Upload metrics_guide.py

metrics_guide.py

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+"""AlphaForge Metrics Guide - Deep explanations of every metric and how to trade with them.
+
+This module teaches you WHAT each number means, WHY it matters, and HOW to act on it.
+Think of this as your quant trading playbook.
+"""
+
+METRICS_GUIDE = {
+    "sharpe_ratio": {
+        "name": "Sharpe Ratio",
+        "formula": "(Portfolio Return - Risk-Free Rate) / Portfolio Volatility",
+        "what_it_means": """
+The Sharpe Ratio tells you how much EXTRA return you get per unit of risk taken.
+It's the #1 metric every hedge fund looks at first.
+
+- Sharpe = 0.5  →  You're getting some reward for risk, but barely worth it
+- Sharpe = 1.0  →  Good. You're getting $1 of return for every $1 of risk
+- Sharpe = 1.5  →  Very good. Professional-grade
+- Sharpe = 2.0+ →  Excellent. Top-quartile hedge fund territory
+- Sharpe = 3.0+ →  Legendary. Renaissance Technologies territory
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If Sharpe < 0.5:  STOP. Your strategy is broken. Reduce position sizes by 50% or stop trading.
+- If Sharpe 0.5-1.0: CAUTION. You're making money but taking too much risk. Tighten stops, reduce leverage.
+- If Sharpe 1.0-1.5: SOLID. This is your baseline. Keep doing what you're doing.
+- If Sharpe 1.5-2.0: GREAT. Consider INCREASING position sizes by 20-30%.
+- If Sharpe > 2.0: EXCEPTIONAL. This is when you go ALL IN. Max out your allocation.
+
+TWO SIGMA BENCHMARK: Their flagship fund runs ~1.8 Sharpe
+CITADEL BENCHMARK: Their equity fund runs ~2.1 Sharpe
+YOUR GOAL: Consistently above 1.2 Sharpe
+""",
+        "real_example": """
+Example: Your strategy returned 15% with 12% volatility. Risk-free rate is 4%.
+Sharpe = (15% - 4%) / 12% = 0.92
+
+Verdict: Decent, but not amazing. You're getting $0.92 per $1 of risk.
+To improve: Either increase return (better signals) or reduce volatility (hedging).
+""",
+        "tier": "CRITICAL",
+        "weight": 0.25
+    },
+
+    "sortino_ratio": {
+        "name": "Sortino Ratio",
+        "formula": "(Portfolio Return - Risk-Free Rate) / Downside Volatility",
+        "what_it_means": """
+Sortino is like Sharpe, but it ONLY counts bad volatility (losses).
+Sharpe punishes you for ALL volatility — even the good kind (big upward jumps).
+Sortino is smarter: it only cares about downside risk.
+
+- Sortino < 1.0  →  Your losses are too frequent or too large
+- Sortino 1.0-1.5 →  Acceptable. You handle downside okay
+- Sortino 1.5-2.5 →  Strong. You make money while controlling losses
+- Sortino 2.5+   →  Elite. You're a loss-cutting machine
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If Sortino < Sharpe: GOOD. Means your upside volatility is helping you.
+- If Sortino ≈ Sharpe: NEUTRAL. Your upside and downside are balanced.
+- If Sortino > Sharpe by 0.5+: EXCELLENT. You have asymmetric upside — the holy grail.
+- If Sortino drops below 0.8: RAISE STOPS IMMEDIATELY. Your downside is out of control.
+
+PRO TIP: Always compare Sortino to Sharpe. The GAP between them tells you
+if your strategy has positive skew (good) or negative skew (dangerous).
+""",
+        "real_example": """
+Example: Return = 12%, Downside volatility = 5%, Total volatility = 15%
+Sharpe = (12-4)/15 = 0.53
+Sortino = (12-4)/5 = 1.6
+
+Verdict: Sharpe looks mediocre, but Sortino is strong! This means most of your 
+volatility is UPWARD (good jumps). Strategy has positive skew. KEEP TRADING.
+""",
+        "tier": "CRITICAL",
+        "weight": 0.20
+    },
+
+    "information_coefficient": {
+        "name": "Information Coefficient (IC)",
+        "formula": "Rank correlation between predicted returns and actual returns",
+        "what_it_means": """
+IC measures: "How good are my predictions ACTUALLY?"
+It's the correlation between what your model PREDICTED and what REALLY happened.
+
+- IC = 0.00  →  Your model is random. Coin-flip level.
