Chart Elements

The layout uses simple grouped bars aligned to specific stress events on the X-axis, with the Y-axis scaling cumulative returns from roughly -50% to +50% to capture typical drawdown ranges. Every component serves a clear purpose:

• Stress Events (X-Axis, left to right): Factory presets include European Debt (04/2010-07/2011) for the sovereign crisis period, Flash Crash (06/2010) for the sudden volatility spike, March 2020 for the initial pandemic flash decline, COVID-19 (01/2020-03/2020) for the full early pandemic drop, and Great Financial Crisis (10/2007-02/2009) for the GFC meltdown. You create custom periods using the wizard when selecting managers—simply input start and end dates during manager setup to test tailored scenarios like rate hikes or sector shocks.
• Y-Axis (Return %): The total cumulative return from the period’s open to close. Negative numbers show the drawdown magnitude (e.g., -42% means a 42% peak-to-trough loss); positive values are uncommon but indicate relative outperformance or quick recovery.
• Bar Pairs (one black and one blue per event):
  • Black Bars: The manager’s actual returns during that window (e.g., -7.6% in the European Debt crisis, showing limited damage).
  • Blue Bars: The benchmark’s returns for the same exact period (e.g., MSCI World at -21.1% in March 2020, a much steeper fall).
• Legend:
  • Black: Selected manager (e.g., GQG Partners LLC – GQG Partners Global Equity).
  • Blue: Benchmark (MSCI World).
• Customization Path: Access via the manager selection wizard—define periods on-the-fly without separate platform tools.

The chart pulls data from inception (e.g., 10/2014 to 12/2025), only plotting events overlapping the track record.

How Stress Tests Are Calculated

All figures rely on the clone returns framework to ensure apples-to-apples stress analysis:

• Manager Actual: Straight cumulative return of the portfolio over the defined window.
• Benchmark: Identical calculation for the index.
• Clone Role (underlying attribution): Static and dynamic clones dissect if the manager’s style (e.g., high-quality stocks holding up in recessions) or skill (e.g., nimble selection/timing) explained relative strength. Windows are peak-to-trough standardized for fairness, and results aren’t annualized given the short, intense nature of crises.
  When you create custom periods in the wizard, the same rigorous clone methodology applies automatically.

Key Insights to Spot

Focus on the black bar versus blue bar height in each event pair to uncover patterns:

• Relative Protection: A black bar noticeably less negative than the blue one (e.g., manager -4% vs. benchmark -21%) demonstrates superior downside management—crucial for real-world portfolios.
• Pattern Across Crises: Consistent black-bar advantage in multiple events (e.g., 4 out of 5) points to a repeatable defensive process, not luck.
• Style or Skill Driver: If the manager significantly outperformed, cross-reference clones (available in detailed views)—was it passive factor resilience or active decisions?
• Custom Scenario Power: Your wizard-defined periods (e.g., 2022 bear market) reveal current relevance beyond historical defaults.
• Amplification Effect: Crises magnify small edges seen in normal times, validating or debunking skill claims.

Actionable Uses

This chart fits seamlessly into risk assessment and decision-making:

• Resilience Prioritization: Favor managers where black bars are shallower than blue across most events, especially customs matching your risk views.
• Due Diligence Prep: Reference specific bars like “Your -8% in COVID beat the benchmark’s -42%—walk us through the positioning.”
• Portfolio Stress Modeling: Aggregate top black-bar performers to simulate blended crisis returns.
• Custom Testing: Use the manager selection wizard for “what-if” periods like geopolitical flares, ensuring hires withstand your scenarios.
• Capacity Correlation: Combine with AUM charts—if strong black bars persist at high assets, the process scales through turmoil.

By enabling wizard-based custom periods, this chart evolves from historical review to forward-looking stress validation.

