Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Data Analysis
Investment Analysis & Portfolio Management Engine
Performs structured investment thesis development, fundamental and technical analysis, portfolio risk management, and trade execution across asset classes.
skill openclawclawhub Free
Performs structured investment thesis development, fundamental and technical analysis, portfolio risk management, and trade execution across asset classes.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
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- Download the package from Yavira.
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- Paste one of the prompts below and point your agent at the extracted folder.
New install
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- 1kalin
- Source page
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Documentation
Investment Analysis & Portfolio Management Engine
Complete investment analysis, portfolio construction, risk management, and trade execution methodology. Works across stocks, crypto, ETFs, bonds, and alternatives. Zero dependencies โ pure agent skill.
Quick Health Check (/8)
Before any investment activity, score your current state: Signalโ Healthyโ Fix FirstInvestment thesis documentedWritten with edge + invalidation"I think it'll go up"Position sizing calculatedKelly/fixed-fractional with max cap"I'll put in $5K"Stop-loss definedPrice or thesis invalidation triggerNo exit planPortfolio heat trackedTotal exposure known, <15%Unknown aggregate riskAsset correlation checkedNo >40% correlated concentrationAll tech / all cryptoRebalance schedule setMonthly or threshold-basedNever rebalancedTax impact consideredHarvesting losses, holding periodsTax-blind tradingPerformance trackedBenchmarked vs buy-and-hold"I think I'm up" Score /8. Below 5 = fix fundamentals before any new positions.
Phase 1: Investment Thesis Development
Every position starts with a thesis. No thesis = no trade.
Thesis Brief Template
thesis: ticker: "AAPL" asset_class: "equity" # equity | crypto | etf | bond | commodity | real_estate date: "2026-02-22" # THE EDGE โ why does this opportunity exist? edge: type: "mispricing" # mispricing | catalyst | trend | mean_reversion | structural description: "Market pricing in worst-case regulation; actual impact is 5-10% revenue, not 30%" why_others_miss_it: "Headline risk scaring generalists; specialists still buying" # THESIS STATEMENT (one sentence) thesis_statement: "AAPL is undervalued by 20% due to regulatory FUD; earnings growth will re-rate within 2 quarters" # TIMEFRAME timeframe: horizon: "3-6 months" catalyst_date: "2026-04-15" # earnings, FDA, macro event catalyst_type: "earnings_beat" # BULL / BASE / BEAR scenarios: bull: probability: 30 target_price: 245 thesis: "Regulation light + Services acceleration" base: probability: 50 target_price: 215 thesis: "Regulation moderate, priced in by Q3" bear: probability: 20 target_price: 165 thesis: "Full regulatory impact + macro downturn" # EXPECTED VALUE # EV = (P_bull ร R_bull) + (P_base ร R_base) + (P_bear ร R_bear) current_price: 190 expected_value: 213.5 # (0.3ร245 + 0.5ร215 + 0.2ร165) ev_vs_current: "+12.4%" # INVALIDATION โ when you're WRONG invalidation: price_stop: 175 # -7.9% from entry thesis_stop: "Revenue decline >10% YoY in any segment" time_stop: "No catalyst by 2026-07-01" # CONVICTION (1-5) conviction: 4 conviction_factors: - "3 independent data sources confirm undervaluation" - "Insider buying last 90 days" - "Valuation below 5Y average on EV/EBITDA"
Edge Type Framework
Edge TypeDescriptionValidation MethodDecay RateMispricingMarket wrong on fundamentalsComp analysis + modelSlow (months)CatalystKnown upcoming eventCalendar + probabilityFast (event-driven)TrendMomentum / technicalPrice action + volumeMedium (weeks)Mean ReversionExtreme deviation from normZ-score + historyMediumStructuralMarket structure creates opportunityFlow analysisSlow
Thesis Quality Checklist
Edge clearly articulated (not just "it's cheap") Bull/base/bear with probabilities summing to 100% Expected value positive vs current price At least 2 independent data sources Invalidation criteria defined (price + thesis + time) Timeframe realistic for the edge type Not just consensus view repackaged Considered "what if I'm wrong?"
