Investment Analysis & Portfolio Management Engine

# Investment Analysis & Portfolio Management Engine

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Install skill "Investment Analysis & Portfolio Management Engine" with this command: npx skills add 1kalin/afrexai-investment-engine

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 — pure agent skill.

Quick Health Check (/8)

Before any investment activity, score your current state:

Signal✅ Healthy❌ Fix First
Investment 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 plan
Portfolio heat trackedTotal exposure known, <15%Unknown aggregate risk
Asset correlation checkedNo >40% correlated concentrationAll tech / all crypto
Rebalance schedule setMonthly or threshold-basedNever rebalanced
Tax impact consideredHarvesting losses, holding periodsTax-blind trading
Performance 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 — 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 × R_bull) + (P_base × R_base) + (P_bear × R_bear)
  current_price: 190
  expected_value: 213.5  # (0.3×245 + 0.5×215 + 0.2×165)
  ev_vs_current: "+12.4%"
  
  # INVALIDATION — 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 Rate
MispricingMarket wrong on fundamentalsComp analysis + modelSlow (months)
CatalystKnown upcoming eventCalendar + probabilityFast (event-driven)
TrendMomentum / technicalPrice action + volumeMedium (weeks)
Mean ReversionExtreme deviation from normZ-score + historyMedium
StructuralMarket 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?"

Phase 2: Fundamental Analysis

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

DimensionMetricHealthyWarningDanger
ProfitabilityGross 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%Declining
GrowthFCF Growth>10%0-10%Declining
LeverageDebt/Equity<0.50.5-1.5>1.5
LeverageInterest Coverage>8x3-8x<3x
LeverageNet Debt/EBITDA<2x2-4x>4x
LiquidityCurrent Ratio>1.51-1.5<1
LiquidityQuick Ratio>1.00.5-1<0.5
EfficiencyAsset Turnover>0.80.4-0.8<0.4
EfficiencyInventory Days<6060-120>120
QualityFCF/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 Required
Network EffectsUsers increase value for other users
Switching CostsPainful to leave (data lock-in, integrations)
Cost AdvantagesStructural cost below competitors
Intangible AssetsBrand, patents, regulatory licenses
Efficient 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 ForFormula
Stock-to-FlowBTCPrice = 0.4 × S2F^3 (check vs actual)
NVT RatioL1 chainsNetwork Value / Daily Transaction Value
TVL RatioDeFiMarket Cap / TVL (below 1 = undervalued)
Fee Revenue MultipleRevenue-generatingMC / Annualized Fees
Metcalfe's LawNetwork tokensValue ∝ n² (active addresses)

Phase 3: Technical Analysis

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 lows
Momentum (weight 2x)RSI 40-60 rising, MACD bull crossRSI 45-55 flatRSI >75 or bearish div
Volume (weight 2x)Rising on up movesAverageRising on down moves
Support/Resistance (weight 1x)Near strong supportMid-rangeNear strong resistance
Pattern (weight 1x)Bullish continuationNo patternBearish reversal

Score -9 to +9. Above +5 = strong buy signal. Below -5 = strong sell signal.


Phase 4: Position Sizing & Risk Management

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 × Risk%) / (Entry - Stop Loss)
  # Example: ($100K × 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 × risk%)
Entry Price:        $___________
Stop Loss Price:    $___________
Risk Per Share:     $___________  (entry - stop)
Position Size:      ___________ shares (dollar risk / risk per share)
Position Value:     $___________  (shares × entry)
Portfolio Weight:   ___%          (position value / equity)

CHECK: Portfolio weight < 10%?  ☐ Yes ☐ No (reduce if no)
CHECK: Portfolio heat < 15%?    ☐ Yes ☐ No (reduce if no)
CHECK: Correlated exposure ok?  ☐ Yes ☐ No (reduce if no)

