Chart Elements

• Lines: Track six skill components—Stock Selection Edge (magnitude of outperformance from security picks), Style Timing Edge (from factor/style shifts), Total Edge (combined), and their Consistency counterparts (frequency of positive results).
• Y-Axis: Z-scores normalized to peer-group percentiles (0 as average/50th percentile; positive = above peers).
• X-Axis: Monthly time series across market cycles, revealing trends and regime shifts.
• Dashed Line: Assets under management (AUM) in levels, overlaid to correlate capacity with skill evolution.

Aapryl’s Skill Methodology

Aapryl isolates true skill by subtracting passive “clones” from manager returns. Static clones replicate long-term factor exposures (e.g., quality, value). Dynamic clones adjust over rolling 36-month windows to capture recent style drifts. Excess return = manager minus dynamic clone (pure stock picks) + dynamic minus static (timing edge).

• Edge Metrics: Omega ratio-inspired—rewards large wins over small losses, scaled vs. peers.
• Consistency Metrics: Batting average of positive excess periods, risk-adjusted for track record length and market volatility.
• Z-Score Normalization: Ranks vs. specific peer universe (here, Global High Quality Blend), enabling cross-manager comparisons.
• Forward Prediction: Aggregates into Aapryl Score, forecasting 3-year top-quartile odds (high scores >60th percentile show ~70% hit rate in backtests).

This returns-based decomposition avoids self-reported biases, focusing on repeatable alpha sources.

Key Insights to Spot

• Skill Drivers: Dominant lines reveal if alpha comes from picks, timing, or balance.
• Persistence: Steady high ranks (>70th percentile) signal process strength; volatility flags regime dependence.
• AUM Correlation: Inflows during skill peaks validate market recognition of edge.

Actionable Uses

• Due Diligence: Confirm narrative (e.g., “quality stock pickers”) matches top-ranked selection lines.
• Monitoring: Watch for sustained drops in core components signaling process erosion.
• Manager Selection: Prioritize stable, high lines in mandate-aligned skills over total return alone.

1. Enter the reporting center by clicking the Reporting Center tab in the portal navigation bar. Click on the (+) symbol in the upper right corner of the screen and select create custom report.
   
2. Name your report by clicking the pencil icon next to the words “Custom Report”
   
3. To add charts and graphs to your custom report, select one of the four options on the left panel (returns, clones, skill, or product details) by either clicking the button or dragging the button into the report area of your choice.
   
4. Once you’ve selected one of the four options, fill in the five required fields and the type of chart you would like then click “process”
   
5. Once your table/graph is created, you are able to edit it by clicking the pencil in the upper right corner of the item.
   
6. You also have the option of duplicating or expanding a chart by selecting these buttons respectively
   
7. Once you’ve added a chart or charts you are able to rearrange them by dragging and dropping them in the desired order.
   
8. Once you are finished editing your report, select either personal so only you can see your report or firm-wide so all your coworkers are able to access the report as well
   
9. You have the option of adding your logo to the report by selecting the “Insert Your Logo” button
   
10. To save the report, select the floppy disk icon in the upper right corner of the screen
    
11. You can export your report via PDF or Excel. Both export option are located in the upper right corner of the page.
    

1. Download the template
   1. Click on “Upload Manager Product(s)”; this will bring you into a three-step uploading process. Aapryl provides a downloadable customized template at the bottom of the screen shown.
      
   2. Once downloaded, you must fill out the product(s) details and the performance history of the product(s). Once you have finished filling out the requirements, you will upload the excel file back into Aapryl.
      
2. Step 2: Visibility.
   1. Select whether you would like to make your analysis personal or firm-wide.
      
3. Step 3: Validate.
   1. This step requires you to validate the manager product data uploaded. When the manager product data has been submitted you can view the product(s) just exactly like any other product on the platform.
   2. If you are receiving a message about the manager product(s) not properly uploading, please click the link down below listed “Download File with Problems Highlighted” and it will show you what boxes need to be filled to continue uploading your Manager Product.
      

After running your Optimization, and viewing the Cyclical Manager Position chart, you may want to add additional funds to your portfolios for diversification across additional economic cycles.

Click the red box within the economic cycle where you would like to add an optimal fund, for which there is currently not coverage.

You will then choose a fund, or funds to add into your Optimization.

The new funds will appear in the Selected Products list within the Edit functionality, where you will then re-run with Optimization with your newly added funds:

When the new results are generated, you will see the new fund(s) that was added, on the Market cycle chart in blue:

Chart Elements

Common Structure (both panels identical layout):

• X-Axis: Time series of periods (e.g., monthly ends from 2017 to 2025), showing evolution across market cycles.
• Y-Axis (Left): Primary metric scale (e.g., Information Ratio from -1.0 to +1.6; positive = skill).
• Y-Axis (Right): Secondary metric scale (e.g., Tracking Error % or Ann. Volatility % from 0% to 16%).
• Lines:
  • Solid Blue: Primary metric (e.g., Information Ratio = excess return / tracking error).
  • Dashed Blue: Secondary metric (e.g., Tracking Error % = annualized std. dev. of excess returns).
• Dropdown Selections:
  • Top Dropdown (e.g., “Information Ratio”): Choose primary metric—Information Ratio, Tracking Error, Ann. Volatility.
  • Bottom Dropdown (e.g., “Tracking Error %”): Pair with secondary—Tracking Error, Ann. Volatility, etc.
  • Rolling Period: Fixed (e.g., 36 months) smooths noise; reveals trends without short-term outliers.