Equity Analysis Framework
Valuation Metrics (collect all, weight by sector) valuation: # Price Multiples pe_ratio: null # Price / Earnings (TTM) forward_pe: null # Price / Forward Earnings peg_ratio: null # PE / Earnings Growth Rate ps_ratio: null # Price / Sales pb_ratio: null # Price / Book ev_ebitda: null # Enterprise Value / EBITDA ev_revenue: null # Enterprise Value / Revenue fcf_yield: null # Free Cash Flow / Market Cap # Compare to: sector_median: null historical_5y_avg: null historical_range: [null, null] # [low, high] # Verdict valuation_score: null # 1-10 (1=very expensive, 10=very cheap) relative_to_sector: null # premium | inline | discount Financial Health Scorecard DimensionMetricHealthyWarningDangerProfitabilityGross Margin>50%30-50%<30%ProfitabilityNet Margin>15%5-15%<5%ProfitabilityROE>15%8-15%<8%ProfitabilityROIC>12%6-12%<6%GrowthRevenue YoY>15%5-15%<5%GrowthEPS YoY>10%0-10%DecliningGrowthFCF Growth>10%0-10%DecliningLeverageDebt/Equity<0.50.5-1.5>1.5LeverageInterest Coverage>8x3-8x<3xLeverageNet Debt/EBITDA<2x2-4x>4xLiquidityCurrent Ratio>1.51-1.5<1LiquidityQuick Ratio>1.00.5-1<0.5EfficiencyAsset Turnover>0.80.4-0.8<0.4EfficiencyInventory Days<6060-120>120QualityFCF/Net Income>80%50-80%<50%QualityAccruals Ratio<5%5-10%>10% Score each dimension 1-3. Total /48. Above 36 = strong. Below 24 = avoid. Moat Assessment (0-25 points) Moat SourceScore 0-5Evidence RequiredNetwork EffectsUsers increase value for other usersSwitching CostsPainful to leave (data lock-in, integrations)Cost AdvantagesStructural cost below competitorsIntangible AssetsBrand, patents, regulatory licensesEfficient ScaleMarket only supports limited competitors Score /25. Above 15 = wide moat. 8-15 = narrow. Below 8 = no moat.
Crypto Analysis Framework
crypto_analysis: # Network Fundamentals network: daily_active_addresses: null transaction_volume_24h: null hash_rate_trend: null # BTC/PoW staking_ratio: null # PoS chains developer_activity: null # GitHub commits 90d tvl: null # DeFi protocols tvl_trend_30d: null # Tokenomics tokenomics: supply_schedule: null # inflationary | deflationary | fixed circulating_vs_total: null # % circulating unlock_schedule: null # upcoming unlocks concentration: null # top 10 holders % # On-Chain Signals on_chain: exchange_reserves_trend: null # decreasing = bullish whale_accumulation: null # large wallet changes realized_profit_loss: null # NUPL mvrv_ratio: null # Market Value / Realized Value # Market Structure market: funding_rate: null # perpetuals funding open_interest_trend: null spot_vs_derivatives_volume: null correlation_to_btc: null correlation_to_sp500: null
Crypto Valuation Methods
MethodBest ForFormulaStock-to-FlowBTCPrice = 0.4 ร S2F^3 (check vs actual)NVT RatioL1 chainsNetwork Value / Daily Transaction ValueTVL RatioDeFiMarket Cap / TVL (below 1 = undervalued)Fee Revenue MultipleRevenue-generatingMC / Annualized FeesMetcalfe's LawNetwork tokensValue โ nยฒ (active addresses)
Price Action Framework
technical_analysis: ticker: "BTC-USD" timeframe: "daily" date: "2026-02-22" # TREND trend: primary: "uptrend" # uptrend | downtrend | range higher_highs: true higher_lows: true above_200ma: true above_50ma: true ma_alignment: "bullish" # 20 > 50 > 200 = bullish # KEY LEVELS levels: resistance: [105000, 110000, 120000] support: [95000, 88000, 80000] current_price: 98500 distance_to_resistance: "+6.6%" distance_to_support: "-3.6%" # MOMENTUM momentum: rsi_14: 58 # <30 oversold, >70 overbought rsi_divergence: null # bullish_div | bearish_div | none macd_signal: "bullish" # bullish | bearish | neutral macd_histogram_trend: "increasing" # VOLUME volume: vs_20d_avg: "+15%" trend: "increasing_on_up_days" # confirms trend # PATTERN pattern: current: "ascending_triangle" reliability: "high" target: 112000 invalidation: 93000
Signal Scoring Matrix
FactorBullish (+)Neutral (0)Bearish (-)Trend (weight 3x)Above 200MA, higher highsRangingBelow 200MA, lower lowsMomentum (weight 2x)RSI 40-60 rising, MACD bull crossRSI 45-55 flatRSI >75 or bearish divVolume (weight 2x)Rising on up movesAverageRising on down movesSupport/Resistance (weight 1x)Near strong supportMid-rangeNear strong resistancePattern (weight 1x)Bullish continuationNo patternBearish reversal Score -9 to +9. Above +5 = strong buy signal. Below -5 = strong sell signal.