Chart Elements

The chart uses stacked horizontal bars for each time period, with the Y-axis showing annualized skill return percentages (e.g., -20% to +10%) and the X-axis listing horizons. Here’s exactly what comprises each element:

• Time Horizons (X-Axis, left to right): QTD (shortest, most volatile), CYTD, 1YR, 3YR, 5YR, ITD (longest, most reliable). Parentheticals note peer count per period (e.g., QTD: 246 funds).
• Y-Axis (Ann Skill Return %): Annualized return specifically attributed to manager skill (peer-adjusted alpha from decomposition: stock selection + style timing, after clones). Positive = skill generated excess; negative = skill detracted. Zero line marks peer average.
• Stacked Bars (color-coded peer percentiles, bottom to top):
  • Dark Brown (75th-90th Percentile – Worst): Bottom 25% of peers (weakest skill).
  • Light Brown (50th-75th Percentile): Middle 25% (below average).
  • Yellow (50th-25th Percentile): Middle 25% (above average).
  • Green (Top 10th-25th Percentile – Best): Strong performers.
  • Blue (Top 10% – Best): Elite top decile.
• Orange Horizontal Line: Your manager’s exact skill return for that period (e.g., 2.78% in 3YR). Its height and stack position show rank.
• Universe Context: Data as-of (e.g., 12/2025), peer group name.

How Skill Return Is Calculated

The “Ann Skill Return %” on the Y-axis represents peer-adjusted alpha—annualized excess return from skill components only:

• Skill Return = (Manager – Static Clone) for long-term + timing adjustment, ranked and normalized vs. peers.
• Positive values mean skill beat peer average; derived from decomposition excluding benchmark/style effects.
  Bars show full peer distribution; orange line overlays manager’s contribution.

Key Insights to Spot

Scan the orange line’s position within stacks across periods:

• Consistent Top Placement: Orange consistently in blue/green (top 25%) signals persistent skill advantage.
• Rank Evolution: Deterioration from QTD green to ITD brown warns of fading edge.
• Peer Spread: Tall stacks indicate variable skill universe; short stacks mean homogenization.
• Negative Skill: Orange below zero across horizons flags systematic underperformance.
• Fund Count Changes: Shrinking peers (e.g., 84 ITD) may reflect survivorship—interpret cautiously.

Actionable Uses

Leverage this for efficient relative evaluation:

• Rank Snapshot: All orange lines in top 25%? High conviction for shortlisting.
• Persistence Check: Strong short-term but weak ITD? Probe for capacity or process shifts.
• Universe Validation: Large consistent fund counts ensure robust percentiles.
• Comparisons: Align with scatter plot—top stack matches top-right quadrant.
• Decision Triggers: Bottom-half ITD orange line + negative skill = deprioritize or investigate.

Chart Elements

The chart uses a standard scatter plot format with these core components:

• X-Axis (Style Timing Skill %): This measures the manager’s peer-relative performance in tactically rotating between factors or styles, such as shifting from value to growth at the right times. Values range from negative (underperformed peers) to positive (outperformed peers), for example from -7% to +5%. A dot further to the right indicates stronger timing skill compared to the peer group.
• Y-Axis (Stock Selection Skill %): This captures peer-relative outperformance from individual security picks after adjusting for style. Positive values (e.g., up to +10%) mean the manager selected stocks that beat what their dynamic style clone would predict; negative values (down to -20%) show underperformance in picks.
• Data Points:
  • Blue Dots: Each represents one peer fund in the universe. The cloud of dots shows the full distribution—dense clusters indicate common skill levels, while outliers highlight exceptional or poor performers.
  • Orange Dot: Your selected manager. Its position relative to the blue cloud tells the story of competitive standing.
• Zero Crosshairs: Vertical and horizontal lines at 0% divide the chart into four quadrants. The top-right quadrant is ideal (strong in both skills), while bottom-left signals weakness across the board.
• Labels and Context: The title notes the universe size (e.g., 245 funds), data as-of date (e.g., 12/2025), and current period (e.g., 3 Year).
• Interactive Features:
  • Hover over blue dots: A tooltip bubble appears with the peer fund’s name and exact skill values, letting you quickly identify competitors.
  • Double-click any dot: Opens the full Aapryl Dashboard in a new browser tab with that specific manager (peer or your own) pre-selected for deeper analysis.
• Period Dropdown: Switch between QTD (shortest, most volatile), 1YR, 3YR, or 5YR (longest, tests durability). Longer periods smooth out noise and better reveal sustainable skill.

How Skill Components Are Calculated

Both axes show annualized, peer-relative z-scores derived from Aapryl’s return decomposition model:

• Style Timing Skill: The difference between the dynamic clone (recent 36-month style) and static clone (fixed inception style), ranked against all peers in the universe. It isolates value added from factor rotations.
• Stock Selection Skill: Manager returns minus dynamic clone returns, ranked vs. peers. This pure residual measures idiosyncratic security-level decisions.
  These are normalized so the peer average sits near zero, making positioning intuitive.

