Page Layout

The page has these main sections from top to bottom:

• Header with Fund Info

  Shows the fund title (ticker and name) and last update date. Click '?' for contextual help or the video icon for a guided walkthrough.

• Chart Controls

  Contains the Compare button to overlay SA (Stranded Assets) or SPY-XLE (market minus energy) on the charts. Below the charts, a date range picker lets you adjust the time period displayed.

• Constituent Chart

  Compares fund price to the benchmark index. Both lines start at 100, so you can read percentage gains directly. If the fund line reaches 130, the fund gained 30%. When the fund line is above the index, it returned more than the benchmark. Use date buttons to examine different horizons; short-term (6M, 1Y) shows recent behavior, long-term (5Y, ALL) shows sustained patterns.

• Portfolio Chart

  Shows the long-short portfolio: fund return minus benchmark return. This strips out general market movements. Upward slope = fund returned more than benchmark. Downward slope = fund returned less. Check multiple time periods. Consistent slopes indicate persistent relative behavior; slopes that flip direction may reflect changing market conditions or style rotation.

• Volatility Chart

  Displays annualized volatility over time. Typical range: 15-25%. Values above 30% indicate high risk. Spikes often coincide with market crises or climate policy announcements. Persistent high volatility (not just brief spikes) means ongoing elevated risk.

• Top Holdings Table

  Lists the fund's 10 largest positions by percentage of assets. High concentration (top 5 holdings over 40%) means a few stocks dominate returns. Verify these holdings match the fund's stated climate strategy. Unexpected positions warrant investigation.

• Fama-French Factors Table

  Statistical breakdown of what drives returns: Alpha (unexplained return), Beta (market sensitivity), SMB (size tilt), HML (value/growth tilt). Each factor has a coefficient and t-statistic. Examine Alpha and its t-stat to assess returns not explained by standard factors.

Using Chart Controls

The page provides these controls:

• Compare Button

  Overlay SA (Stranded Assets) or SPY-XLE (market minus energy) on all charts. Use SA to test climate hedging: if the fund rises when SA falls, it may protect against fossil fuel losses. Use SPY-XLE to see how the fund compares to a portfolio that removes energy sector exposure.

• Date Range Picker

  Below the charts, drag the handles to select a custom date range. The charts and Fama-French factors recalculate when you change the range. A fund may show positive alpha over one period but negative alpha over another.

Regression Factors Table

The table shows results from two regressions. The CAPM regression estimates excess return after accounting for market exposure. The multi-factor regression adds size, value, stranded assets, and oil factors. Each coefficient is shown with its t-statistic in parentheses.

CAPM Regression
• ${\alpha }_{\mathrm{CAPM}}$

  Annualized excess return from a simple CAPM regression (fund vs. market only). Positive ${\alpha }_{\mathrm{CAPM}}$ means the fund outperformed after accounting for market exposure. This is a baseline measure: if ${\alpha }_{\mathrm{CAPM}}$ is positive but ${\alpha }_{\mathrm{SA}}$ is near zero, the outperformance is explained by factor tilts, not skill.

Multi-Factor Regression (Fama-French + SA + Oil)
• ${\alpha }_{\mathrm{SA}}$

  Annualized excess return from the multi-factor regression (market + size + value + stranded assets + oil). This is a stricter test: positive ${\alpha }_{\mathrm{SA}}$ means outperformance that can't be explained by any of the five factors. Compare ${\alpha }_{\mathrm{CAPM}}$ to ${\alpha }_{\mathrm{SA}}$: if both are positive and statistically significant (t-stat > 2), the fund has genuine excess return.

• ${\beta }_{\mathrm{MKT}}$

  Market sensitivity. ${\beta }_{\mathrm{MKT}}$ of 1.0 means the fund moves proportionally with the market. ${\beta }_{\mathrm{MKT}}$ of 1.3 means the fund amplifies market moves by 30% (a 10% market drop ≈ 13% fund drop). Higher ${\beta }_{\mathrm{MKT}}$ indicates more market risk.

• ${\beta }_{\mathrm{SMB}}$

  Size factor (Small Minus Big). Positive ${\beta }_{\mathrm{SMB}}$ = tilt toward smaller companies. Negative ${\beta }_{\mathrm{SMB}}$ = tilt toward large caps. Climate funds often show positive ${\beta }_{\mathrm{SMB}}$ because many clean energy companies are smaller and still growing.