Position Sizing Rules (MANDATORY)
risk_rules: # Per-Trade Risk max_risk_per_trade: 2% # of total equity max_risk_aggressive: 3% # only with 5/5 conviction # Portfolio Heat max_portfolio_heat: 15% # total risk across all positions max_correlated_exposure: 25% # in correlated assets max_single_position: 10% # of total equity # Position Size Formula # Position Size = (Account ร Risk%) / (Entry - Stop Loss) # Example: ($100K ร 2%) / ($190 - $175) = $2,000 / $15 = 133 shares # Kelly Criterion (optional, aggressive) # f* = (bp - q) / b # b = win/loss ratio, p = win probability, q = 1-p # ALWAYS use Half-Kelly or Quarter-Kelly (full Kelly = too aggressive)
Position Size Calculator
Account Equity: $___________ Risk Per Trade: ___% (max 2%) Dollar Risk: $___________ (equity ร risk%) Entry Price: $___________ Stop Loss Price: $___________ Risk Per Share: $___________ (entry - stop) Position Size: ___________ shares (dollar risk / risk per share) Position Value: $___________ (shares ร entry) Portfolio Weight: ___% (position value / equity) CHECK: Portfolio weight < 10%? โ Yes โ No (reduce if no) CHECK: Portfolio heat < 15%? โ Yes โ No (reduce if no) CHECK: Correlated exposure ok? โ Yes โ No (reduce if no)
Stop-Loss Decision Tree
Is this a TREND trade? โโโ YES โ Trailing stop below swing low (ATR-based: 2ร ATR) โ Initial stop: Below last higher low โ Trail: Move stop to below each new higher low โ โโโ NO โ Is this a CATALYST trade? โโโ YES โ Time-based + price stop โ Price: Below pre-catalyst support โ Time: Close if no move within 2 days post-catalyst โ โโโ Is this a VALUE trade? โโโ YES โ Thesis invalidation stop โ Price: Below bear case scenario price โ Thesis: Close if fundamental thesis breaks โ Time: Close if no re-rating in stated timeframe โ โโโ MEAN REVERSION โ Tight stop Price: If moves further from mean (wider Z-score) Target: Mean / fair value level
Risk Management Hard Rules
Never average down without a plan โ Adding to losers kills accounts. Only add if: thesis intact AND price at predetermined add level AND total position still within limits Cut losses fast, let winners run โ Asymmetric payoff is the goal. 1:3 risk/reward minimum No revenge trading โ After a loss, wait 24 hours before next trade Daily loss limit โ Stop trading for the day after -3% account drawdown Weekly loss limit โ Reduce position sizes by 50% after -5% weekly drawdown Monthly loss limit โ Go to cash if -10% monthly drawdown. Review all positions. Correlation check โ Before every new position, check correlation to existing holdings Black swan rule โ If any asset moves >15% in 24h, review ALL positions immediately
Asset Allocation Framework
portfolio: name: "Growth + Income" target_allocation: # Core (60-70% โ low turnover) core: us_large_cap: 25% # S&P 500 / quality growth international: 10% # Developed markets fixed_income: 15% # Bonds / treasuries bitcoin: 10% # Digital gold thesis real_estate: 5% # REITs # Satellite (20-30% โ active management) satellite: growth_stocks: 15% # Individual stock picks crypto_alts: 5% # L1s, DeFi thematic: 5% # AI, clean energy, etc. # Cash (5-15%) cash: 10% # Dry powder for opportunities # Rebalance Rules rebalance: method: "threshold" # calendar | threshold | hybrid threshold: 5% # Rebalance when drift >5% from target calendar_check: "monthly" # Review allocations monthly tax_aware: true # Use new contributions to rebalance first
Portfolio Models by Risk Profile
ProfileStocksBondsCryptoAltsCashExpected ReturnMax DrawdownConservative30%40%5%10%15%6-8%-15%Balanced50%20%10%10%10%8-12%-25%Growth60%10%15%10%5%12-18%-35%Aggressive50%0%30%15%5%15-25%-50%Degen20%0%50%25%5%20-40%+-70%+
Correlation Matrix Template
Track correlations between holdings. Target: no two positions with >0.7 correlation exceeding 20% combined weight. SPY BTC ETH AAPL MSFT GLD TLT SPY 1.00 BTC 0.35 1.00 ETH 0.30 0.85 1.00 AAPL 0.82 0.25 0.20 1.00 MSFT 0.85 0.28 0.22 0.78 1.00 GLD -0.10 -0.05 -0.08 -0.12 -0.10 1.00 TLT -0.35 -0.15 -0.12 -0.30 -0.32 0.40 1.00