Key Insights to Spot

Look for these patterns to draw meaningful conclusions:

• Quadrant Dominance: An orange dot in the top-right quadrant means your manager beats most peers on both dimensions— a strong buy signal. Conversely, bottom-left placement warrants caution.
• Relative Outlier Status: If the orange dot sits far above or right of the blue cloud, the manager has a differentiated edge. Check if it’s consistently there across time horizons.
• Peer Dispersion: A tight cluster of blue dots suggests commoditized skill levels in the universe (harder to stand out). Wide spreads create more opportunities for alpha.
• Changes Over Time: Toggle from QTD to 5YR— if the orange dot migrates toward top-right in longer periods, it indicates improving or persistent skill rather than luck.
• Universe Robustness: With 245 funds, rankings are statistically meaningful; smaller universes require more scrutiny.

Actionable Uses

This chart shines in comparative and due diligence workflows:

• Competitive Scouting: Hover over top-right blue dots to note rival names, then double-click to open their Dashboards and compare processes head-to-head.
• Conviction Building: A stable top-right position across 3YR and 5YR horizons supports allocation decisions, especially with positive peer-adjusted alpha from other charts.
• Skill Gap Analysis: If your manager skews left (weak timing), ask targeted questions like “How do you handle factor rotations?” during meetings.
• Persistence Screening: Use the dropdown to filter managers who maintain strong quadrants over multiple periods, avoiding one-hit wonders.
• Quick Navigation: Double-click your own orange dot anytime for a full Dashboard view, or explore peers without leaving the analysis flow.

By combining hover details, double-click navigation, and time toggles, this chart turns peer benchmarking into an efficient, interactive tool for manager selection.

Table Elements

Column Headers (Time Horizons, left to right):

• Peer Group: Specific Aapryl universe (e.g., Global Large High Quality Blend).
• QTD, CYTD, 1YR, 3YR, 5YR, ITD: Return periods—Quarter-To-Date (shortest), Calendar YTD, 1/3/5 Years, Inception-To-Date (longest). All annualized where applicable.

Row Breakdown:

• Manager Composite: The manager’s total return for each period (e.g., 0.84% CYTD).
• Static Clone (Long-Term Style Adj Bench): Passive long-term style replication return (e.g., 2.93% QTD)—what holding fixed factors yields.
• Benchmark (e.g., MSCI World): Broad index return (e.g., 3.12% QTD).
• Manager vs Benchmark: Excess return (Manager – Benchmark; e.g., -3.17% QTD).
• Style Effect (Clone Bench): Factor tilts’ contribution (e.g., -0.19% QTD).
• Peer Adjusted Alpha (Manager – Static Clone): Style-neutral skill excess (e.g., -2.99% QTD).
• Peer Quartile Rank (1 best, 4 worst): Manager’s percentile position (e.g., 5th percentile = top 5%, very strong).
• Peer Funds: Universe size per period (e.g., 246 funds QTD).
• R-Squared: Style explanation % (bottom row; e.g., 75% overall).

How It Works

Returns are gross or net composite (firm-wide), vs. benchmark and clones. Peer ranks use survivorship-free universe matching style. Alpha = Manager – Static Clone (pure skill). Positive ranks (1-2) + alpha confirm edge; R-squared validates decomposition reliability.

Key Insights to Spot

• Persistence Across Horizons: Consistent top-quartile ranks (1-2) signal repeatable skill vs. short-term luck.
• Alpha Drivers: Peer Adjusted Alpha >0 with good ranks shows skill beyond style.
• Style Impact: Negative Style Effect but positive alpha means manager overcame factor headwinds.
• Universe Context: Large # peers (200+) make ranks robust; watch shrinkage signaling universe changes.
• R-Squared Fit: 70-90% typical—high means style explains most; low flags unique strategy.

Actionable Uses

• Quick Screening: Scan for all 1-2 ranks + positive ITD alpha.
• Narrative Test: Strong ranks but negative style effect? Credit to skill.
• Capacity Check: Deteriorating ranks over longer horizons warn of scale issues.
• Comparisons: Benchmark against peers in same columns for relative bets.
• DD Deep Dive: Drill into periods with rank jumps for process questions.

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.

Chart Elements

• Lines:
  • Manager Actual: Growth of $100 invested in the real fund.
  • Manager Clone: Growth of $100 in the Aapryl clone replicating the manager’s style.
  • Comparison: Growth of $100 in the selected comparator (e.g., clone benchmark or peer average).
• Y-Axis: Cumulative value of the initial $100 investment.
• X-Axis: Time periods across the manager’s track record.
• Benchmarks: Clone Benchmark (peer-adjusted style); Actual Benchmark (broad market index)—each tracking $100 growth.

