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Found 30 Skills
Breaks down trading ideas into component parts for systematic Pine Script implementation. Use when analyzing trading concepts, decomposing strategies, planning indicator features, or extracting ideas from YouTube videos. Triggers on conceptual questions, "how would I build", YouTube URLs, or video analysis requests.
Orchestrates Pine Script development by coordinating workflows and planning complex projects. Use when building complete trading systems, managing multi-step projects, planning indicator/strategy development, or coordinating multiple capabilities. Triggers on complex requests mentioning multiple features, "build a complete", "trading system", or project planning needs.
Analyze historical downtrend durations and generate interactive HTML histograms showing typical correction lengths by sector and market cap.
Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Use PROACTIVELY for quantitative finance, trading algorithms, or risk analysis.
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.
Analyze option volatility by combining vol surface data, option pricing with Greeks, and historical price data to assess implied vs realized volatility. Use when pricing options, analyzing volatility surfaces, computing Greeks, assessing vol premiums, or evaluating vol trading strategies.
Apply the Efficient Market Hypothesis (Fama, 1970) to evaluate information incorporation in asset prices across weak, semi-strong, and strong forms. Use this skill when the user needs to assess market efficiency, determine if a trading strategy can generate abnormal returns, evaluate event studies, or when they ask 'can technical analysis work', 'does the market already know this', or 'is this anomaly exploitable'.
Run a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation
Backtest trading strategies on historical data and interpret performance metrics. Provides run_backtest (crypto strategies) and run_prediction_market_backtest (Polymarket strategies). Fast execution (20-60s), minimal cost ($0.001). Returns Sharpe ratio, max drawdown, win rate, profit factor, and trade statistics. Use this skill after building or improving strategies to validate performance before deploying. NEVER deploy without thorough backtesting (6+ months recommended).
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
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.
Use when the task requires operating exchanges with the ritmex-bot CLI, including capability checks, market/account/position queries, order operations, strategy run, dry-run simulation, and JSON output parsing.