Trade Journal Template
trade: id: "T-2026-042" date_opened: "2026-02-22" date_closed: null # WHAT ticker: "BTC-USD" direction: "long" asset_class: "crypto" # SIZING entry_price: 98500 position_size: 0.15 # BTC position_value: 14775 portfolio_weight: "8.2%" # RISK stop_loss: 93000 risk_amount: 825 # (98500-93000) ร 0.15 risk_percent: "0.82%" # of portfolio # TARGETS target_1: 105000 # 50% of position target_2: 115000 # 30% of position target_3: 130000 # 20% of position (runner) risk_reward: "1:3.8" # avg target vs risk # THESIS thesis: "BTC consolidating above 200MA, halving supply reduction, ETF inflows accelerating" edge_type: "trend + structural" conviction: 4 # EXECUTION entry_type: "limit" # market | limit | scaled scale_plan: null # or: [{"price": 97000, "size": "50%"}, {"price": 95000, "size": "50%"}] # RESULT (fill on close) exit_price: null exit_reason: null # target_hit | stop_hit | thesis_invalidated | time_stop | manual pnl_dollar: null pnl_percent: null r_multiple: null # PnL / initial risk # REVIEW followed_plan: null # yes | partially | no lessons: null mistakes: null grade: null # A-F
Execution Checklist (Before EVERY Trade)
Thesis documented with edge, invalidation, timeframe Position size calculated (โค2% risk, โค10% portfolio weight) Stop-loss set (price + thesis + time) At least 2 take-profit targets defined Risk/reward โฅ1:2 (preferably 1:3+) Portfolio heat check (total risk <15%) Correlation check (not adding to concentrated exposure) No emotional driver (revenge, FOMO, boredom) Checked economic calendar (no surprise events imminent) Entry type decided (market/limit/scaled)
Order Types Decision
SituationOrder TypeWhyStrong conviction, want in nowMarketSpeed over priceGood setup, not urgentLimit at supportBetter entryHigh-conviction, want scale inScaled limits (3 levels)Average entry, reduce timing riskBreakout tradeStop-limit above resistanceOnly enter if breakout confirmsCatalyst tradeLimit pre-catalystPosition before event
Daily Dashboard
daily_dashboard: date: "2026-02-22" # PORTFOLIO SNAPSHOT portfolio: total_equity: null daily_pnl: null daily_pnl_percent: null weekly_pnl: null monthly_pnl: null ytd_pnl: null # POSITIONS open_positions: 0 portfolio_heat: "0%" # sum of all position risks cash_percent: "100%" # BENCHMARK benchmark: sp500_ytd: null btc_ytd: null portfolio_vs_sp500: null portfolio_vs_btc: null # ACTIVITY trades_today: 0 alerts_triggered: []
Performance Metrics (Track Weekly)
MetricFormulaTargetWin RateWinning trades / Total trades>50%Average RAverage R-multiple of all trades>1.5RProfit FactorGross profit / Gross loss>2.0Expectancy(Win% ร Avg Win) - (Loss% ร Avg Loss)PositiveMax DrawdownPeak to trough decline<-15%Sharpe Ratio(Return - RFR) / Std Dev>1.5Sortino Ratio(Return - RFR) / Downside Dev>2.0Calmar RatioAnnual Return / Max Drawdown>1.0Recovery FactorNet Profit / Max Drawdown>3.0
Monthly Review Template
monthly_review: month: "2026-02" # PERFORMANCE portfolio_return: null benchmark_return: null # vs S&P 500 alpha: null # portfolio - benchmark # TRADING STATS total_trades: 0 winning_trades: 0 losing_trades: 0 win_rate: null average_winner: null average_loser: null largest_winner: null largest_loser: null profit_factor: null # RISK STATS max_drawdown: null avg_portfolio_heat: null risk_rule_violations: 0 # BEHAVIOR ANALYSIS followed_plan_rate: null # % of trades that followed the plan emotional_trades: 0 # trades driven by FOMO/revenge/boredom early_exits: 0 # cut winners short late_exits: 0 # held losers too long # TOP 3 LESSONS lessons: - null - null - null # ADJUSTMENTS FOR NEXT MONTH adjustments: - null
Regime Framework