+- IC = 0.02  →  Barely useful. Weak but tradable at scale.
+- IC = 0.05  →  Decent. This is where most quant strategies live.
+- IC = 0.10  →  Strong. You're genuinely predicting better than chance.
+- IC = 0.15+ →  Exceptional. Top-tier signal quality.
+
+KEY INSIGHT: IC compounds. If you have 0.05 IC daily, that's MASSIVE over a year.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If IC < 0.02:  YOUR SIGNAL IS DEAD. Stop trading it. Retrain the model.
+- If IC 0.02-0.05: WORKABLE. Trade smaller sizes. This is your bread-and-butter range.
+- If IC 0.05-0.08: STRONG. Increase allocation to this signal. Scale up positions.
+- If IC 0.08-0.12: EXCELLENT. This is your golden goose. Maximize exposure.
+- If IC turns NEGATIVE: SIGNAL DECAY. Your model is now WRONG. FLIP THE SIGNAL or stop.
+
+IC IR (IC / std(IC)): 
+- IC IR < 0.5: Unstable signal. Too noisy.
+- IC IR 0.5-1.0: Decent stability.
+- IC IR > 1.0: Rock solid. You can build a career on this.
+""",
+        "real_example": """
+Example: You predicted AAPL would return +2%, MSFT +1%, TSLA -1%.
+Actual returns: AAPL +3%, MSFT 0%, TSLA -2%.
+
+Your ranking was: AAPL > MSFT > TSLA
+Actual ranking was: AAPL > MSFT > TSLA
+IC = 1.0 (perfect!)
+
+But if actual was: TSLA +5%, AAPL +1%, MSFT -1%
+Then your ranking was wrong. IC would be negative.
+
+This is why IC is rank-based — it cares about ORDER, not exact values.
+""",
+        "tier": "CRITICAL",
+        "weight": 0.20
+    },
+
+    "max_drawdown": {
+        "name": "Maximum Drawdown",
+        "formula": "(Peak Value - Trough Value) / Peak Value",
+        "what_it_means": """
+Max Drawdown is: "What's the worst losing streak I've ever had?"
+It's the biggest drop from your highest point to your lowest point.
+
+- Max DD < 5%   →  You're a conservative saint
+- Max DD 5-10%  →  Conservative. Sleep-well-at-night level
+- Max DD 10-20% →  Moderate. Normal for active strategies
+- Max DD 20-30% →  Aggressive. You'll have sleepless nights
+- Max DD 30-50% →  Dangerous. Most people panic-sell here
+- Max DD > 50%  →  You will blow up. Guaranteed.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If Max DD exceeds your personal pain threshold: REDUCE RISK by 50%.
+- If Max DD > 25%: Add hedges (buy puts, short index, reduce beta).
+- If Max DD < 10% for 6 months: You can INCREASE leverage by 25%.
+- If drawdown lasts > 3 months: Something is structurally broken. Review strategy.
+
+THE PSYCHOLOGY RULE:
+Most traders can handle 10% drawdown.
+At 20%, they start questioning the strategy.
+At 30%, they panic and sell the bottom.
+At 40%, they quit trading forever.
+
+Set your max pain level BEFORE you trade. AlphaForge suggests 15% as default.
+""",
+        "real_example": """
+Example: You started with $1M. Grew to $1.3M (peak). Then dropped to $1.1M (trough).
+Max DD = ($1.3M - $1.1M) / $1.3M = 15.4%
+
+This means at your worst moment, you were down $200K from your best moment.
+Can you handle seeing $200K evaporate? If not, trade smaller.
+
+RECOVERY MATH: After a 15.4% drawdown, you need +18.2% to get back to peak.
+After a 50% drawdown, you need +100% just to break even. This is why drawdown KILLS.
+""",
+        "tier": "CRITICAL",
+        "weight": 0.15
+    },
+
+    "calmar_ratio": {
+        "name": "Calmar Ratio",
+        "formula": "Annualized Return / |Max Drawdown|",
+        "what_it_means": """
+Calmar answers: "How much return do I get relative to my worst nightmare?"
+It compares your yearly gain to your maximum drawdown.
+
+- Calmar < 1.0  →  Your drawdown is BIGGER than your annual return. Dangerous.
+- Calmar 1.0-2.0 →  Decent. You're getting paid for the risk.
+- Calmar 2.0-3.0 →  Strong. Good risk/reward balance.
+- Calmar 3.0+   →  Excellent. Your returns dwarf your worst losses.