Stop-Loss Decision Tree

Is this a TREND trade?
├── YES → Trailing stop below swing low (ATR-based: 2× ATR)
│         Initial stop: Below last higher low
│         Trail: Move stop to below each new higher low
│
└── NO → Is this a CATALYST trade?
    ├── YES → Time-based + price stop
    │         Price: Below pre-catalyst support
    │         Time: Close if no move within 2 days post-catalyst
    │
    └── Is this a VALUE trade?
        ├── YES → Thesis invalidation stop
        │         Price: Below bear case scenario price
        │         Thesis: Close if fundamental thesis breaks
        │         Time: Close if no re-rating in stated timeframe
        │
        └── MEAN REVERSION → Tight stop
            Price: If moves further from mean (wider Z-score)
            Target: Mean / fair value level

Risk Management Hard Rules

  1. Never average down without a plan — Adding to losers kills accounts. Only add if: thesis intact AND price at predetermined add level AND total position still within limits
  2. Cut losses fast, let winners run — Asymmetric payoff is the goal. 1:3 risk/reward minimum
  3. No revenge trading — After a loss, wait 24 hours before next trade
  4. Daily loss limit — Stop trading for the day after -3% account drawdown
  5. Weekly loss limit — Reduce position sizes by 50% after -5% weekly drawdown
  6. Monthly loss limit — Go to cash if -10% monthly drawdown. Review all positions.
  7. Correlation check — Before every new position, check correlation to existing holdings
  8. Black swan rule — If any asset moves >15% in 24h, review ALL positions immediately

Phase 5: Portfolio Construction

Asset Allocation Framework

portfolio:
  name: "Growth + Income"
  target_allocation:
    # Core (60-70% — 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% — 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 Drawdown
Conservative30%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

Phase 6: Trade Execution

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) × 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 (≤2% risk, ≤10% portfolio weight)
  • Stop-loss set (price + thesis + time)
  • At least 2 take-profit targets defined
  • Risk/reward ≥1:2 (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 TypeWhy
Strong conviction, want in nowMarketSpeed over price
Good setup, not urgentLimit at supportBetter entry
High-conviction, want scale inScaled limits (3 levels)Average entry, reduce timing risk
Breakout tradeStop-limit above resistanceOnly enter if breakout confirms
Catalyst tradeLimit pre-catalystPosition before event

Phase 7: Performance Tracking

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)

MetricFormulaTarget
Win RateWinning trades / Total trades>50%
Average RAverage R-multiple of all trades>1.5R
Profit FactorGross profit / Gross loss>2.0
Expectancy(Win% × Avg Win) - (Loss% × Avg Loss)Positive
Max DrawdownPeak to trough decline<-15%
Sharpe Ratio(Return - RFR) / Std Dev>1.5
Sortino Ratio(Return - RFR) / Downside Dev>2.0
Calmar RatioAnnual Return / Max Drawdown>1.0
Recovery 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

Phase 8: Market Regime Detection

Regime Framework

RegimeCharacteristicsStrategyPosition Size
Bull TrendRising 200MA, breadth >60%, VIX <20Trend following, buy dipsFull size
Bear TrendFalling 200MA, breadth <40%, VIX >30Short / inverse, raise cashHalf size
Range/ChopFlat 200MA, breadth 40-60%Mean reversion, sell premiumQuarter size
High VolVIX >35, large daily swingsReduce exposure, hedgeMinimum size
EuphoriaVIX <12, extreme bullish sentimentTake profits, hedgeScale down
PanicVIX >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>80
AAII Bull-Bear>-30% spread±10%>+30% spread
Put/Call Ratio>1.20.7-0.9<0.5
VIX Term StructureBackwardationFlatSteep contango
Crypto Fear & Greed<1540-60>85
BTC Funding RatesDeeply negativeNeutral>0.05%

Phase 9: Dividend & Income Analysis

Dividend Quality Score (0-100)

