution and easyquotation for market data. Its event-driven architecture is inspired by vn.py and routes market updates into user-defined strategies. The default configuration can stream broad Sina market data at roughly one-second intervals. Alternative quotation sources can be substituted, including selected depth and fund data supported by easyquotation. Trading support includes several Chinese broker...
    Downloads: 0 This Week
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  • 14
    AutoHedge

    AutoHedge

    Build your autonomous hedge fund in minutes

    ...It is built around the concept of algorithmic hedging, where strategies are executed programmatically rather than manually, enabling faster and more consistent responses to market changes. The system supports integration with financial data sources, allowing it to process real-time or historical data for analysis and strategy execution. It also emphasizes modularity, enabling developers to customize strategies, risk parameters, and decision logic. AutoHedge is particularly useful for experimentation and research in algorithmic trading and financial automation. Overall, it represents an attempt to bring agent-based intelligence into portfolio management and risk mitigation workflows.
    Downloads: 1 This Week
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  • 15
    Zipline Reloaded

    Zipline Reloaded

    Zipline, a Pythonic Algorithmic Trading Library

    ...It continues the original Zipline project after Quantopian ended operations. Developers write trading algorithms while the engine simulates orders, market events, portfolio changes, and strategy performance over historical data. Common statistics such as moving averages and linear regression are available within algorithm workflows. Pandas-based input and output integrate naturally with the broader Python data-science ecosystem. Strategies can also use libraries such as SciPy, Matplotlib, statsmodels, and scikit-learn for analysis and modeling. ...
    Downloads: 0 This Week
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  • 16
    Nothing Ever Happens

    Nothing Ever Happens

    Focused async Python bot for Polymarket

    Nothing Ever Happens is an experimental open-source trading bot designed for the Polymarket platform that implements a deliberately simple and unconventional strategy: automatically buying “No” positions across non-sports binary prediction markets. The project is built in Python using asynchronous architecture, allowing it to monitor markets, evaluate opportunities, and execute trades continuously with minimal latency. Its core concept is based on statistical observations that a majority of prediction market outcomes resolve negatively, and it attempts to exploit this base-rate bias through systematic participation rather than predictive modeling. ...
    Downloads: 0 This Week
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  • 17
    talos

    talos

    Hyperparameter Optimization for TensorFlow, Keras and PyTorch

    Talos radically changes the ordinary Keras, TensorFlow (tf.keras), and PyTorch workflow by fully automating hyperparameter tuning and model evaluation. Talos exposes Keras and TensorFlow (tf.keras) and PyTorch functionality entirely and there is no new syntax or templates to learn. Talos is made for data scientists and data engineers that want to remain in complete control of their TensorFlow (tf.keras) and PyTorch models, but are tired of mindless parameter hopping and confusing...
    Downloads: 0 This Week
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  • 18
    Lama Cleaner

    Lama Cleaner

    Image inpainting tool powered by SOTA AI Model

    Image inpainting tool powered by SOTA AI Model. Remove any unwanted object, defect, or people from your pictures or erase and replace(powered by stable diffusion) anything on your pictures. Lama Cleaner is a free, open-source and fully self-hostable inpainting tool powered by state-of-the-art AI models. You can use it to remove any unwanted object, defect, or people from your pictures or erase and replace anything on your pictures. Many AICG creators are using Lama Cleaner to clean-up their...
    Downloads: 28 This Week
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  • 19
    Quantitative Trading System

    Quantitative Trading System

    A comprehensive quantitative trading system with AI-powered analysis

    Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and generating trading signals based on quantitative models. ...
    Downloads: 0 This Week
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  • 20
    Nevergrad

    Nevergrad

    A Python toolbox for performing gradient-free optimization

    ...Nevergrad supports parallelization, budget scheduling, and multiple cost/resource constraints, allowing it to scale to nontrivial optimization problems. It includes visualization tools and diagnostic metrics to compare strategy performance, track parameter evolution, and detect stagnation.
    Downloads: 0 This Week
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  • 21
    qaqarot

    qaqarot

    Quantum Computer Library for Everyone

    The Blueqat project has been renamed the Qaqarot Project because of the branding strategy of blueqat inc.
    Downloads: 0 This Week
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  • 22
    LongCat-Video

    LongCat-Video

    Foundational video generation model with 13.6B parameters

    ...A unified architecture handles text-to-video, image-to-video, and video-continuation tasks without separate models. It is pretrained for continuation, allowing it to create minutes-long sequences while limiting color drift and quality loss. A coarse-to-fine strategy operates across time and space to produce 720p video at 30 frames per second efficiently. Block Sparse Attention reduces high-resolution inference costs, while multi-reward GRPO training improves visual quality and prompt alignment. The repository includes inference scripts for single- and multi-GPU execution, model-download instructions, and interactive generation examples. ...
    Downloads: 18 This Week
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  • 23
    AIDE ML

    AIDE ML

    AI-Driven Exploration in the Space of Code

    AIDE ML is an open-source research framework designed to explore automated machine learning development through agent-based search and code optimization. The project implements the AIDE algorithm, which uses a tree-search strategy guided by large language models to iteratively generate, evaluate, and refine code. Instead of relying on manual experimentation, the agent autonomously drafts machine learning pipelines, debugs errors, and benchmarks performance against user-defined evaluation metrics. The system repeatedly improves its generated code by exploring different implementation paths and selecting the best-performing solutions. ...
    Downloads: 13 This Week
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  • 24
    DreamO

    DreamO

    A Unified Framework for Image Customization

    ...DreamO’s design introduces a feature routing constraint that helps disentangle different control conditions (like identity, style, clothing) when more than one is specified, which significantly reduces conflicts and artifacts when combining controls. It also uses a “placeholder strategy” to precisely align conditional inputs (e.g. where to place clothing or objects) in generated images, giving users fine-grained control over composition.
    Downloads: 0 This Week
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  • 25
    Diplomacy Cicero

    Diplomacy Cicero

    Code for Cicero, an AI agent that plays the game of Diplomacy

    ...The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. ...
    Downloads: 0 This Week
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