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QuantSchool: Diversification by forecast parameters

Beyond Asset Classes: Parameter-Based Diversification

QuantWave's multi-dimensional forecasting system enables sophisticated diversification across signal characteristics, not just traditional asset classes.

Key Diversification Dimensions

1. Time Horizon Diversification

• Short-Term (1-5 days): 20-30% of portfolio
• Medium-Term (1-4 weeks): 40-50% of portfolio
• Long-Term (1-6 months): 20-30% of portfolio

2. Probability Distribution

Confidence Band	Suggested Weight	Position Sizing
High (75%+)	40-50%	Full size
Medium (60-74%)	30-40%	Reduced size
Low (50-59%)	10-20%	Minimum size

Advanced Parameter Diversification

1. Strategy Type Mix

• Trend Following: 40-60%
• Mean Reversion: 20-30%
• Event-Driven: 10-20%
• Arbitrage: 0-10%

2. Risk Profile Balance

• Low Risk: Core positions (50-60%)
• Medium Risk: Strategic positions (30-40%)
• High Risk: Opportunistic (10-20%)

QuantWave Diversification Tools

1. Parameter Matrix

• Visual mapping of forecast characteristics
• Identifies concentration risks
• Suggests balancing opportunities

2. Correlation Analyzer

• Measures strategy interdependence
• Tests portfolio stress scenarios
• Optimizes parameter combinations

Implementation Framework

The 5-Step Parameter Balance

1. Analyze current parameter distribution
2. Identify over-concentrated dimensions
3. Select complementary forecasts
4. Adjust position sizing accordingly
5. Monitor correlation effects

Common Mistakes

• Overloading one probability band
• Ignoring strategy correlations
• Mismatching time horizons
• Over-optimizing parameter sets

Performance Metrics

• Parameter contribution analysis
• Strategy correlation impact
• Drawdown by parameter group

QuantWave's parameter-based diversification provides a sophisticated approach to building robust portfolios. By systematically balancing across multiple forecast dimensions, investors can achieve more stable returns regardless of market conditions.