FactorWeightScoring
Yield vs Sector15At/above median = 15, below = proportional
Payout Ratio20<50% = 20, 50-75% = 15, 75-100% = 5, >100% = 0
Growth Rate (5Y CAGR)20>10% = 20, 5-10% = 15, 0-5% = 10, declining = 0
Consecutive Years15>25y = 15 (Aristocrat), 10-25 = 10, 5-10 = 5, <5 = 0
FCF Coverage15FCF/Div >1.5 = 15, 1-1.5 = 10, <1 = 0
Debt/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

Phase 10: Tax Optimization

Tax-Loss Harvesting Rules

  1. When: Position down >10% from cost basis AND held <12 months
  2. How: Sell the position, immediately buy a correlated (not substantially identical) replacement
  3. Wash sale rule: Cannot buy back the same security within 30 days (before or after)
  4. Replacement examples: SPY→VOO, AAPL→QQQ, BTC spot→BTC futures ETF
  5. 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 ForWhy
TaxableLong-term holds, tax-loss harvestingCapital gains treatment
Traditional IRA/401kBonds, REITs, high-dividendDefer high-tax income
Roth IRAHighest growth potentialTax-free growth
HSAAggressive growthTriple tax advantage

Phase 11: Screening & Idea Generation

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 For
Yahoo Financefinance.yahoo.comFundamentals, quotes
Finvizfinviz.comScreening, heatmaps
Macrotrendsmacrotrends.netHistorical financials
CoinGeckocoingecko.comCrypto data
DeFiLlamadefillama.comDeFi TVL, yields
FREDfred.stlouisfed.orgMacro data
TradingViewtradingview.comCharts, technicals
SEC EDGARsec.gov/edgarFilings, insider trades
Glassnodeglassnode.comOn-chain data
Fear & Greedalternative.meCrypto sentiment

Phase 12: Advanced Strategies

Options Basics (for hedging)

StrategyWhenRiskReward
Protective PutOwn stock, want downside protectionPremium paidUnlimited upside, limited downside
Covered CallOwn stock, willing to cap upsideCapped gainsPremium income
Cash-Secured PutWant to buy at lower priceMust buy at strikePremium + lower entry
CollarWant 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 — 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 × 1.5"
        multiplier: 0.5          # buy less in euphoria

Rebalancing Decision Tree

Is any allocation >5% from target?
├── NO → No action needed. Check again next month.
│
└── YES → Is it a tax-advantaged account?
    ├── YES → Rebalance by selling overweight, buying underweight
    │
    └── NO (taxable) → Can you rebalance with new contributions?
        ├── YES → Direct new money to underweight positions
        │
        └── NO → Are there tax losses to harvest?
            ├── YES → Sell losers (harvest), redirect to underweight
            │
            └── NO → Is the drift >10%?
                ├── YES → Rebalance (accept tax hit for risk control)
                └── NO → Wait for next contribution or year-end

Investor Psychology Rules

10 Cognitive Biases That Kill Returns

BiasTrapDefense
Loss AversionHolding losers, cutting winnersPre-set stops, mechanical exits
Confirmation BiasOnly seeing data that supports thesisActively seek disconfirming evidence
Recency BiasExtrapolating recent performanceLook at full cycle data (10+ years)
AnchoringFixating on purchase priceFocus on current value vs alternatives
FOMOChasing after 50%+ moveStick to your screener, your edge
OverconfidenceToo large positions after winsFixed position sizing rules
Disposition EffectSelling winners too earlyTrailing stops, let runners run
HerdingBuying because everyone isContrarian checkpoints
Sunk 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)

DimensionWeightCriteria
Thesis Quality20Clear edge, documented invalidation, realistic timeframe
Risk Management25Position sizing, stops, portfolio heat, correlation
Analysis Depth15Fundamental + technical + macro considered
Execution15Entry/exit discipline, order type selection, patience
Record Keeping10Trade journal, performance metrics, monthly reviews
Psychology10Emotional control, bias awareness, plan adherence
Tax 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 — turning market noise into signal. 🖤💛

Source Transparency

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