+
+Calmar is MORE important than Sharpe for long-term survival.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If Calmar < 1.0: EMERGENCY. Your strategy will eventually blow up. Cut size by 75%.
+- If Calmar 1.0-1.5: CAUTION. You're surviving but not thriving. Add diversification.
+- If Calmar 1.5-2.5: SOLID. This is sustainable long-term.
+- If Calmar > 3.0: EXCEPTIONAL. You've found a gem. Scale up carefully.
+
+THE SURVIVAL RULE: No strategy with Calmar < 1.0 survives 5 years. Period.
+""",
+        "real_example": """
+Example: Annual return = 20%, Max drawdown = 15%
+Calmar = 20 / 15 = 1.33
+
+Verdict: Okay but not great. You're making 20% but had a 15% nightmare.
+
+Better: Annual return = 15%, Max drawdown = 5%
+Calmar = 15 / 5 = 3.0
+
+Verdict: MUCH better! Lower return but tiny drawdown. You'll compound wealth 
+steadily without panic-selling. THIS is the path to GOAT status.
+""",
+        "tier": "HIGH",
+        "weight": 0.10
+    },
+
+    "win_rate": {
+        "name": "Win Rate",
+        "formula": "Number of winning days / Total trading days",
+        "what_it_means": """
+Win Rate is: "How often am I right?"
+But here's the SECRET: Win rate ALONE is meaningless.
+
+A 30% win rate can be profitable (if wins are 3x bigger than losses).
+A 70% win rate can be unprofitable (if losses are 3x bigger than wins).
+
+What matters is: Win Rate × Average Win / (1 - Win Rate) × Average Loss
+This is your EXPECTANCY. If it's > 0, you're profitable.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If Win Rate < 40% but profitable: You have positive skew. Your wins are HUGE.
+  → Keep going but prepare for long losing streaks mentally.
+- If Win Rate > 60% but barely profitable: You have negative skew. 
+  → DANGER. One big loss wipes out 10 small wins. Tighten stops.
+- If Win Rate 45-55% with good profits: BALANCED. The sweet spot.
+- If Win Rate drops 10% from historical average: SIGNAL DECAY. Retrain.
+
+THE MENTAL GAME:
+A 50% win rate means you'll have 5 losses in a row ~3% of the time.
+You'll have 10 losses in a row ~0.1% of the time (but it WILL happen).
+Prepare mentally. This is why position sizing > prediction accuracy.
+""",
+        "real_example": """
+Example A: 40% win rate. Average win = $300, average loss = $100
+Expectancy = (0.4 × $300) - (0.6 × $100) = $120 - $60 = +$60 per trade
+Verdict: PROFITABLE despite low win rate!
+
+Example B: 65% win rate. Average win = $100, average loss = $250
+Expectancy = (0.65 × $100) - (0.35 × $250) = $65 - $87.50 = -$22.50 per trade
+Verdict: LOSING despite high win rate! This is a classic trap.
+""",
+        "tier": "MEDIUM",
+        "weight": 0.05
+    },
+
+    "profit_factor": {
+        "name": "Profit Factor",
+        "formula": "Gross Profits / Gross Losses",
+        "what_it_means": """
+Profit Factor is: "For every $1 I lose, how much do I make?"
+
+- PF < 1.0  →  You're losing money. Period.
+- PF = 1.0  →  You're breaking even before costs. Losing money after costs.
+- PF 1.0-1.5 →  Marginal. Profitable but fragile.
+- PF 1.5-2.0 →  Good. Solid edge.
+- PF 2.0-3.0 →  Strong. Professional grade.
+- PF 3.0+   →  Exceptional. Don't tell anyone your secret.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If PF < 1.0: STOP IMMEDIATELY. You have no edge.
+- If PF 1.0-1.3: BARELY ALIVE. One bad streak kills you. Reduce size 50%.
+- If PF 1.3-1.8: HEALTHY. This is sustainable.
+- If PF > 2.0: ROBUST. You can survive multiple bad streaks.
+
+THE COMPOUNDING RULE:
+PF of 1.5 with 50% win rate = steady wealth builder
+PF of 1.2 with 60% win rate = fragile, will eventually break
+
+Higher PF > Higher Win Rate (for survival).
+""",
+        "real_example": """
+Example: Over 100 trades, your winners totaled $50,000. Your losers totaled $30,000.
+Profit Factor = $50,000 / $30,000 = 1.67
+
+Verdict: For every $1 you lost, you made $1.67. Solid.
