Understanding Cross-Sectional Analysis & Correlation

When evaluating stocks, absolute returns only tell part of the story. What matters equally is how a stock performs relative to other stocks in the market.

Cross-Sectional Analysis compares all stocks at a specific point in time, ranking them by performance to reveal which are truly outperforming or underperforming the broader market.

What is Cross-Sectional Analysis?

Cross-sectional analysis examines multiple stocks at the same point in time, comparing their returns and calculating where each stock ranks relative to all others.

Think of it this way: Instead of asking "Did this stock go up?", cross-sectional analysis asks "Did this stock go up more than most other stocks?"

This approach is powerful because:

  • A stock can have negative returns but still be a top performer if the overall market is down more
  • It identifies relative strength which often persists over time
  • It normalizes for market conditions, making different periods comparable

Understanding Percentile Rankings

The percentile rank tells you what percentage of stocks a given stock has outperformed. A stock at the 80th percentile has outperformed 80% of all stocks in the analysis.

Percentile RangeCategoryWhat It Means
90-100Top PerformersStock outperformed 90%+ of the market
70-90Strong PerformersAbove average returns, consistently beating the market
30-70Average PerformersReturns in line with the broader market
10-30Weak PerformersBelow average returns, underperforming most stocks
0-10Bottom PerformersStock underperformed 90%+ of the market

Available Time Periods

Cross-sectional analysis is available across multiple lookback periods, each revealing different aspects of performance:

PeriodTrading DaysBest Used For
1 Year252 daysStandard annual comparison, most commonly used
2 Years504 daysMedium-term trends, filters out single-year anomalies
3 Years756 daysLong-term performance, captures full market cycles
4 Years1008 daysExtended view, useful for identifying consistent performers

Correlation Metrics Explained

Beyond ranking, our correlation analyzer calculates how each stock's returns relate to the market index. These metrics help you understand risk and diversification.

Pearson Correlation

Range: -1 to +1

Measures the linear relationship between stock returns and market returns

Interpretation: +1 = perfect positive correlation, 0 = no correlation, -1 = perfect negative correlation

Spearman Correlation

Range: -1 to +1

Measures the rank-based relationship, less sensitive to outliers than Pearson

Interpretation: More robust for non-linear relationships and extreme price movements

Beta

Range: Any value

Measures how much a stock moves relative to the market index

Interpretation: Beta > 1 = more volatile than market, Beta < 1 = less volatile, Beta < 0 = inverse movement

R-Squared

Range: 0 to 1

Shows what percentage of stock movement is explained by market movement

Interpretation: Higher R² = stock closely follows market, Lower R² = stock moves independently

Understanding Beta in Detail

Beta is one of the most important metrics for understanding a stock's risk profile relative to the market.

Beta = 1.0 Stock moves exactly with the market
Beta = 1.5 Stock is 50% more volatile than market. If market rises 10%, stock tends to rise 15%
Beta = 0.5 Stock is 50% less volatile than market. More defensive, smaller swings
Beta < 0 Stock moves opposite to market (rare). Can provide hedging benefits

Formula: Beta = Covariance(Stock Returns, Market Returns) / Variance(Market Returns)

Practical Use Cases

Relative Strength Screening

Identify stocks that are outperforming their peers regardless of absolute returns

Example: In a bear market, a stock with -5% return might still be in the 90th percentile if most stocks are down -20%

Sector Rotation Analysis

Compare stocks within the same industry to find leaders and laggards

Example: Filter by industry and sort by percentile to see which companies are gaining market share

Portfolio Rebalancing

Identify which holdings are performing well relative to alternatives

Example: Replace bottom quartile stocks with top quartile performers in the same sector

Mean Reversion Candidates

Find stocks at extreme percentiles that might revert to average

Example: Stocks below 10th percentile may be oversold; stocks above 90th may be extended

How to Use Cross-Sectional Analysis

1.

Select Your Time Period

Choose 1Y for recent performance or longer periods to filter noise and identify consistent performers.

2.

Filter by Market Cap

Use market cap filters to compare stocks within similar size categories for a fairer comparison.

3.

Sort by Percentile Rank

Identify top performers (high percentile) or potential value opportunities (low percentile).

4.

Click to View Stock Details

Click any row to see the full stock analysis page with correlation metrics, charts, and more.

Key Takeaways

  • Cross-sectional analysis compares all stocks at the same point in time to find relative winners and losers
  • Percentile rank shows what percentage of stocks a given stock has outperformed
  • Beta measures volatility relative to the market — higher beta = more risk and reward potential
  • Pearson & Spearman correlations measure how closely a stock follows market movements
  • R-Squared indicates how much of a stock's movement is explained by the market

Remember: Relative performance often persists. Stocks in the top percentiles tend to continue outperforming, making cross-sectional analysis a powerful tool for momentum-based strategies.

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All information is provided "as-is" for informational purposes only, not for trading or financial advice.

This platform provides statistical analysis and quantitative research tools. All outputs are for informational and educational purposes only. This is not investment advice. Users should conduct their own research and consult with qualified financial advisors before making investment decisions.

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