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Found 127 Skills
Portfolio rebalancing via Longbridge — analyse weight drift (current vs target), generate a rebalance trade list, factor in transaction costs and tax impact, and output buy/sell recommendations with rationale. Triggers: "再平衡", "组合再平衡", "仓位调整", "目标权重", "权重偏移", "配置调整", "再平衡交易", "再平衡", "組合再平衡", "倉位調整", "目標權重", "權重偏移", "配置調整", "rebalancing", "portfolio rebalance", "target weight", "weight drift", "allocation adjustment", "rebalance trades", "drift threshold".
Institutional research and analyst ratings — buy/hold/sell distribution, consensus price target, EPS/revenue forecasts, and rating change history. ESG and credit ratings are not available via Longbridge. Triggers: "研报评级", "机构评级", "买入评级", "目标价", "机构观点", "分析师推荐", "券商评级", "机构研究", "研報評級", "機構評級", "買入評級", "目標價", "機構觀點", "分析師推薦", "券商評級", "analyst rating", "institution rating", "buy rating", "price target", "broker recommendation", "analyst opinion", "research rating", "sell-side rating", "consensus target", "EPS forecast", "analyst consensus".
Portfolio diagnosis via Longbridge — concentration risk (top-5 weight), sector/industry distribution, currency exposure, factor exposure (large/small-cap, value/growth), pairwise correlation risk across holdings, and deviation from benchmark. Triggers: "组合诊断", "持仓集中度", "组合分析", "因子暴露", "行业分布", "货币敞口", "相关性风险", "组合检查", "組合診斷", "持倉集中度", "組合分析", "因子暴露", "行業分布", "貨幣敞口", "相關性風險", "portfolio diagnosis", "concentration risk", "factor exposure", "sector distribution", "currency exposure", "correlation risk", "portfolio review", "holdings analysis".
ARK-style single-stock disruptive-innovation diagnostic. Suitability gate on 4 dimensions (platform fit / innovation revenue / R&D intensity / management vision); if it passes, builds TAM (low/base/high), Wright's-Law cost curve with sourced learning rate, three-scenario 5-year target (Bull/Base/Bear, 15% discount), risks, conditional action frame. Data: Longbridge CLI first, MCP fallback, WebSearch only for TAM / learning rates / industry runway. Runs cross-statement reconciliation BEFORE analysis. Closes with a data-source appendix whose final row is the reconciliation summary. Independent implementation — not affiliated with ARK Invest. Triggers: "木头姐", "ARK", "ARKK", "颠覆式创新", "莱特定律", "TAM", "5年目标价", "情景分析", "AI 与大数据", "自动化与机器人", "能源存储", "基因革命", "区块链与金融科技", "木頭姐", "顛覆式創新", "萊特定律", "5年目標價", "Cathie Wood", "ARK Invest", "disruptive innovation", "Wright's Law", "learning rate", "bull base bear", "scenario analysis".
Quantitative signal scanning and position sizing tool based on the original Turtle Trading method. It retrieves market data for A-shares / Hong Kong stocks / US stocks / Singapore stocks via longbridge CLI, and automatically calculates ATR (N value), breakout signals (System 1 / System 2), stop-loss prices, add-on positions, and Unit position sizes. Trigger this tool when users mention 海龟, turtle, 海龟交易, 海龟信号, turtle signal, turtle trading, or ask about breakout signals, ATR, N value, Unit positions, stop-loss prices, add-on positions, S1/S2 signals, 20-day high/low, 55-day breakout, or request to scan watchlists/indexes for trading signals using the turtle system. It also triggers when users say "扫描突破信号", "帮我算Unit", "海龟止损", "海龟系统分析", or any combination of a stock name/code with "海龟". **Applicable scenarios:** - Scan for breakout signals (20-day/55-day high/low breakouts) after daily market close - Calculate ATR, stop-loss prices, and add-on positions for single stocks or batches of targets - Calculate reasonable Unit position sizes based on account net assets - Determine whether existing positions trigger exit or add-on conditions - Scan turtle signals for watchlist stocks / index components **Not applicable for:** - Fundamental analysis (Turtle system is purely technical) - Predicting price direction - Automatic order placement (only outputs signals; users operate on their own) - Short-selling opening operations for A-shares/Hong Kong stocks/Singapore stocks
Orderbook depth (5/10-level bid/ask), broker queue (HK only), and tick-by-tick trades for stocks via Longbridge Securities. Use for orderbook microstructure questions. Triggers: "盘口", "买卖盘", "5 档", "10 档", "深度", "经纪商队列", "逐笔", "tick", "成交明细", "盤口", "買賣盤", "5 檔", "10 檔", "經紀商隊列", "逐筆", "成交明細", "depth", "orderbook", "level 2", "broker queue", "tick data", "trades", "time and sales".