RegimeCharacteristicsStrategyPosition SizeBull TrendRising 200MA, breadth >60%, VIX <20Trend following, buy dipsFull sizeBear TrendFalling 200MA, breadth <40%, VIX >30Short / inverse, raise cashHalf sizeRange/ChopFlat 200MA, breadth 40-60%Mean reversion, sell premiumQuarter sizeHigh VolVIX >35, large daily swingsReduce exposure, hedgeMinimum sizeEuphoriaVIX <12, extreme bullish sentimentTake profits, hedgeScale downPanicVIX >50, capitulation signalsAccumulate qualityScale in slowly
Macro Checklist (Weekly)
Fed funds rate / next meeting: ___ US 10Y yield trend: ___ Dollar (DXY) trend: ___ VIX level: ___ Credit spreads: ___ (tightening/widening) Yield curve: ___ (inverted/flat/steep) Leading indicators: ___ (improving/declining) Global liquidity trend: ___ (expanding/contracting) Sector rotation: ___ (risk-on/risk-off) Crypto market cap trend: ___
Sentiment Indicators
IndicatorExtreme Fear (Buy)NeutralExtreme Greed (Sell)CNN Fear & Greed<2040-60>80AAII Bull-Bear>-30% spreadยฑ10%>+30% spreadPut/Call Ratio>1.20.7-0.9<0.5VIX Term StructureBackwardationFlatSteep contangoCrypto Fear & Greed<1540-60>85BTC Funding RatesDeeply negativeNeutral>0.05%
Dividend Quality Score (0-100)
FactorWeightScoringYield vs Sector15At/above median = 15, below = proportionalPayout Ratio20<50% = 20, 50-75% = 15, 75-100% = 5, >100% = 0Growth Rate (5Y CAGR)20>10% = 20, 5-10% = 15, 0-5% = 10, declining = 0Consecutive Years15>25y = 15 (Aristocrat), 10-25 = 10, 5-10 = 5, <5 = 0FCF Coverage15FCF/Div >1.5 = 15, 1-1.5 = 10, <1 = 0Debt/EBITDA15<2 = 15, 2-4 = 10, >4 = 5 Score /100. Above 75 = excellent income pick. Below 40 = dividend at risk.
Income Portfolio Construction
Core income (60%): Dividend Aristocrats, quality REITs, investment-grade bonds Growth income (25%): Dividend growers (low yield, high growth rate) High yield (15%): Higher risk, higher yield (junk bonds, BDCs, covered calls) Yield target: 4-6% blended, growing 5-8% annually
Tax-Loss Harvesting Rules
When: Position down >10% from cost basis AND held <12 months How: Sell the position, immediately buy a correlated (not substantially identical) replacement Wash sale rule: Cannot buy back the same security within 30 days (before or after) Replacement examples: SPYโVOO, AAPLโQQQ, BTC spotโBTC futures ETF Track: Cumulative harvested losses, offset against gains + $3K income deduction
Holding Period Optimization
Holding PeriodTax Rate (US)Strategy<1 yearOrdinary income (up to 37%)Only for high-conviction short-term trades>1 yearLong-term CG (0/15/20%)Default for all positions when possible>5 years (QOZ)Reduced + deferredQualified Opportunity Zone investments
Tax-Efficient Account Allocation
Account TypeBest ForWhyTaxableLong-term holds, tax-loss harvestingCapital gains treatmentTraditional IRA/401kBonds, REITs, high-dividendDefer high-tax incomeRoth IRAHighest growth potentialTax-free growthHSAAggressive growthTriple tax advantage
Stock Screener Criteria Templates
Value Screen: P/E < sector median P/B < 1.5 Debt/Equity < 0.5 ROE > 12% FCF positive 5 consecutive years Insider buying last 90 days Growth Screen: Revenue growth > 20% YoY EPS growth > 15% YoY Gross margin > 50% Net retention > 110% (SaaS) TAM > $10B Dividend Screen: Dividend yield > 3% Payout ratio < 60% Dividend growth > 5% CAGR (5Y) Consecutive increases > 10 years Debt/EBITDA < 3 Crypto Screen: Market cap > $1B (avoid micro-caps) Daily volume > $50M Active development (GitHub commits) Not >90% held by top 10 wallets Clear revenue model or adoption metrics
Research Sources (No API Required)
SourceURLBest ForYahoo Financefinance.yahoo.comFundamentals, quotesFinvizfinviz.comScreening, heatmapsMacrotrendsmacrotrends.netHistorical financialsCoinGeckocoingecko.comCrypto dataDeFiLlamadefillama.comDeFi TVL, yieldsFREDfred.stlouisfed.orgMacro dataTradingViewtradingview.comCharts, technicalsSEC EDGARsec.gov/edgarFilings, insider tradesGlassnodeglassnode.comOn-chain dataFear & Greedalternative.meCrypto sentiment
Options Basics (for hedging)