Panel Examples:

• Top Panel: Information Ratio (left) vs. Tracking Error (right)—IR peaks when excess is high relative to risk.
• Bottom Panel: Same pairing, confirming consistency across views.

How Metrics Are Calculated

All vs. benchmark (e.g., MSCI World), annualized over rolling windows:

• Information Ratio (IR): Excess return / Tracking Error. >0.5 good; >1.0 excellent; negative = value destruction.
• Tracking Error %: Std. dev. of monthly excess returns (active risk); 4-8% typical for equities.
• Volatility %: Std. dev. of total returns (absolute risk).
  These capture both reward (numerator) and risk denominators, spotting if high returns come from skill or volatility.

Key Insights to Spot

• IR Stability: Consistent >0.5 line signals repeatable risk-adjusted skill; sharp drops flag regime issues.
• Risk/Return Trade-off: Rising tracking error with flat IR means more risk for same reward—watch for spikes.
• Volatility Patterns: High vol periods correlating with low IR indicate poor navigation.
• Dropdown Power: Switch to IR vs. Volatility to see if absolute risk drives issues; Tracking Error vs. Volatility isolates benchmark deviation.

Actionable Uses

• Consistency Gauge: Favor managers with stable >0.5 IR through cycles.
• Risk Budgeting: Cap allocations where tracking error >10% unless IR compensates.
• Regime Analysis: Zoom on downturns—does IR hold or collapse?
• Comparisons: Standardize dropdowns (e.g., 36-mo IR vs. TE) across managers for screening.

Chart Elements

• The center pie shows benchmark factor breakdown by percentage (e.g., 46% Value blue, 25% Economic Sensitivity gray, 25% Growth yellow, 19% Quality green).
• The X-axis labels identify factors: Economic Sensitivity (gray), Growth (yellow), Quality (green), Value (blue).
• The toggle buttons allow Static (full history) vs. Dynamic (most recent 36 months) clone calculation.
• The radio buttons switch between Distinct and Factor decomposition modes.
• Cap Size and Region toggles enable additional breakdowns.
• Benchmark selector shows current selection with period dropdown (e.g., most recent 36 months).
• Data as-of notes recency (e.g., 12/2025).

How It Works

Aapryl builds static clones from inception-period factor loadings and dynamic clones from rolling 36-month windows. Available factors (depending on benchmark): Value (low P/E, P/B), Core (neither value/growth), Growth (high growth rates, P/E, P/B), Defensive (stability via low earnings variability, high ROA, low leverage), Economic Sensitivity (cyclical based on earnings variability, ROA, leverage), Momentum (high price momentum), Quality (high ROA, low leverage, earnings stability), Yield (high dividend yields), Low Volatility (lowest std. dev. or beta). Distinct aggregates similar factors; Factor shows granular split.

Key Insights to Spot

Dominant slice reveals primary tilt (e.g., 46% Value). Dynamic vs. static divergence signals evolving exposures. High Quality or Low Volatility % explains defensive behavior. Economic Sensitivity dominance flags cyclical bets. Factor availability varies by benchmark universe.

Actionable Uses

Match manager clones to benchmark factors for style fit. Screen benchmarks aligning with portfolio mandate. Probe factor mismatches in DD meetings. Monitor dynamic shifts for regime changes. Compare across universes for allocation decisions.

This Aapryl style box tracks the manager’s style evolution from Oct 2014-12/2025. X-axis classifies from Value (left) to Growth (right); Y-axis from Cyclical/Aggressive (bottom) to Defensive (top). Larger/darker circles indicate more recent periods, revealing drifts.

Chart Elements

• X-axis labels: Low Value (left), High Value, Relative Value, GARP, Aggressive Growth, High Growth (right).
• Y-axis labels: Low Quality (bottom), Relative Quality, High Quality Blend (top).
• Blue circles: Manager positions (e.g., GQG Partners LLC – GQG Partners Global Equity); size grows with recency.
• Yellow square/region: Aapryl peer group (High Quality Blend).
• Red circles: MSCI World peer benchmark positions.
• Toggle: Static (full history, selected) vs. Dynamic.
• Period range: Oct 2014-12/2025.
• Legend: Manager (blue), MSCI World peer (red), Aapryl peer group (yellow).

How It Works

Aapryl positions managers via factor clone exposures (static full history or dynamic). X-axis interpolates Value (low P/B, P/E) to Growth (high growth); Y-axis Cyclical (Economic Sensitivity) to Defensive (stability). Segregated boxes classify (9 styles: Low Value/Low Quality to High Growth/High Quality). Circle size scales with time proximity (largest = most recent), plotting trajectory across track record.

Key Insights to Spot

Stable clustering in High Quality Blend signals consistent style. Rightward drift shows growth tilt evolution. Size progression reveals recent positioning (e.g., large blue in GARP/High Quality). Peer comparison: Manager vs. MSCI (red) or Aapryl group (yellow). Box outliers flag aggressive bets.

Actionable Uses

Validate stated style vs. trajectory. Spot drifts for process questions. Compare to peers/benchmarks for fit. Screen stable High Quality managers. Monitor recent large circles for current alignment.