+After transaction costs (say $5,000), net PF = $45K/$35K = 1.29
+
+Transaction costs dropped your PF from 1.67 to 1.29! This is why 
+keeping costs low is CRITICAL. Use low-cost brokers, trade less.
+""",
+        "tier": "HIGH",
+        "weight": 0.05
+    },
+
+    "alpha": {
+        "name": "Alpha (Jensen's Alpha)",
+        "formula": "Portfolio Return - (Risk-Free Rate + Beta × (Market Return - Risk-Free Rate))",
+        "what_it_means": """
+Alpha is: "How much EXTRA return did I generate ABOVE what the market explains?"
+If Beta = 1 and market goes up 10%, you "should" make 10%.
+If you made 15%, your Alpha = 5%. That's YOUR skill.
+
+- Alpha < 0%   →  You're underperforming a simple index fund. Just buy SPY.
+- Alpha 0-2%   →  Matching the market. No edge.
+- Alpha 2-5%   →  Good. You're adding value.
+- Alpha 5-10%  →  Strong. Significant edge.
+- Alpha 10%+   →  Elite. You're in the top 1% of managers.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If Alpha < 0% for 6+ months: JUST BUY THE INDEX. You're wasting time and money.
+- If Alpha 0-3%: You're a "closet indexer." Either commit to active or go passive.
+- If Alpha 3-7%: SOLID EDGE. Keep refining but don't over-optimize.
+- If Alpha > 7%: EXCEPTIONAL. Document your process. This edge won't last forever.
+
+THE HUMBLING TRUTH:
+80% of active managers have NEGATIVE alpha after fees.
+S&P 500 has returned ~10%/year for decades.
+If you can't beat that, just buy SPY and enjoy life.
+""",
+        "real_example": """
+Example: You returned 18%. Market (SPY) returned 12%. Your Beta = 1.2. Risk-free = 4%.
+Expected return = 4% + 1.2 × (12% - 4%) = 4% + 9.6% = 13.6%
+Alpha = 18% - 13.6% = 4.4%
+
+Verdict: You beat what the market explains by 4.4%. That's YOUR skill.
+But if you paid 2% in fees, net alpha = 2.4%. Still good, but fees HALVED it.
+
+This is why hedge funds charge 2% + 20% — they claim to generate alpha.
+Most don't. You can beat them with discipline.
+""",
+        "tier": "HIGH",
+        "weight": 0.05
+    },
+
+    "beta": {
+        "name": "Beta",
+        "formula": "Covariance(Portfolio, Market) / Variance(Market)",
+        "what_it_means": """
+Beta measures: "How much do I move when the market moves?"
+
+- Beta = 0.0  →  You're market-neutral. Market crashes, you don't care.
+- Beta = 0.5  →  You're conservative. Market up 10%, you up 5%.
+- Beta = 1.0  →  You move exactly with the market (like SPY).
+- Beta = 1.5  →  You're aggressive. Market up 10%, you up 15%. Market down 10%, you down 15%.
+- Beta = -0.5 →  You move opposite to market. Market crashes, you gain.
+
+Beta is NOT good or bad. It's a CHOICE based on your goals.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If you want MARKET EXPOSURE (bullish): Target Beta 0.8-1.2
+- If you want LOW RISK (wealth preservation): Target Beta 0.3-0.6
+- If you want MARKET NEUTRAL (hedge fund style): Target Beta 0.0 ± 0.1
+- If you want INVERSE (betting on crash): Target Beta -0.5 to -1.0
+
+DYNAMIC BETA MANAGEMENT:
+- In bull markets (regime = 'bull'): Increase beta to 1.2-1.5 to capture upside
+- In bear markets (regime = 'bear'): Reduce beta to 0.3-0.5 to protect capital
+- In high volatility: Reduce beta to 0.0-0.3. Survive first, profit second.
+
+THE BETA TRAP:
+Most amateur traders have Beta > 1.5 without knowing it.
+They think they're skilled, but they're just LEVERAGED to the market.
+When the market crashes, they get destroyed.
+""",
+        "real_example": """
+Example: Market (SPY) drops 20% in a month.
+- If your Beta = 0.3: You drop ~6%. Annoying but survivable.
+- If your Beta = 1.5: You drop ~30%. Devastating.
+- If your Beta = -0.2: You GAIN ~4%. You're the smart one.
+
+This is why Beta management is MORE important than stock picking.
+Being in the right "market exposure" at the right time beats being right about Apple.
