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benutzerdefinierte Handelsstrategien

  • An AI agent that autonomously analyzes cryptocurrency markets, on-chain data, and trading indicators to provide actionable insights.
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    What is Crypto Analyst Agent?
    Crypto Analyst Agent leverages large language models and on-chain data APIs to monitor cryptocurrency markets in real time. It fetches price feeds, block data, liquidity metrics, and social sentiment indicators, then applies technical analysis such as moving averages, RSI, and MACD. The agent produces concise reports, charts, and trade signal suggestions, helping users stay ahead of market movements and optimize portfolio performance automatically.
    Crypto Analyst Agent Core Features
    • Real-time cryptocurrency price fetching
    • On-chain metrics analysis
    • Technical indicator calculations (RSI, MACD, MA)
    • Automated market analysis report generation
    • Trade signal suggestion engine
    • Custom prompt-driven data queries
  • Quadency offers advanced crypto trading bots and tools for automated and manual trades.
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    What is Quadency?
    Quadency is a comprehensive cryptocurrency trading platform that supports both automated and manual trading. It aggregates various trading platforms and wallets into a single interface, providing users with advanced tools to manage their digital assets effectively. From creating custom trading strategies and backtesting them to executing live trades, Quadency empowers traders to maximize their trading efficiency. The platform also offers portfolio analytics, market research, and news updates to keep traders informed and ahead of the curve.
  • Open-source Python framework using multiple AI agents to automate stock data acquisition, signal generation, backtesting, and live trading execution.
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    What is Stock Market Multi-Agent?
    Stock Market Multi-Agent is an advanced open-source Python framework designed to streamline automated trading through coordinated AI agents. Each agent specializes in a specific function: Data Acquisition agents fetch and clean real-time market feeds, Signal Generation agents apply machine learning models for predictive insights, Backtesting agents rigorously evaluate strategies on historical datasets, Portfolio Management agents optimize asset allocation, Execution agents interface with brokerage APIs to place orders, and Risk Management agents enforce safeguards. The config-driven architecture allows plug-and-play modules, supporting customization of algorithms, data sources, and risk parameters. Suitable for research, live trading, and development, it accelerates quantitative strategy deployment and operational scalability.
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