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Glide-up score
Advanced multi-factor statistical analysis of portfolio growth quality, consistency, and long-term performance stability
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Understanding the Glide-up score

The Glide-up score is our most advanced portfolio performance metric, evaluating investment fund quality through multiple dimensions. It identifies funds with steady, consistent growth patterns and separates them from those with volatile or erratic returns.
Unlike simple return metrics, our Glide-up score rewards consistency, penalizes severe drawdowns, and values proven long-term track records.
Traditional performance metrics often fail to capture the quality of returns. Two funds with identical average returns can deliver vastly different investor experiences - one with smooth, steady growth and another with wild swings and severe losses. Our Glide-up score addresses this gap by evaluating how returns are achieved, not just the final numbers.

Four key performance components

Growth Score
Highest Priority
Rewards positive upward trajectory using statistical regression slope analysis
Linearity Score
High Priority
Measures consistency of growth patterns and deviation from long-term trend line
Drawdown Score
Medium Priority
Penalizes severe portfolio declines and measures volatility control
History Score
Lower Priority
Values longer track records and proven long-term investment performance

Why smooth growth matters for your investments

Risk-adjusted returns

High Glide-up score funds show consistent growth patterns without excessive volatility in historical data

Investment predictability

Consistent growth patterns help investors plan their financial future and set realistic return expectations

Quality investment signal

Identifies fund managers with sustainable investment strategies versus lucky short-term market winners

How the glide-up score works

Our Glide-up score uses advanced statistical methods and regression analysis to evaluate portfolio performance quality:
Statistical analysis
• Ordinary Least Squares (OLS) regression on equity curves
• Logarithmic transformation for better growth measurement
• Root Mean Squared Error (RMSE) for linearity assessment
• Peak-to-trough drawdown calculation
Weighted combination
• Growth score: Sigmoid function of regression slope
• Linearity score: Inverse relationship with RMSE
• Drawdown score: Penalty based on maximum drawdown
• History score: Dynamic baseline from median track length
These components are combined using a weighted geometric mean formula, with positive growth trajectory being the most influential factor, followed by growth consistency and volatility control, with track record length providing supporting influence.
The result is a standardized 0-100 score where higher values indicate smoother, more consistent portfolio growth with proven long-term performance.
Scores above 70 typically show smooth upward trajectories and minimal drawdowns in historical performance. Scores between 50-70 suggest solid performers with reasonable consistency. Lower scores may indicate either volatile growth patterns, significant drawdowns, limited track records, or negative growth trends.
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