A/H premium ratio for Mainland-Chinese companies dual-listed in Hong Kong and A-shares (e.g. 939.HK / 601398.SH, 1810.HK / 600519.SH-pair) via Longbridge Securities — historical premium time series (kline) or today's intraday premium curve. Only HK-side symbols of dual-listed pairs return data. Triggers: "AH 溢价", "A H 溢价率", "AH 折价", "AH 价差", "工行 AH", "建行 AH", "比价", "A 股贵还是港股贵", "AH premium", "A/H premium", "AH ratio", "AH 溢價", "A H 溢價率", "AH 折價", "AH 價差", "比價", "A 股貴還是港股貴", "dual listed premium", "Hong Kong A-share premium", "premium ratio", "939.HK", "1398.HK", "600519.SH 对应港股".
gpui-component library patterns for building reusable UI components. Use when creating buttons, inputs, dialogs, forms, or following Longbridge component library conventions in GPUI applications.
Quantitative statistics framework for time-series analysis using Longbridge price data — ADF unit root test (stationarity), cointegration (Engle-Granger / Johansen), GARCH volatility modelling (conditional heteroskedasticity), regression diagnostics (Durbin-Watson / Breusch-Pagan), bootstrap confidence intervals, hypothesis tests (t-test / F-test). Requires statsmodels and scipy. Triggers: "量化统计", "ADF检验", "单位根", "协整检验", "GARCH", "自相关", "异方差", "Bootstrap", "假设检验", "量化統計", "ADF檢驗", "單位根", "協整檢驗", "異方差", "假設檢驗", "quantitative statistics", "ADF test", "unit root", "cointegration", "GARCH", "autocorrelation", "heteroskedasticity", "bootstrap", "hypothesis test", "statsmodels".
Quantitative strategy generation and optimisation framework via Longbridge — create, modify, and backtest quant strategies: parameter grid search, walk-forward validation, overfitting detection (in-sample vs. out-of-sample), strategy combination (multi-strategy correlation diversification), Sharpe / Calmar ratio optimisation. Generates Python code frameworks for local execution. Triggers: "策略优化", "策略生成", "参数优化", "网格搜索", "回测优化", "过拟合", "walk-forward", "策略回测优化", "策略組合", "策略優化", "策略生成", "參數優化", "網格搜索", "回測優化", "strategy optimization", "strategy generation", "parameter optimization", "grid search", "overfitting", "walk-forward validation", "strategy backtest", "Sharpe ratio", "Calmar ratio".
Trade execution modelling framework (backtesting analysis only) via Longbridge — covers slippage models (linear / square-root market impact), VWAP/TWAP execution logic, market impact cost estimation (Kyle lambda), volume participation rate (POV) strategy. Helps quant traders build realistic execution assumptions in backtests. Triggers: "执行模型", "滑点模型", "VWAP执行", "TWAP执行", "市场冲击", "执行成本", "成交量参与率", "交易执行", "執行模型", "滑點模型", "VWAP執行", "TWAP執行", "市場冲擊", "執行成本", "交易執行", "execution model", "slippage model", "VWAP", "TWAP", "market impact", "execution cost", "volume participation rate", "Kyle lambda", "square root model", "POV strategy".
Machine-learning prediction strategy framework via Longbridge Securities — walk-forward rolling training with feature engineering (MACD, RSI, Bollinger Band width, volume change rate) and a scikit-learn classifier (Random Forest / Gradient Boosting); retrains every 60 days, predicts 5-day direction; buy signal when probability > 0.6, sell when < 0.4; evaluates win rate, profit factor, and Sharpe ratio. Triggers: "机器学习", "ML策略", "预测模型", "随机森林", "梯度提升", "深度学习", "AI选股", "walk-forward", "機器學習", "ML策略", "預測模型", "隨機森林", "梯度提升", "machine learning", "ML strategy", "predictive model", "random forest", "gradient boosting", "AI stock selection", "walk-forward", "rolling training", "feature engineering", "scikit-learn", "XGBoost".