StrategyWhenRiskRewardProtective PutOwn stock, want downside protectionPremium paidUnlimited upside, limited downsideCovered CallOwn stock, willing to cap upsideCapped gainsPremium incomeCash-Secured PutWant to buy at lower priceMust buy at strikePremium + lower entryCollarWant protection, willing to cap upsideCapped both waysLow/no cost protection
DCA (Dollar Cost Averaging) Framework
dca_plan: asset: "BTC" frequency: "weekly" # daily | weekly | biweekly | monthly amount: 250 # per purchase day: "Monday" # specific day duration: "indefinite" # or end date # SMART DCA (optional โ buy more when cheap) smart_dca: enabled: true base_amount: 250 multiplier_rules: - condition: "price < 200MA" multiplier: 1.5 # buy 50% more - condition: "RSI < 30" multiplier: 2.0 # double buy - condition: "price > 200MA ร 1.5" multiplier: 0.5 # buy less in euphoria
Rebalancing Decision Tree
Is any allocation >5% from target? โโโ NO โ No action needed. Check again next month. โ โโโ YES โ Is it a tax-advantaged account? โโโ YES โ Rebalance by selling overweight, buying underweight โ โโโ NO (taxable) โ Can you rebalance with new contributions? โโโ YES โ Direct new money to underweight positions โ โโโ NO โ Are there tax losses to harvest? โโโ YES โ Sell losers (harvest), redirect to underweight โ โโโ NO โ Is the drift >10%? โโโ YES โ Rebalance (accept tax hit for risk control) โโโ NO โ Wait for next contribution or year-end
10 Cognitive Biases That Kill Returns
BiasTrapDefenseLoss AversionHolding losers, cutting winnersPre-set stops, mechanical exitsConfirmation BiasOnly seeing data that supports thesisActively seek disconfirming evidenceRecency BiasExtrapolating recent performanceLook at full cycle data (10+ years)AnchoringFixating on purchase priceFocus on current value vs alternativesFOMOChasing after 50%+ moveStick to your screener, your edgeOverconfidenceToo large positions after winsFixed position sizing rulesDisposition EffectSelling winners too earlyTrailing stops, let runners runHerdingBuying because everyone isContrarian checkpointsSunk Cost"I've held this long, can't sell now"Would you buy this TODAY at this price?Hindsight"I knew it all along"Review trade journal honestly
Trading Psychology Checklist (Daily)
Am I calm? (no anger, fear, or euphoria) Am I following my system? (not improvising) Am I within risk limits? (checked portfolio heat) Am I trading my plan? (not reacting to noise) Have I done my analysis? (not trading on tips)
Quality Scoring (0-100)
DimensionWeightCriteriaThesis Quality20Clear edge, documented invalidation, realistic timeframeRisk Management25Position sizing, stops, portfolio heat, correlationAnalysis Depth15Fundamental + technical + macro consideredExecution15Entry/exit discipline, order type selection, patienceRecord Keeping10Trade journal, performance metrics, monthly reviewsPsychology10Emotional control, bias awareness, plan adherenceTax Efficiency5Harvesting, account allocation, holding periods Score /100. Above 80 = professional-grade process. Below 50 = gambling.
Natural Language Commands
CommandAction"Analyze [ticker]"Full fundamental + technical analysis"Compare [ticker1] vs [ticker2]"Side-by-side comparison"Build thesis for [ticker]"Generate thesis brief template"Size position for [ticker] at [price]"Calculate position size with risk"Portfolio health check"Score current portfolio /8"Monthly review"Generate performance review template"Screen for [value/growth/dividend/crypto]"Apply screening criteria"What's the market regime?"Assess current macro environment"Tax harvest opportunities"Identify positions for loss harvesting"DCA plan for [asset]"Generate dollar cost averaging plan"Dividend score for [ticker]"Run dividend quality analysis"Risk report"Portfolio heat, correlations, exposure summary Built by AfrexAI โ turning market noise into signal. ๐ค๐
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- README.md