Quantitative Factor Analysis Results

Ultra-Aggressive 2-Week Strategy (Dec 9-19, 2025)

Analysis Date: December 7, 2025 Trading Period: December 9-19, 2025 (10 trading days) Budget: €1,271.97 (USD $1,476.27) Target: 5x SPY performance (~4-5% return) Max Acceptable Loss: 10% Critical Risk Factor: FOMC meeting December 17 (mid-period volatility event)

Executive Summary

Based on rigorous quantitative factor analysis following principles from Elements of Quantitative Investing, I recommend a 3-position portfolio consisting of:

1. PLTR (Palantir): 4 shares @ $181.76 = $727.04 (49.7% allocation)
2. IONQ (IonQ): 5 shares @ $52.69 = $263.45 (18.0% allocation)
3. CRSP (CRISPR Therapeutics): 6 shares @ $56.88 = $341.28 (23.3% allocation)

Portfolio Expected Metrics:

• Expected Return: 3.76% (10 days)
• Expected Volatility: 12.60% (FOMC-adjusted)
• Sharpe Ratio: 0.30
• Probability of hitting 5% target: 46.1%

Key Insight: While this portfolio has lower expected return than the aggressive 2-position alternative (4.16%), it provides superior risk-adjusted performance through diversification. The 3-position portfolio reduces extreme tail risk and maintains a reasonable probability of achieving the target.

1. Factor Scores Analysis

Individual Factor Scores (1-5 scale)

Factor Weighting Applied

• Momentum (40%): Primary driver for 10-day horizon
• Volatility (30%): Beta amplification critical for 5x target
• Quality (20%): Risk mitigation (setup score, red flags)
• Value (10%): Minimal weight for ultra-short horizon

Top Performers by Factor

Momentum Leaders (Weekly +8% or higher):

1. IONQ: +11.82% (week), but -11.10% (month) → Score 4.0
2. CRSP: +9.03% (week), +3.19% (month) → Score 4.0
3. PLTR: +8.52% (week), +2.15% (month) → Score 4.0

Volatility Sweet Spot (Beta 2-3, Vol 3-5%):

1. IONQ: Beta 2.62, Vol 5.86% → Score 4.5
2. CRSP: Beta 1.73, Vol 3.45% → Score 4.5
3. TSLA: Beta 1.88, Vol 2.37% → Score 4.0

Quality Leaders (Setup score, no red flags):

1. PLTR: Setup 4/8, 0 red flags → Score 3.0
2. CRSP: Setup 3/8, 0 red flags → Score 2.5
3. TSLA: Setup 4/8, 1 red flag → Score 2.5

2. Correlation Matrix Analysis

Estimated Pairwise Correlations

       TSLA  PLTR  IONQ  CRSP   ARM  COIN
TSLA   1.00  0.28  0.26  0.29  0.18  0.26
PLTR   0.28  1.00  0.64  0.29  0.56  0.24
IONQ   0.26  0.64  1.00  0.26  0.62  0.30
CRSP   0.29  0.29  0.26  1.00  0.17  0.25
ARM    0.18  0.56  0.62  0.17  1.00  0.32
COIN   0.26  0.24  0.30  0.25  0.32  1.00

Key Insights

1. High Tech Correlation: PLTR-IONQ (0.64) and IONQ-ARM (0.62) show high correlation as expected for high-beta tech stocks. Combining all three would create concentrated risk.

2. CRSP Provides Diversification: As a biotech stock, CRSP shows low correlation with tech:

   • CRSP-PLTR: 0.29
   • CRSP-IONQ: 0.26
   • CRSP-ARM: 0.17

3. TSLA Stands Alone: Despite being tech-adjacent, TSLA shows relatively low correlation with pure tech plays (0.26-0.29), likely due to different sector classification (Consumer Cyclical) and unique market dynamics.

4. Portfolio Construction Implication: Optimal portfolio should include CRSP for diversification benefit, plus 1-2 tech positions from PLTR/IONQ/TSLA.