+""",
+        "tier": "HIGH",
+        "weight": 0.05
+    },
+
+    "information_ratio": {
+        "name": "Information Ratio",
+        "formula": "(Portfolio Return - Benchmark Return) / Tracking Error",
+        "what_it_means": """
+Information Ratio measures: "How much excess return do I get per unit of ACTIVE risk?"
+It's like Sharpe, but compares you to a BENCHMARK instead of risk-free rate.
+
+- IR < 0.0  →  You're losing to the benchmark. Just buy the index.
+- IR 0.0-0.3 →  Barely adding value. Probably not worth the effort.
+- IR 0.3-0.5 →  Decent. You're adding some value.
+- IR 0.5-1.0 →  Good. Meaningful active management skill.
+- IR 1.0+   →  Excellent. Top-tier active manager.
+
+THE GOLDEN RULE: IR > 0.5 means active management is WORTH the fees/time.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If IR < 0: STOP ACTIVE TRADING. Buy SPY and save yourself the stress.
+- If IR 0-0.3: You're "expensive index fund." Reduce active bets, increase passive.
+- If IR 0.3-0.7: SOLID ACTIVE MANAGEMENT. Keep your current strategy.
+- If IR > 0.7: EXCEPTIONAL. You have genuine skill. Consider managing money for others.
+
+TRACKING ERROR:
+Low tracking error + positive IR = "closet indexer with slight edge"
+High tracking error + positive IR = "concentrated bets paying off"
+High tracking error + negative IR = "you're gambling, not investing"
+""",
+        "real_example": """
+Example: You returned 14%. SPY returned 10%. Tracking error = 8%.
+IR = (14% - 10%) / 8% = 0.5
+
+Verdict: You're making 4% extra but with 8% of "different" risk.
+IR = 0.5 means it's worth it, but barely.
+
+Better scenario: You returned 16%. SPY returned 10%. Tracking error = 5%.
+IR = (16% - 10%) / 5% = 1.2
+
+Verdict: MUCH better! More excess return with LESS tracking error.
+This is the definition of skill. IR > 1.0 is top 5% of all managers.
+""",
+        "tier": "MEDIUM",
+        "weight": 0.05
+    },
+
+    "turnover": {
+        "name": "Portfolio Turnover",
+        "formula": "Sum of absolute weight changes / 2",
+        "what_it_means": """
+Turnover measures: "How much of my portfolio did I trade?"
+100% turnover = You sold everything and bought new stuff.
+
+- Turnover < 20%/year  →  Very low. Buy-and-hold style.
+- Turnover 20-50%/year →  Low. Long-term focused.
+- Turnover 50-100%/year →  Moderate. Typical for active strategies.
+- Turnover 100-200%/year →  High. Trading frequently.
+- Turnover > 300%/year  →  Very high. Day-trading territory.
+
+HIGH TURNOVER = HIGH COSTS. Every trade costs money.
+""",
+        "how_it_influences": """
+ACTIONABLE RULES:
+- If turnover > 150% but Sharpe < 1.0: You're trading too much. Reduce rebalancing frequency.
+- If turnover < 30% but Sharpe > 1.5: Perfect. Low cost, high return.
+- If transaction costs > 20% of gross profits: Your strategy is paying your broker, not you.
+
+THE COST RULE:
+At 3bps (0.03%) per trade + 150% annual turnover:
+Total cost = 150% × 0.03% × 2 (buy + sell) = 0.09% per year
+
+At 10bps + 300% turnover:
+Total cost = 300% × 0.10% × 2 = 0.60% per year
+
+This doesn't sound like much, but on $1M, that's $6,000/year in friction.
+Over 20 years at 10% return, that's $40,000+ in lost compounding.
+""",
+        "real_example": """
+Example: Your strategy rebalances weekly. Each rebalance has 40% turnover.
+Annual turnover = 40% × 52 weeks = 2,080%
+
+At 3bps cost: Annual friction = 2,080% × 0.03% × 2 = 1.25%
+
+If your gross alpha is 3%, your NET alpha is 3% - 1.25% = 1.75%
+You lost 42% of your edge to transaction costs!
+
+SOLUTION: Rebalance monthly instead of weekly.
+Annual turnover = 40% × 12 = 480%
+Annual friction = 480% × 0.03% × 2 = 0.29%
+Net alpha = 3% - 0.29% = 2.71%
+
+You DOUBLED your net alpha just by trading less! This is why patience pays.
