Investment Analysis & Portfolio Management Engine
by @1kalin
Performs structured investment thesis development, fundamental and technical analysis, portfolio risk management, and trade execution across asset classes.
clawhub install afrexai-investment-engineπ About This Skill
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 β pure agent skill.
Quick Health Check (/8)
Before any investment activity, score your current state:
| Signal | β Healthy | β 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 β 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 Γ R_bull) + (P_base Γ R_base) + (P_bear Γ R_bear)
current_price: 190
expected_value: 213.5 # (0.3Γ245 + 0.5Γ215 + 0.2Γ165)
ev_vs_current: "+12.4%"
# INVALIDATION β 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
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
# 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
| Method | Best For | Formula | |--------|----------|---------| | Stock-to-Flow | BTC | Price = 0.4 Γ 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 β nΒ² (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
| 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 Γ Risk%) / (Entry - Stop Loss)
# Example: ($100K Γ 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 Γ risk%)
Entry Price: $___________
Stop Loss Price: $___________
Risk Per Share: $___________ (entry - stop)
Position Size: ___________ shares (dollar risk / risk per share)
Position Value: $___________ (shares Γ entry)
Portfolio Weight: ___% (position value / equity)CHECK: Portfolio weight < 10%? β Yes β No (reduce if no)
CHECK: Portfolio heat < 15%? β Yes β No (reduce if no)
CHECK: Correlated exposure ok? β Yes β No (reduce if no)
Stop-Loss Decision Tree
Is this a TREND trade?
βββ YES β Trailing stop below swing low (ATR-based: 2Γ ATR)
β Initial stop: Below last higher low
β Trail: Move stop to below each new higher low
β
βββ NO β Is this a CATALYST trade?
βββ YES β Time-based + price stop
β Price: Below pre-catalyst support
β Time: Close if no move within 2 days post-catalyst
β
βββ Is this a VALUE trade?
βββ YES β Thesis invalidation stop
β Price: Below bear case scenario price
β Thesis: Close if fundamental thesis breaks
β Time: Close if no re-rating in stated timeframe
β
βββ MEAN REVERSION β 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 β 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 β Asymmetric payoff is the goal. 1:3 risk/reward minimum 3. No revenge trading β After a loss, wait 24 hours before next trade 4. Daily loss limit β Stop trading for the day after -3% account drawdown 5. Weekly loss limit β Reduce position sizes by 50% after -5% weekly drawdown 6. Monthly loss limit β Go to cash if -10% monthly drawdown. Review all positions. 7. Correlation check β Before every new position, check correlation to existing holdings 8. Black swan rule β 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% β 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% β 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
| 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) Γ 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)
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% Γ Avg Win) - (Loss% Γ 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
lessons:
- null
- null
- null
# ADJUSTMENTS FOR NEXT MONTH
adjustments:
- null
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)
Sentiment Indicators
| Indicator | Extreme Fear (Buy) | Neutral | Extreme Greed (Sell) | |-----------|-------------------|---------|---------------------| | CNN Fear & Greed | <20 | 40-60 | >80 | | AAII Bull-Bear | >-30% spread | Β±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
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: SPYβVOO, AAPLβQQQ, BTC spotβBTC 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:
Growth Screen:
Dividend Screen:
Crypto Screen:
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 β 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 Γ 1.5"
multiplier: 0.5 # buy less in euphoria
Rebalancing Decision Tree
Is any allocation >5% from target?
βββ NO β No action needed. Check again next month.
β
βββ YES β Is it a tax-advantaged account?
βββ YES β Rebalance by selling overweight, buying underweight
β
βββ NO (taxable) β Can you rebalance with new contributions?
βββ YES β Direct new money to underweight positions
β
βββ NO β Are there tax losses to harvest?
βββ YES β Sell losers (harvest), redirect to underweight
β
βββ NO β Is the drift >10%?
βββ YES β Rebalance (accept tax hit for risk control)
βββ NO β 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)
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.
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 |
*Built by AfrexAI β turning market noise into signal.* π€π