Interactive Options:

• Select/deselect: Actual fund, clones, clone benchmark, actual benchmark.
• Toggle: Comparison line (overlay selected items) or Net Difference line (excess return gaps).

How Clones Work

Aapryl clones are passive portfolios that mirror a manager’s factor exposures (e.g., quality, value). The Manager Clone dynamically tracks recent style, enabling clear separation of active decisions from passive replication. Use toggles to spotlight differences revealing true skill.

Key Insights to Spot

• Outperformance Source: Manager line above clones shows added value from decisions beyond style.
• Style Fit: Clone proximity confirms alignment with stated approach.
• Benchmark Context: Compare against clone benchmark for peer-relative success.
• Excess Gaps: Net difference toggle quantifies alpha periods (e.g., manager reaches $180 vs. clone at $150).

Actionable Uses

• Skill Breakdown: Toggle net difference to measure contributions over time.
• Process Check: Verify if growth aligns with manager’s pitch.
• Risk Gauge: Large divergences highlight active risk levels.
• Peer Ranking: Apply consistent views for multi-manager evaluation.

Chart Elements

• Top Panel (Returns vs. Benchmark):
  • Blue Bar: Manager excess return (actual minus benchmark).
  • Orange Bar: Style Clone excess return (clone minus benchmark).
• Bottom Panel (Attribution):
  • Green Bar: Positive skill return (periods of manager outperformance vs. clone).
  • Red Bar: Negative skill return (periods of underperformance vs. clone).
• X-Axis: Return percentages (annualized or period-specific).
• Period: Selected timeframe (e.g., quarterly or custom).

How Skill Attribution Works

Returns decompose as: Benchmark + Style Excess (clone captures factor tilts) + Skill (manager minus clone). Positive skill (green) shows added value from picks/timing; negative (red) flags shortfalls. Style clone excess (orange) reveals if passive style replication beat the broad benchmark.

Key Insights to Spot

• Skill Impact: Green bars > red indicate net positive alpha from active decisions.
• Style Strength: Large orange bars show factor tilts driving relative gains.
• Total Excess: Blue bar = orange + (green – red); mismatches signal attribution accuracy.
• Period Trends: Compare across quarters to detect consistency.

Actionable Uses

• Source ID: Distinguish style luck from skill for manager meetings.
• Trend Analysis: Track if skill flips from positive to negative over time.
• Benchmark Check: Validate if clone excess aligns with market regimes.
• Portfolio Decisions: Prioritize managers with persistent green dominance.

Chart Elements

The chart is structured in sections, with each row showing annualized excess returns (positive = outperformance) calculated over the full track record. Here’s what every line means:

Top Section – Total Excess Returns
These rows compare overall performance against the broad benchmark (e.g., MSCI World):

• Manager vs Benchmark: The manager’s total annualized excess return. For example, 12.4% means the fund grew faster than the benchmark by this amount annually since inception. This is your headline number—what most people start with.
• Static Clone (Long-Term Style Adjusted Benchmark): A passive portfolio built to match the manager’s fixed, inception-period factor exposures (think quality, value, size, momentum). If this shows 10.7%, it tells you what a “buy-and-hold” version of the manager’s style would have delivered vs. the benchmark.
• Dynamic Clone (Short-Term Style Adjusted Benchmark): Like the static clone but rebalanced every 36 months to reflect recent style changes. A value like 10.5% shows if short-term tactical tilts in factors helped or hurt relative to the benchmark.

Middle Section – Style and Alpha Attribution
This bridges raw excess to skill:

• Style Effect (Clone Benchmark – Benchmark): The passive contribution from the manager’s overall factor tilts. -0.75% would mean the style itself underperformed the broad benchmark—perhaps quality/value factors lagged during a growth-led market.
• Style Adjusted Alpha (Manager – Static Clone): Pure active return after stripping out long-term style. 2.1% here means the manager added this much value through decisions beyond just holding their stated style.

Bottom Section – Factor Skill Decomposition
The real insight—breaks active return into timing vs. picks:

• Style Timing (Style Adjusted Alpha – Dynamic Clone): The portion from tactically rotating factors (e.g., overweighting value during its cycles). 0.5% indicates modest timing skill.
• Stock Selection (Style Adjusted Alpha – Style Timing): What’s left after timing—idiosyncratic wins from individual security choices. 1.5% shows strong bottom-up alpha.