+""",
+        "tier": "MEDIUM",
+        "weight": 0.05
+    }
+}
+
+
+def get_metric_explanation(metric_key: str) -> dict:
+    """Get full explanation for a metric"""
+    return METRICS_GUIDE.get(metric_key, {})
+
+
+def print_all_metrics():
+    """Print the complete metrics guide"""
+    print("=" * 80)
+    print("ALPHAFORGE METRICS GUIDE - YOUR PATH TO GOAT STATUS")
+    print("=" * 80)
+    print()
+    
+    for key, info in METRICS_GUIDE.items():
+        print(f"\n{'='*80}")
+        print(f"📊 {info['name'].upper()} [{info['tier']} | Weight: {info['weight']*100:.0f}%]")
+        print(f"{'='*80}")
+        print(f"\n📝 FORMULA:\n{info['formula']}")
+        print(f"\n💡 WHAT IT MEANS:\n{info['what_it_means']}")
+        print(f"\n🎯 HOW IT INFLUENCES YOUR TRADING:\n{info['how_it_influences']}")
+        print(f"\n📖 REAL EXAMPLE:\n{info['real_example']}")
+        print()
+
+
+def get_goat_score(metrics: dict) -> dict:
+    """
+    Calculate a composite GOAT score based on all metrics.
+    This tells you how close you are to elite quant status.
+    """
+    score = 0
+    max_score = 0
+    breakdown = {}
+    
+    weights = {
+        'sharpe_ratio': 0.25,
+        'sortino_ratio': 0.20,
+        'information_coefficient': 0.20,
+        'max_drawdown': 0.15,
+        'calmar_ratio': 0.10,
+        'win_rate': 0.05,
+        'profit_factor': 0.05,
+        'alpha': 0.05,
+        'beta': 0.05,
+        'information_ratio': 0.05,
+        'turnover': 0.05
+    }
+    
+    # Sharpe scoring
+    sharpe = metrics.get('sharpe_ratio', 0)
+    sharpe_score = min(sharpe / 2.0, 1.0) * 100
+    score += sharpe_score * weights['sharpe_ratio']
+    max_score += 100 * weights['sharpe_ratio']
+    breakdown['sharpe'] = {'value': sharpe, 'score': sharpe_score, 'max': 100}
+    
+    # Sortino scoring
+    sortino = metrics.get('sortino_ratio', 0)
+    sortino_score = min(sortino / 2.5, 1.0) * 100
+    score += sortino_score * weights['sortino_ratio']
+    max_score += 100 * weights['sortino_ratio']
+    breakdown['sortino'] = {'value': sortino, 'score': sortino_score, 'max': 100}
+    
+    # IC scoring
+    ic = metrics.get('ic_mean', metrics.get('mean_ic', 0))
+    ic_score = min(ic / 0.10, 1.0) * 100
+    score += ic_score * weights['information_coefficient']
+    max_score += 100 * weights['information_coefficient']
+    breakdown['ic'] = {'value': ic, 'score': ic_score, 'max': 100}
+    
+    # Max DD scoring (inverted - lower is better)
+    mdd = abs(metrics.get('max_drawdown', 0))
+    mdd_score = max(0, (1 - mdd / 0.30)) * 100
+    score += mdd_score * weights['max_drawdown']
+    max_score += 100 * weights['max_drawdown']
+    breakdown['max_drawdown'] = {'value': mdd, 'score': mdd_score, 'max': 100}
+    
+    # Calmar scoring
+    calmar = metrics.get('calmar_ratio', 0)
+    calmar_score = min(calmar / 3.0, 1.0) * 100
+    score += calmar_score * weights['calmar_ratio']
+    max_score += 100 * weights['calmar_ratio']
+    breakdown['calmar'] = {'value': calmar, 'score': calmar_score, 'max': 100}
+    
+    total_score = (score / max_score * 100) if max_score > 0 else 0
+    
+    # Determine tier
+    if total_score >= 85:
+        tier = "LEGENDARY GOAT"
+        emoji = "🐐"
+    elif total_score >= 70:
+        tier = "ELITE QUANT"
+        emoji = "⭐"
+    elif total_score >= 55:
+        tier = "SOLID PRO"
+        emoji = "💪"
+    elif total_score >= 40:
+        tier = "DEVELOPING"
+        emoji = "📈"
+    else:
+        tier = "NEEDS WORK"
+        emoji = "🔧"
+    
+    return {
+        'total_score': total_score,
+        'tier': tier,
+        'emoji': emoji,
+        'breakdown': breakdown
+    }
+
+
+if __name__ == '__main__':
+    print_all_metrics()