afrexai-investment-engine

name	afrexai-investment-engine
description	Investment Analysis & Portfolio Management 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 documented	Written with edge + invalidation	"I think it'll go up"
Position sizing calculated	Kelly/fixed-fractional with max cap	"I'll put in $5K"
Stop-loss defined	Price or thesis invalidation trigger	No exit plan
Portfolio heat tracked	Total exposure known, <15%	Unknown aggregate risk
Asset correlation checked	No >40% correlated concentration	All tech / all crypto
Rebalance schedule set	Monthly or threshold-based	Never rebalanced
Tax impact considered	Harvesting losses, holding periods	Tax-blind trading
Performance tracked	Benchmarked 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 Type	Description	Validation Method	Decay Rate
Mispricing	Market wrong on fundamentals	Comp analysis + model	Slow (months)
Catalyst	Known upcoming event	Calendar + probability	Fast (event-driven)
Trend	Momentum / technical	Price action + volume	Medium (weeks)
Mean Reversion	Extreme deviation from norm	Z-score + history	Medium
Structural	Market structure creates opportunity	Flow analysis	Slow

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

Dimension	Metric	Healthy	Warning	Danger
Profitability	Gross Margin	>50%	30-50%	<30%
Profitability	Net Margin	>15%	5-15%	<5%
Profitability	ROE	>15%	8-15%	<8%
Profitability	ROIC	>12%	6-12%	<6%
Growth	Revenue YoY	>15%	5-15%	<5%
Growth	EPS YoY	>10%	0-10%	Declining
Growth	FCF Growth	>10%	0-10%	Declining
Leverage	Debt/Equity	<0.5	0.5-1.5	>1.5
Leverage	Interest Coverage	>8x	3-8x	<3x
Leverage	Net Debt/EBITDA	<2x	2-4x	>4x
Liquidity	Current Ratio	>1.5	1-1.5	<1
Liquidity	Quick Ratio	>1.0	0.5-1	<0.5
Efficiency	Asset Turnover	>0.8	0.4-0.8	<0.4
Efficiency	Inventory Days	<60	60-120	>120
Quality	FCF/Net Income	>80%	50-80%	<50%
Quality	Accruals Ratio	<5%	5-10%	>10%

Score each dimension 1-3. Total /48. Above 36 = strong. Below 24 = avoid.

Moat Assessment (0-25 points)

Moat Source	Score 0-5	Evidence Required
Network Effects		Users increase value for other users
Switching Costs		Painful to leave (data lock-in, integrations)
Cost Advantages		Structural cost below competitors
Intangible Assets		Brand, patents, regulatory licenses
Efficient Scale		Market 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
    
  
  
                
     
     
     
     

Crypto Valuation Methods

Method	Best For	Formula
Stock-to-Flow	BTC	Price = 0.4 × S2F^3 (check vs actual)
NVT Ratio	L1 chains	Network Value / Daily Transaction Value
TVL Ratio	DeFi	Market Cap / TVL (below 1 = undervalued)
Fee Revenue Multiple	Revenue-generating	MC / Annualized Fees
Metcalfe's Law	Network tokens	Value ∝ 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"
    
  
  
     
       
    
  
  
     
     
     
     

Signal Scoring Matrix

Factor	Bullish (+)	Neutral (0)	Bearish (-)
Trend (weight 3x)	Above 200MA, higher highs	Ranging	Below 200MA, lower lows
Momentum (weight 2x)	RSI 40-60 rising, MACD bull cross	RSI 45-55 flat	RSI >75 or bearish div
Volume (weight 2x)	Rising on up moves	Average	Rising on down moves
Support/Resistance (weight 1x)	Near strong support	Mid-range	Near strong resistance
Pattern (weight 1x)	Bullish continuation	No pattern	Bearish 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             
      
                

Portfolio Models by Risk Profile

Profile	Stocks	Bonds	Crypto	Alts	Cash	Expected Return	Max Drawdown
Conservative	30%	40%	5%	10%	15%	6-8%	-15%
Balanced	50%	20%	10%	10%	10%	8-12%	-25%
Growth	60%	10%	15%	10%	5%	12-18%	-35%
Aggressive	50%	0%	30%	15%	5%	15-25%	-50%
Degen	20%	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 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

Situation	Order Type	Why
Strong conviction, want in now	Market	Speed over price
Good setup, not urgent	Limit at support	Better entry
High-conviction, want scale in	Scaled limits (3 levels)	Average entry, reduce timing risk
Breakout trade	Stop-limit above resistance	Only enter if breakout confirms
Catalyst trade	Limit pre-catalyst	Position 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)

Metric	Formula	Target
Win Rate	Winning trades / Total trades	>50%
Average R	Average R-multiple of all trades	>1.5R
Profit Factor	Gross profit / Gross loss	>2.0
Expectancy	(Win% × Avg Win) - (Loss% × Avg Loss)	Positive
Max Drawdown	Peak to trough decline	<-15%
Sharpe Ratio	(Return - RFR) / Std Dev	>1.5
Sortino Ratio	(Return - RFR) / Downside Dev	>2.0
Calmar Ratio	Annual Return / Max Drawdown	>1.0
Recovery Factor	Net 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
  
     
     
     
    
  
  
     

---

Phase 8: Market Regime Detection

Regime Framework

Regime	Characteristics	Strategy	Position Size
Bull Trend	Rising 200MA, breadth >60%, VIX <20	Trend following, buy dips	Full size
Bear Trend	Falling 200MA, breadth <40%, VIX >30	Short / inverse, raise cash	Half size
Range/Chop	Flat 200MA, breadth 40-60%	Mean reversion, sell premium	Quarter size
High Vol	VIX >35, large daily swings	Reduce exposure, hedge	Minimum size
Euphoria	VIX <12, extreme bullish sentiment	Take profits, hedge	Scale down
Panic	VIX >50, capitulation signals	Accumulate quality	Scale 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

Indicator	Extreme Fear (Buy)	Neutral	Extreme Greed (Sell)
CNN Fear & Greed	<20	40-60	>80
AAII Bull-Bear	>-30% spread	±10%	>+30% spread
Put/Call Ratio	>1.2	0.7-0.9	<0.5
VIX Term Structure	Backwardation	Flat	Steep contango
Crypto Fear & Greed	<15	40-60	>85
BTC Funding Rates	Deeply negative	Neutral	>0.05%

---

Phase 9: Dividend & Income Analysis

Dividend Quality Score (0-100)

Factor	Weight	Scoring
Yield vs Sector	15	At/above median = 15, below = proportional
Payout Ratio	20	<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 Years	15	>25y = 15 (Aristocrat), 10-25 = 10, 5-10 = 5, <5 = 0
FCF Coverage	15	FCF/Div >1.5 = 15, 1-1.5 = 10, <1 = 0
Debt/EBITDA	15	<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 Period	Tax Rate (US)	Strategy
<1 year	Ordinary income (up to 37%)	Only for high-conviction short-term trades
>1 year	Long-term CG (0/15/20%)	Default for all positions when possible
>5 years (QOZ)	Reduced + deferred	Qualified Opportunity Zone investments

Tax-Efficient Account Allocation

Account Type	Best For	Why
Taxable	Long-term holds, tax-loss harvesting	Capital gains treatment
Traditional IRA/401k	Bonds, REITs, high-dividend	Defer high-tax income
Roth IRA	Highest growth potential	Tax-free growth
HSA	Aggressive growth	Triple 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)

Source	URL	Best For
Yahoo Finance	finance.yahoo.com	Fundamentals, quotes
Finviz	finviz.com	Screening, heatmaps
Macrotrends	macrotrends.net	Historical financials
CoinGecko	coingecko.com	Crypto data
DeFiLlama	defillama.com	DeFi TVL, yields
FRED	fred.stlouisfed.org	Macro data
TradingView	tradingview.com	Charts, technicals
SEC EDGAR	sec.gov/edgar	Filings, insider trades
Glassnode	glassnode.com	On-chain data
Fear & Greed	alternative.me	Crypto sentiment

---

Phase 12: Advanced Strategies

Options Basics (for hedging)

Strategy	When	Risk	Reward
Protective Put	Own stock, want downside protection	Premium paid	Unlimited upside, limited downside
Covered Call	Own stock, willing to cap upside	Capped gains	Premium income
Cash-Secured Put	Want to buy at lower price	Must buy at strike	Premium + lower entry
Collar	Want protection, willing to cap upside	Capped both ways	Low/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

Bias	Trap	Defense
Loss Aversion	Holding losers, cutting winners	Pre-set stops, mechanical exits
Confirmation Bias	Only seeing data that supports thesis	Actively seek disconfirming evidence
Recency Bias	Extrapolating recent performance	Look at full cycle data (10+ years)
Anchoring	Fixating on purchase price	Focus on current value vs alternatives
FOMO	Chasing after 50%+ move	Stick to your screener, your edge
Overconfidence	Too large positions after wins	Fixed position sizing rules
Disposition Effect	Selling winners too early	Trailing stops, let runners run
Herding	Buying because everyone is	Contrarian 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)

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Quality Scoring (0-100)

Dimension	Weight	Criteria
Thesis Quality	20	Clear edge, documented invalidation, realistic timeframe
Risk Management	25	Position sizing, stops, portfolio heat, correlation
Analysis Depth	15	Fundamental + technical + macro considered
Execution	15	Entry/exit discipline, order type selection, patience
Record Keeping	10	Trade journal, performance metrics, monthly reviews
Psychology	10	Emotional control, bias awareness, plan adherence
Tax Efficiency	5	Harvesting, account allocation, holding periods

Score /100. Above 80 = professional-grade process. Below 50 = gambling.

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Natural Language Commands

Command	Action
"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

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