Period Correlations - Revenue/Profitability Analysis

What This Page Does

This tool analyzes how 56 macroeconomic variables (employment, interest rates, consumer spending, etc.) correlate with credit card trust revenue metrics. Use it to identify leading indicators that predict changes in Portfolio Yield or Payment Rate 1-36 months ahead. Start by selecting companies below, then explore the correlation tables or build your own composite macro index.

Advanced: Custom Time Periods

Define custom economic periods (e.g., recessions, rate hikes) to analyze how correlations change across different market regimes ▼

Configure periods for:

Editing periods for: Consensus View

Load a preset configuration:

Using default periods: 3 periods (Pre-Pandemic, Pandemic, Post-Pandemic)

Period-to-Period Comparison

Compare how correlations changed between time periods. For example: Did unemployment become more predictive after the pandemic vs before?

By default, comparisons analyze how correlations changed from baseline (first period) to later periods. Add more comparisons to analyze additional period transitions.

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Stress Scenarios

Step 1: Select Companies to Analyze

Choose which credit card trust issuers to include in your analysis. The correlation tables below will show how macroeconomic variables relate to the combined portfolio metrics of your selected companies.

Step 2: Build Custom Macro Indices

Combine multiple FRED variables into a single predictive indicator (e.g., "Consumer Stress Index" from unemployment + debt + savings) ▼

Create New Index

Index Name

Select Variables (recommended: 3-10)

0 variables selected

Click variables below to add them

Weighting Method

Equal

Simple average

Correlation

Weight by |r|

Inv. Volatility

Stable vars weighted more

Step 3: Correlation Analysis Results

The tables below show how each macroeconomic variable correlates with your selected companies' Portfolio Yield. Higher positive correlations (green) mean the variable moves together with revenue. Negative correlations (red) indicate inverse relationships. Lag values (0m-36m) show how far ahead each variable predicts revenue changes.

Compare Companies Side-by-Side

See how different issuers respond to the same macroeconomic variables. Identify which companies are more sensitive to interest rates, employment, or consumer spending. Useful for portfolio diversification and relative value analysis.

Companies selected in Consensus View:

Deep Dive: Single Company Analysis

Analyze one issuer in detail. See exactly which macro variables have the strongest predictive power for that company's revenue, and at what lag. Ideal for single-name credit research or when evaluating a specific ABS trust.

Select a company to analyze:

Pan.Beh (Pre to Pandemic):

Post.Beh (Pre to Post):

Time Periods (Monthly Data):

Data Sources:

Revenue Metrics: Monthly 10-D trust filings (SEC)

Economic Data: FRED (Federal Reserve) monthly series

Trusts: COF, DFS, SYF, AXP, JPM, BAC, C

Revenue Metrics Explained: