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Found 67 Skills
NautilusTrader algorithmic trading platform reference. NautilusTrader 量化交易框架参考。 Use this skill when: - Working with NautilusTrader API (使用 NautilusTrader API) - Implementing trading strategies (实现交易策略) - Running backtests (运行回测) - Configuring data feeds and adapters (配置数据源和适配器) - Debugging NautilusTrader code (调试 NautilusTrader 代码) - Understanding trading concepts like positions, orders, and fills (理解持仓、订单、成交等概念) Keywords: NautilusTrader, strategy, backtest, trading, adapter, Binance, quantitative, 量化, 策略, 回测
Comprehensive trading skills system with multi-broker support, strategy execution, and autonomous trading capabilities
Backtest crypto trading strategies from natural language ideas. Use when: user describes trading ideas, wants to validate strategies, mentions "backtest", "trading strategy", "buy low sell high", "RSI", "MACD", "oversold", "overbought", "crypto strategy", "validate strategy", "backtest", "DCA", or similar.
Crypto 单因子量化研究服务 Skill。当用户说"写一个因子"、"研究因子"、"量化打工"、 "提交因子"、"因子回测"时加载此 Skill。 Agent 负责编写因子插件代码并通过 HTTP 接口与服务器交互， 服务器负责所有数据处理和计算，Agent 本地无需任何市场数据。
Use this skill whenever the user wants to paper trade, simulate trades, virtual trading, demo mode, practice trading, backtest strategies, test strategy performance, use paper money, manage a virtual portfolio, track simulated P&L, or do risk-free trading on Polymarket prediction markets. Also use when the user asks about their portfolio, positions, trade history, or performance report for paper trading. This is the core trading engine — it executes simulated trades against real live Polymarket prices with zero financial risk.
Run a heavy neural-trader job (long walk-forward, big Monte-Carlo, parameter sweep, model training) on the Anthropic Managed Agent cloud runtime instead of locally
RQAlpha 米筐开源事件驱动回测框架。支持A股和期货，模块化架构，可自由扩展；当用户需要使用 rqalpha 进行策略回测、模拟交易或Mod插件开发时使用。
Measure the valuation range (overvalued/undervalued) of the mining stock sector relative to the metal itself using the ratio of Silver Mining Stock Price to Silver Price, and derive 'bottom/top' signals and scenario projections through historical percentiles and analogous intervals.
Master Moon Dev's Ai Agents Github with 48+ specialized agents, multi-exchange support, LLM abstraction, and autonomous trading capabilities across crypto markets
Perform quantitative analysis of returns, correlations, risk factors, and portfolio optimization. Statistical modeling with institutional-grade rigor.
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation
Trade mean reversion setups in the style of Scarface Trades, the mean reversion specialist known for mathematical precision and statistical edge. Emphasizes standard deviation bands, RSI extremes, and calculated entries with defined risk. Use when trading overextended moves, fading extremes, or building systematic reversion strategies.