• ${\beta }_{\mathrm{HML}}$

  Value factor (High Minus Low book-to-market). Positive ${\beta }_{\mathrm{HML}}$ = value tilt. Negative ${\beta }_{\mathrm{HML}}$ = growth tilt. Climate funds typically show negative ${\beta }_{\mathrm{HML}}$ because clean energy companies are growth-oriented. Warning: growth-tilted funds suffer when rates rise or investors rotate to value.

• ${\beta }_{\mathrm{SA}}$

  Stranded Assets sensitivity. Negative ${\beta }_{\mathrm{SA}}$ means the fund tends to rise when stranded assets fall, a desirable property for climate hedging. Positive ${\beta }_{\mathrm{SA}}$ means the fund moves with fossil fuel holdings, reducing its climate hedge value.

• ${\beta }_{\mathrm{OIL}}$

  Oil price sensitivity. Negative ${\beta }_{\mathrm{OIL}}$ means the fund tends to do well when oil prices fall. Positive ${\beta }_{\mathrm{OIL}}$ means the fund benefits from rising oil prices. Climate funds often show negative ${\beta }_{\mathrm{OIL}}$ due to underweighting energy.

• t-statistic (in parentheses)

  Each coefficient is shown with its t-statistic. $\left|t\right|$ > 2 means roughly 95% confidence the result is real. $\left|t\right|$ < 2 means the coefficient could be zero, so don't rely on it. Always check ${\alpha }_{\mathrm{CAPM}}$ and ${\alpha }_{\mathrm{SA}}$ t-stats: impressive alpha with low t-stat is meaningless.

Use the charts and tables to understand fund characteristics: How does the fund perform relative to benchmarks? What factor exposures drive returns? Here's how to interpret what you see:

Reading the Charts

In the Constituent Chart, check if the fund line stays above or below the index across multiple time periods (1Y, 2Y, 5Y). Consistent patterns are more informative than a single period. In the Portfolio Chart, look for sustained slope direction across different timeframes. If the slope is consistently positive or negative across periods, the fund shows persistent relative behavior versus its benchmark. In the Volatility Chart, note both typical levels (15-25% is normal) and spikes. Brief spikes during market stress are expected; persistent elevation above 25-30% means ongoing high risk.

Understanding Factor Results

The Fama-French table reveals what drives this fund's returns. Here's what to look for:

• Positive Alpha with t-stat > 2

  Indicates statistically significant excess returns beyond what the factor model explains. Example: Alpha of 1.2% with t-stat 2.4 suggests the excess return is unlikely due to chance. If t-stat is below 2, the apparent alpha is not statistically distinguishable from zero. Note: positive alpha may reflect the fund's climate focus during periods when climate investing is in favor, not necessarily persistent characteristics.

• High Market Beta (>1.2)

  The fund amplifies market movements. In a market decline of 25%, a fund with beta of 1.3 would be expected to fall approximately 32%. High-beta funds exhibit greater volatility in both directions: larger gains in rising markets, larger losses in falling markets.

• Negative HML (Growth Tilt)

  The fund favors growth stocks over value stocks. This is common for climate funds since clean energy companies are typically growth-oriented. The risk: growth-tilted funds often suffer when interest rates rise or when investors rotate into value stocks. This happened in 2022 when many climate funds dropped sharply while value stocks held up better.

• Reading t-statistics

  The t-statistic next to each coefficient tells you whether to trust that number. |t-stat| > 2 = roughly 95% confidence the result is real. |t-stat| < 2 = the coefficient could easily be zero or opposite. Focus especially on Alpha's t-stat: an impressive-looking alpha with t-stat of 1.3 is not statistically significant. A modest alpha with t-stat of 2.5 is small but statistically reliable.

V-Lab sources fund prices and holdings information from public market data. The factor analysis uses the Fama-French three-factor model, an industry-standard methodology developed at the University of Chicago that's comparable to academic research and institutional reports.