Summary Metrics (at the very bottom):

• Aapryl Score (1-5 scale, where 1 is best/high skill persistence and 5 is worst/low persistence): A forward-looking rating based on the consistency and magnitude of skill components above. A score of 1 suggests high odds of repeating top-quartile performance; 5 flags likely mediocrity.
• R-squared: Measures how well the clones explain the manager’s returns (75.76% means style/timing account for ~76% of variance; higher is more reliable decomposition).

How Decomposition Works

Imagine total excess return as a math equation:
Manager vs Benchmark = Style Effect + Style Timing + Stock Selection

• The clones act as subtractors: Static removes long-term style, dynamic removes short-term style too. What’s left is pure skill.
• All figures are annualized since inception (e.g., “Oct 2014” start date), so they smooth over market cycles. Positive values in skill rows add up to explain the top-line excess; negatives reveal drags.

Key Insights to Spot

• Where Alpha Comes From: If stock selection dwarfs style timing, the manager excels at picks, not market timing—great for bottom-up strategies.
• Style’s Role: Negative style effect? The manager’s factors underperformed broadly, so credit goes to skill overcoming that.
• Decomposition Reliability: R-squared over 70-80% means the clones fit well; below 50% suggests unique bets or data noise.
• Future Potential: Pair strong skill rows (e.g., >1% selection) with a low Aapryl Score (1-2) for high-confidence picks.

Actionable Uses

• Validate Manager Stories: If they claim “we’re stock pickers,” demand dominant stock selection and low style timing reliance.
• Build Portfolios: Use breakdowns to balance timing-heavy vs. selection-heavy managers for diversification.
• Screen Efficiently: Set filters like Style Adjusted Alpha >1%, Aapryl Score ≤2, R-squared >70%.
• Monitor Changes: Recalculate for rolling periods—if stock selection shrinks, dig into recent decisions.

Chart Elements

Core Components:

• X-Axis (Assets Under Management in $B): Horizontal scale showing AUM levels for each data point (e.g., 0 to 30+ billion). Each point represents a specific quarter or period in the track record.
• Y-Axis (Manager Skill %): Vertical scale for the manager’s skill score (e.g., -7.5% to +7.5%). Positive values mean skill beat peers that quarter; negative means underperformance. Derived from Aapryl’s edge/consistency decomposition (stock selection + timing).
• Data Points (Blue Dots): One dot per period (e.g., quarterly since 10/2014). Position shows skill vs. AUM for that snapshot—cluster them to spot patterns.
• Trend Implied: Slope and correlation (not explicitly labeled but visually assessible)—steep positive slope means skill holds or improves as AUM grows.

Context Labels:

• Period range (e.g., 10/2014-12/2025) confirms full track record coverage.
• No explicit R-squared or p-value here, but tight clustering around a line indicates strong correlation.

How It Works

Each quarter’s skill score (from prior decomposition charts) is plotted against contemporaneous AUM. This tests the classic “skill dilution” hypothesis: Does performance decay as assets scale? Aapryl calculates skill as peer-relative z-score from excess returns after clone adjustment. The scatter visualizes if high-AUM periods coincide with strong/weak skill, with correlation strength signaling capacity limits.

Key Insights to Spot

• Positive Correlation: Dots trend upward rightward—strong skill persists or strengthens with growth, suggesting scalable process (ideal for allocation).
• Negative Slope: Dots fall as AUM rises—early small-AUM outperformance fades with scale, flagging capacity constraints.
• Clustering: Tight vertical spread at high AUM means consistent skill regardless of size; wide scatter warns of variability.
• Outliers: Lone high-skill dots at peak AUM validate “one more good quarter”; persistent low dots signal trouble.
• Capacity Threshold: Where dots shift from top-right to bottom-right quadrant often marks diseconomies.

Actionable Uses

• Scalability Check: Greenlight managers with positive/upward trends through current AUM levels.
• Risk Flagging: Avoid if recent high-AUM dots cluster low—performance may erode further.
• Due Diligence Questions: Ask “What changed at AUM inflection points?” backed by specific dots.
• Portfolio Limits: Cap exposure based on where skill inflection occurs in the scatter.
• Trend Monitoring: Replot quarterly—if new dots break the favorable pattern, reassess.

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.