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Found 48 Skills
Calculate Value at Risk to estimate maximum portfolio loss at a given confidence level. Use this skill when the user needs to quantify downside risk, set risk limits, or report regulatory risk measures — even if they say 'worst case loss', 'portfolio risk', or 'how much could we lose'.
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.
Comprehensive trading skills system with multi-broker support, strategy execution, and autonomous trading capabilities
Build and deploy agentic finance applications on the Alva platform. Access 250+ financial data sources (crypto, equities, macro, on-chain, social), run cloud-side analytics, backtest trading strategies, and release interactive playbooks -- all from your AI agents.
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
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。
Portfolio management. Display of held securities, trade records, structural analysis. Input data foundation for stress testing.
Master Moon Dev's Ai Agents Github with 48+ specialized agents, multi-exchange support, LLM abstraction, and autonomous trading capabilities across crypto markets
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.
Perform quantitative analysis of returns, correlations, risk factors, and portfolio optimization. Statistical modeling with institutional-grade rigor.
Use to perform market backtests with PlausibleAI Backtester, including symbol discovery, strategy validation, strategy mining, and batch execution.
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.