菜单
Bridgewater-style portfolio risk assessment - correlation and factor concentration, VaR / recession stress test, tail-risk scenarios, and hedges. Use when the user asks about risk, drawdown, concentration, correlation, stress test, factor exposure, or hedging.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| name | risk-assessment |
| description | Bridgewater-style portfolio risk assessment - correlation and factor concentration, VaR / recession stress test, tail-risk scenarios, and hedges. Use when the user asks about risk, drawdown, concentration, correlation, stress test, factor exposure, or hedging. |
Before forming any view, load prior decisions so verdicts stay consistent across sessions:
mcp__aifolimizer__get_cross_ticker_lessons (max_lessons=3) - portfolio-level win/loss patternsmcp__aifolimizer__get_ticker_decision_history (ticker=…, max_decisions=5) and mcp__aifolimizer__get_ticker_reflection (symbol=…, n=3). If a prior decision exists and this run flips it, state explicitly WHY (new data / catalyst / price); never silently contradict a logged decision.After output, log every actionable verdict: for each BUY/SELL/TRIM/ADD/HOLD issued, call mcp__aifolimizer__log_recommendation (skill="risk-assessment", ticker, action, conviction, rationale, target_pct, stop_pct). Skipping breaks the cross-session feedback loop and causes drift.
mcp__aifolimizer__get_profile - account contextmcp__aifolimizer__get_personal_context - province, marginal tax rate, risk tolerance, time horizon, account waterfall. Use the live risk tolerance/horizon instead of the generic buckets below, and ground §11 tax-aware rebalancing. If present=false, note the risk framing is generic and suggest profile-setupmcp__aifolimizer__get_portfolio - current holdingsmcp__aifolimizer__get_risk_metrics - vol, Sharpe, Sortino, VaR, expected shortfallmcp__aifolimizer__get_correlation_matrix - which positions move togethermcp__aifolimizer__get_concentration_warnings - over-allocation flagsmcp__aifolimizer__get_factor_exposure for the top 3-5 holdings by weight - multi-factor betas (market/size/value/profitability/investment/momentum) + annualized alpha. Surfaces hidden FACTOR concentration that name/sector diversification hides (e.g. 4 different names all loaded on momentum = one factor bet)mcp__aifolimizer__get_factor_snapshot - current factor regime. A book heavy on a factor that is rolling over is a live risk even if the names look uncorrelatedget_profile - never hardcodeget_factor_exposure); flag if 3+ names share a dominant factor betamcp__aifolimizer__get_positioning_signals on those names and gate on crowding: crowding_score >= 70 = consensus-crowded → defer the add; <= 30 = contrarian, favor when fundamentals supportget_risk_metrics cached 1h - state as-of timestamp; never claim "real-time" risk.get_correlation_matrix covers top-N holdings only; small positions excluded - do NOT claim full-portfolio correlation.get_risk_metrics - pull separately via get_crypto_data and discuss qualitatively.get_factor_exposure uses US Fama-French factors - loadings for .TO/non-US names are directional only; low R² (<0.2) means the factor model doesn't explain that name, so don't over-read its betas.Run a parallel bull/bear adversarial research pipeline on a specific ticker. Use when the user asks for "adversarial research", "bull bear analysis", "deep research on [ticker]", a bull-bear debate on X, or wants a rigorous debate-style investment thesis. (Bare "should I buy X?" belongs to pre-trade-check.) Then spawns parallel sub-agents over live data.
Monthly rebalance + DCA prompt for the long-term core ETF sleeve only (broad-market index ETFs) - NOT single-stock adds (use cash-deployment) and NOT max-Sharpe reweighting (use optimize-allocation). Use when the user asks "should I rebalance?", "where should I deploy my paycheck?", "DCA recommendation", "is my allocation drifting?", "auto-invest plan", or on the 1st of each month. Computes target vs actual core allocation, suggests DCA amount per ETF, accounts for tax-account routing.
Plan how to deploy uninvested cash across existing portfolio holdings. Use when the user asks "where do I put my cash?", "I have $X to invest", "deploy my cash", "what should I buy with my settled funds?", or "add to my best names". Routes capital to existing tickers ranked by setup quality and avoids concentration pile-on. Fetches portfolio + technicals + fundamentals via aifolimizer MCP.
Run a one-shot morning portfolio digest that ties together health, alerts, macro regime, crowding risk, concentration, and earnings calendar into a single decision-ready brief. Use when the user asks for "morning briefing", "daily digest", "what's happening today?", "what changed overnight?", or "give me the morning rundown". Composes existing MCP tools - no new data sources.
Harvard Endowment-style dividend income analysis - yield, payout-ratio safety, DRIP projection, and tax-account placement for income holdings. Use when the user asks about dividends, passive income, DRIP, yield, payout ratio, dividend safety, or "what should I hold for income?".
Run a JPMorgan-style pre-earnings analysis on a specific ticker. Use when the user asks about an upcoming earnings report, "should I hold through earnings?", "what's the expected move?", or names a stock and earnings in the same query. Fetches portfolio via aifolimizer MCP.