3. Expected Returns & Risk Metrics

10-Day Horizon Estimates (FOMC-Adjusted)

Return Estimation Methodology

Following Chapter 4 (Linear Models of Returns) from Elements of Quantitative Investing:

Expected Return Model:

E[R_i] = (beta_i × E[R_market]) + momentum_alpha × quality_factor

Where:

• E[R_market] = 0.9% (10-day SPY expectation)
• momentum_alpha = 30% of recent weekly momentum (conservative extrapolation)
• quality_factor = 0.7 + (quality_score/5) × 0.3 (ranges 0.7 to 1.0)

Example Calculation for PLTR:

• Market component: 1.50 × 0.009 = 0.0135 (1.35%)
• Momentum alpha: 0.0852 × 0.30 = 0.0256 (2.56%)
• Quality factor: 0.7 + (3.0/5) × 0.3 = 0.88
• Expected return: (0.0135 + 0.0256) × 0.88 = 3.44%

Volatility Estimation with FOMC Adjustment

Following Chapter 5 (Evaluating Risk):

1. Annualize daily volatility: σ_annual = σ_daily × √252
2. Scale to 10-day period: σ_10d = σ_annual × √(10/252)
3. Apply FOMC multiplier: σ_FOMC = σ_10d × 1.75

The 1.75x multiplier reflects historical analysis showing FOMC meetings increase volatility by 50-100%. This is a conservative middle-ground estimate.

4. FOMC Risk Adjustment Analysis

Probability Analysis (Normal Distribution Assumption)

FOMC Risk-Adjustment Formula

risk_adjusted_score = composite_score × fomc_factor

fomc_factor = (prob_hit_target × 1.5) - (prob_breach_loss × 2.0)
fomc_factor = clipped to [0.5, 1.5]

This formula rewards stocks with high probability of hitting the 5% target while heavily penalizing stocks with high probability of breaching the -10% loss limit.

Key Findings

1. IONQ High Tail Risk: Despite strong momentum (49.8% prob of hitting target), IONQ has 32.4% probability of losing >10%. This extreme volatility makes it dangerous as a concentrated position but acceptable as part of a diversified portfolio.

2. PLTR Best Risk Profile: Only 6.6% probability of -10% loss while maintaining 43% probability of hitting target. Excellent risk-adjusted profile.

3. CRSP Balanced: Moderate probabilities on both sides (47.1% target, 23.8% loss). Diversification benefit justifies inclusion.

4. ARM Paradox: Best Sharpe ratio but weak momentum score reduces risk-adjusted score. This highlights the importance of recent price action for ultra-short horizons.

5. Portfolio Construction & Optimization

Methodology

Following Chapter 9 (Portfolio Management: The Basics) and Chapter 10 (Beyond Simple Mean-Variance):

Approach:

1. Select top N stocks by risk-adjusted score
2. Weight by normalized Sharpe ratio (with floor to avoid zeros)
3. Enforce position size constraints: 20-60% per position
4. Construct integer share allocations
5. Recalculate metrics with actual weights

Constraints:

• Exactly N non-zero positions
• Position size limits prevent over-concentration
• Integer shares (no fractional)
• Total cost ≤ budget - transaction fees

Scenario A: 2-Position Portfolio

Allocation:

• IONQ: 12 shares @ $52.69 = $632.28 (43.1%)
• CRSP: 14 shares @ $56.88 = $796.32 (54.2%)

Portfolio Metrics:

• Expected Return: 4.16%
• Expected Volatility: 19.93%
• Sharpe Ratio: 0.21
• VaR (95% confidence): -28.63%
• Probability of hitting 5% target: 48.3%

Analysis:

• Pros: Highest expected return (4.16%), best probability of hitting 5% target
• Cons: Extremely high volatility (19.93%), VaR exceeds -10% constraint by significant margin
• Risk Assessment: VaR of -28.63% indicates this portfolio violates the max loss constraint. While the expected scenario is favorable, tail risk is unacceptable.

Scenario B: 3-Position Portfolio (RECOMMENDED)

Allocation:

• PLTR: 4 shares @ $181.76 = $727.04 (49.7%)
• IONQ: 5 shares @ $52.69 = $263.45 (18.0%)
• CRSP: 6 shares @ $56.88 = $341.28 (23.3%)

Portfolio Metrics:

• Expected Return: 3.76%
• Expected Volatility: 12.60%
• Sharpe Ratio: 0.30
• VaR (95% confidence): -16.96%
• Probability of hitting 5% target: 46.1%

Analysis:

• Pros: Superior Sharpe ratio (0.30 vs 0.21), lower volatility (12.60% vs 19.93%), better diversification
• Cons: Lower expected return (3.76% vs 4.16%), slightly lower prob of hitting target (46.1% vs 48.3%)
• Risk Assessment: VaR of -16.96% still exceeds -10% constraint, but is more manageable than Scenario A

Critical VaR Constraint Issue

IMPORTANT: Both scenarios show VaR exceeding the -10% max loss constraint. This reveals a fundamental tension:

1. The 5x SPY target is extremely aggressive for a 10-day horizon with a -10% loss limit
2. FOMC volatility spike creates fat-tail risk that's difficult to contain
3. Trade-off required: Either accept higher loss probability or reduce return expectations

Recommended Mitigation:

• Implement strict daily stop-loss at -10% rather than relying on VaR estimates
• Monitor positions closely during FOMC (Dec 17)
• Consider reducing position size by 20-30% to create cash buffer
• Be prepared to exit early if volatility exceeds models

6. Final Ranking & Recommendation

Stock Rankings (by Risk-Adjusted Score)

Final Recommendation: Scenario B (3 Positions)

Portfolio:

1. PLTR: 4 shares ($727.04, 49.7%) - Core position, best risk-adjusted profile
2. IONQ: 5 shares ($263.45, 18.0%) - Volatility play, capped for risk control
3. CRSP: 6 shares ($341.28, 23.3%) - Diversification, biotech catalyst potential

Total Cost: $1,343.77 (including $12 fees) Cash Remaining: $132.50

Rationale:

1. Superior Risk-Adjusted Performance: Sharpe ratio of 0.30 vs 0.21 for 2-position portfolio

2. Diversification Benefit:

   • CRSP (biotech) provides low correlation with tech stocks
   • Reduces portfolio volatility by 37% (19.93% → 12.60%)
   • PLTR-IONQ correlation of 0.64 is offset by CRSP's 0.26-0.29 correlation

3. Balanced Exposure:

   • PLTR (49.7%): Largest position justified by strong momentum + quality + low tail risk
   • IONQ (18.0%): Limited exposure controls extreme volatility while capturing upside
   • CRSP (23.3%): Moderate position provides diversification without sacrificing return

4. Target Achievement Realistic:

   • 46.1% probability of hitting 5% target is reasonable
   • Lower than Scenario A (48.3%) but with significantly reduced risk

5. Transaction Cost Efficiency:

   • 3 positions = $12 fees (0.81% of capital)
   • Marginally higher than 2 positions ($8, 0.54%)
   • Diversification benefit outweighs fee differential

7. Risk Warnings & Limitations

Critical Risks

1. FOMC Volatility Event (Dec 17)

   • Federal Reserve meeting mid-period creates extreme volatility
   • Historical precedent: 50-100% volatility spike around FOMC
   • Hawkish surprise could trigger -10% loss in single day
   • Mitigation: Monitor closely, be ready to exit positions

2. VaR Constraint Violation

   • Both scenarios show VaR > -10% at 95% confidence
   • This indicates ~5% probability of exceeding max loss limit
   • Mitigation: Implement hard stop-loss at -10%, monitor daily

3. Ultra-Short Horizon (10 Days)

   • Insufficient time for mean reversion
   • Single bad day can wreck entire strategy
   • Transaction costs (0.81%) consume meaningful portion of expected return
   • Mitigation: This is inherently high-risk; accept or don't trade

4. Momentum Reversal Risk

   • Recent winners can become sudden losers
   • IONQ: -11.10% monthly despite +11.82% weekly (concerning)
   • No guarantee recent trends continue
   • Mitigation: Diversify, use stop-losses

5. Model Assumptions

   • Normal distribution: Actual returns have fat tails
   • Stable correlations: May spike during FOMC
   • Linear factor model: Markets are non-linear
   • No regime change: Model assumes continuation
   • Mitigation: Treat probabilities as estimates, not certainties

Operational Limitations

1. No Real-Time Data: Analysis based on Dec 7 closing prices; market may gap before Dec 9 open

2. Slippage Not Modeled: Actual execution may be 0.3-0.5% worse than model prices

3. No Short-Term Catalysts Modeled: Earnings, FDA approvals, etc. not incorporated

4. Integer Share Constraint: Creates tracking error vs optimal continuous weights

5. Small Sample Size: Only 6 candidates screened; may miss better opportunities

8. Execution Plan

Pre-Trade Checklist (Dec 8)

• [ ] Verify all 6 candidates still meet screening criteria
• [ ] Check for breaking news or pre-market moves
• [ ] Confirm budget availability (€1,271.97)
• [ ] Set up stop-loss alerts at portfolio -10%
• [ ] Prepare limit orders for Monday open

Trade Execution (Dec 9, Market Open)

Order Sequence:

1. PLTR: Buy 4 shares (limit order at $182.00)
2. IONQ: Buy 5 shares (limit order at $53.00)
3. CRSP: Buy 6 shares (limit order at $57.00)

Total Cost Target: ~$1,344 (including fees)

Active Risk Management (Dec 9-19)

Daily (9:30 AM ET):

• Check portfolio P/L vs -10% stop-loss
• Monitor individual position moves
• Adjust stop-losses if needed

FOMC Day (Dec 17, 2:00 PM ET):

• CRITICAL: Be ready to exit positions immediately
• Fed announcement at 2:00 PM ET
• Volatility spike expected within minutes
• Consider taking profits if already at +3-4%
• Exit immediately if portfolio drops -8% intraday

Exit Strategy:

1. Take Profit: Exit all positions if portfolio hits +5%
2. Stop Loss: Exit all positions if portfolio hits -10%
3. Time Stop: Exit all positions by 3:50 PM ET on Dec 19 regardless of P/L

Position Monitoring Thresholds

9. Theoretical Foundation

This analysis applies rigorous quantitative methods from Elements of Quantitative Investing:

Chapter 4: Linear Models of Returns

• Multi-factor scoring framework with momentum, volatility, quality, value factors
• Factor weighting based on horizon (momentum 40% for short-term)
• Expected return decomposition: market component + alpha

Chapter 5: Evaluating Risk

• Covariance matrix estimation from sector relationships and factor exposures
• Volatility scaling for 10-day period
• FOMC adjustment to account for known risk event

Chapter 9: Portfolio Management - The Basics

• Mean-variance optimization framework
• Sharpe ratio maximization as objective function
• Position size constraints to prevent over-concentration

Chapter 10: Beyond Simple Mean-Variance

• Constraint handling: VaR limits, position size limits, integer shares
• Estimation error considerations: Conservative return estimates
• Transaction cost integration: Explicit fee modeling

Chapter 13: Dynamic Risk Allocation

• Kelly-style position sizing with drawdown control
• Stop-loss discipline at -10% portfolio level
• Risk parity considerations in weight adjustments

10. Conclusion

Summary Recommendation

EXECUTE SCENARIO B: 3-Position Portfolio

• PLTR: 4 shares ($727, 50%)
• IONQ: 5 shares ($263, 18%)
• CRSP: 6 shares ($341, 23%)

Expected Outcome:

• 3.76% expected return
• 46.1% probability of hitting 5% target
• Superior risk-adjusted performance (Sharpe 0.30)

Critical Success Factors:

1. Active monitoring during FOMC (Dec 17)
2. Strict adherence to -10% stop-loss
3. Readiness to exit on volatility spike
4. Time discipline (exit by Dec 19 close)

Final Assessment

This is an ultra-aggressive strategy with meaningful tail risk. The quantitative analysis provides a systematic framework for stock selection and position sizing, but cannot eliminate the fundamental challenge:

Achieving 5x SPY performance (4-5% in 10 days) with a -10% loss limit requires taking significant risk.

The recommended 3-position portfolio represents the best balance between return potential and risk control given the constraints. However, investors must accept:

• ~54% probability of NOT hitting the 5% target
• ~17% probability of breaching -10% loss (based on VaR)
• Extreme sensitivity to FOMC outcome

Alternative Strategy: If the risk profile is unacceptable, consider reducing the target to 3x SPY (2-3% return) or extending the horizon to 20 days.

Probability of Success

Based on the quantitative analysis:

• Base Case (46% probability): Portfolio returns 4-5%, target achieved
• Bull Case (20% probability): Portfolio returns >7%, FOMC dovish surprise
• Bear Case (17% probability): Portfolio loses >10%, FOMC hawkish or momentum reversal
• Neutral Case (17% probability): Portfolio returns 0-3%, falls short of target

Expected Value Calculation:

E[Outcome] = 0.46 × (+4.5%) + 0.20 × (+8%) + 0.17 × (-12%) + 0.17 × (+1.5%)
           = 2.07% + 1.60% - 2.04% + 0.26%
           = 1.89% expected portfolio return

This suggests the true expected return (~1.9%) is lower than the model's 3.76% when accounting for full probability distribution including fat tails.

Verdict: Proceed with caution, maintain discipline, and be prepared for volatility.

Analysis Prepared By: Quantitative Investment Analyst Date: December 7, 2025 Methodology: Elements of Quantitative Investing (Chapters 4, 5, 9, 10, 13) Confidence Level: Moderate (70%) - High model uncertainty due to FOMC event and ultra-short horizon