Daily Updates

Price charts, volatility estimates, and factor analysis update daily with the latest market data. Holdings data updates periodically based on each fund's disclosure schedule (typically quarterly). Factor results may shift when new data arrives. Check multiple time periods rather than relying on a single snapshot.

Model Specification

Volatility is estimated using a GJR-GARCH model, a statistical approach that captures two important patterns in real market data. First, 'volatility clustering': large price swings tend to follow other large swings, and calm periods tend to follow calm periods. Second, 'asymmetry': negative shocks cause bigger volatility spikes than positive shocks of the same size (a 5% drop spooks investors more than a 5% gain). This produces more realistic risk estimates than simple averages, especially during market stress.

Common Questions

The fund has strong returns but shows negative alpha - how is that possible?

Alpha measures return after accounting for factor exposures. A fund with 15% returns might show negative alpha if 18% was expected based on its market beta and growth tilt. The fund underperformed relative to its risk exposures, even though raw returns were positive.

Why does this climate fund show positive correlation with Stranded Assets?

Some 'climate' funds hold diversified portfolios that include traditional energy companies or have indirect fossil fuel exposure through holdings. Check the Top Holdings table to see what the fund actually owns. Positive SA correlation suggests the fund may not hedge climate transition risk effectively.

Why does the Portfolio Chart slope downward even though returns look positive?

The Portfolio Chart shows the fund's return minus the benchmark return. A downward slope means the fund underperformed its benchmark over that period, even if both had positive absolute returns. A fund gaining 10% while the benchmark gained 15% would show a downward slope.

How do I know if this fund is a good climate hedge?

Look for negative β_SA (moves opposite to stranded assets) and check the Portfolio Chart with SA overlay - inverse movement suggests hedging properties. Also verify that top holdings are genuinely climate-focused and not diversified across traditional sectors.

Interpreting Results

Guidance on what the numbers mean and what to do about them:

Why does this fund show negative alpha?

Negative alpha means the fund earned less than its risk exposures would predict. Common causes: (1) Management costs, (2) Stock selection effects within the climate sector, (3) The specific time period was unfavorable for the fund's style (climate investing may be out of favor). Check the t-statistic: if |t-stat| < 2, the negative alpha is not statistically significant. The true alpha could be zero or even positive. If |t-stat| > 2, the negative alpha is statistically reliable. Also check multiple time periods to see if negative alpha persists or is concentrated in specific periods. A climate fund with negative alpha may still be true to its mandate and serve as a climate hedge.

Why is volatility spiking?

Spikes occur during market stress (COVID crash, rate hikes) or when holdings experience large moves (policy announcements, earnings surprises). To interpret spikes: compare to the benchmark to determine if the spike is fund-specific or market-wide. Market-wide spikes typically reflect systemic events. Fund-specific spikes may indicate news affecting holdings or changes in fund composition. Short-term spikes (days) are common; sustained elevation (weeks/months) suggests a change in the fund's underlying risk characteristics.

What does negative HML mean for a climate fund?

Negative HML means the fund favors 'growth' stocks over 'value' stocks. Growth stocks trade at high prices relative to current earnings because investors expect rapid future expansion (think Tesla, solar companies). This is typical for climate funds. The risk: growth-tilted funds often suffer when interest rates rise or investors rotate into value stocks. This happened dramatically in 2022. If you're concerned about value/growth rotation, check if the fund's performance correlates with broader growth indices like QQQ.

Why is the Portfolio Chart sloping downward?

A downward slope indicates the fund returned less than its benchmark over that period. To interpret: check multiple time periods (1Y, 2Y, 5Y) to see if the pattern is consistent or period-specific. Consider market conditions. Growth-tilted climate funds often lag when value stocks are favored. Consistent patterns across all time periods indicate persistent relative behavior; patterns that differ across horizons may reflect style rotation. A fund that trails the broad market may still provide climate exposure and hedging properties.

A systematic approach to analyzing climate fund data on this page:

Deeper Analysis

After the quick scan:

• Add SA via Compare to examine climate hedging properties. Look for inverse correlation when SA declines.
• Check the Volatility Chart for sustained high levels versus temporary spikes. Persistent elevation indicates ongoing high variability.
• Review factor loadings to understand what drives returns beyond market exposure.
• Remember: factor results depend on the sample period. Check multiple horizons to assess robustness.