Showing 6 open source projects for "simulate"

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  • 1
    AI Hedge Fund

    AI Hedge Fund

    An AI Hedge Fund Team

    This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. ...
    Downloads: 11 This Week
    Last Update:
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  • 2
    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,...
    Downloads: 1 This Week
    Last Update:
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  • 3
    AutoHedge

    AutoHedge

    Build your autonomous hedge fund in minutes

    AutoHedge is an AI-driven financial automation system designed to simulate and manage hedging strategies using intelligent agents. The project focuses on applying autonomous decision-making to financial risk management, allowing agents to analyze market conditions and adjust positions dynamically. 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. ...
    Downloads: 0 This Week
    Last Update:
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  • 4
    TradingGym

    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. The list contains the feature columns to use in the trading status.
    Downloads: 2 This Week
    Last Update:
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  • 5
    Simulate business working capital cash flows by changing credit terms, customer payment behavior, credit limits and demand levels. Experience how cash flow problems can kill a business. V2 uploaded for OS X
    Downloads: 0 This Week
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  • 6
    A small program in python developed to simulate poker bankroll growth over time depending on money and risk management strategies used. No GUI, user must edit parameters in source file. Outputs to .csv format.
    Downloads: 0 This Week
    Last Update:
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