These terms appear in the rankings table columns and the time series chart. Understanding them will help you interpret the data:

1. Page Header (Top of Page)

The header displays the dataset name, model type, and last update date. The most prominent element is the capital shortfall summary:

The large dollar figure is the total capital shortfall:

• Total Capital Shortfall Amount

  Sum of all positive SRISK values for banks in the current view. In Global view, this aggregates across all regions. When a specific region is selected, it shows that region's total only. This is how much emergency capital the banking system would need if the market dropped by the specified percentage.

• What This Number Means

  If a crisis matching your threshold occurred today, this is the total bailout money needed to keep all undercapitalized banks solvent. The number excludes banks with negative SRISK (those that would remain adequately capitalized).

3. Individual Bank Chart (Inside SRISK Graph Panel)

A collapsible panel shows historical data for a selected bank. Click the panel header to expand or collapse it.

• Series Dropdown

  Choose what metric to plot: SRISK, Marginal SRISK, LRMES, Market Beta, Correlation, Volatility, Leverage, or Stressed Leverage. Each shows different aspect of the selected bank's risk over time.

• Date Range Controls

  Use the From/To date pickers or click preset buttons (6M, 1Y, 2Y, 5Y, 10Y, All) to adjust the time period. Download buttons at the top right let you export chart data after logging in.

4. Options Panel (Right Side on Desktop, Above Rankings on Mobile)

• Region and Country Filters

  For multi-region analyses, the page defaults to a Global view showing all firms across all regions. Select a specific region (Africa, Americas, Asia, Europe) to filter, or choose Global to see all firms ranked together. Single-region analyses show that region's firms directly and hide the region selector. Use the Country dropdown to filter to banks from a specific country within the selected region.

• Separate Accounts (Insurance Companies)

  Insurance companies have special balance sheet items. This slider adjusts how separate accounts are treated in leverage calculations. Default is 40%. Most users can leave this unchanged.

• Reset Buttons

  Individual reset buttons restore each parameter to defaults. The 'RESET OPTIONS' button at the bottom restores all settings at once.

When to Adjust the Options

Most users can leave options at their defaults. Here's when you might want to change them:

• Crisis Threshold (Default: 40%)

  40% matches the 2008 crisis severity. Lower it (e.g., 20%) to see which banks become vulnerable in a moderate downturn. Raise it (e.g., 50%) to stress-test against a worse-than-2008 scenario. Watch the total shortfall change as you adjust.

• Capital Requirement (Default: 8% Americas, 5.5% Europe)

  Different accounting standards require different capital ratios to achieve equivalent safety. The defaults reflect regulatory norms. Raise the requirement to see how many banks fail a stricter capital test; lower it to model more lenient requirements.

• Separate Accounts (Default: 40%)

  Only relevant for insurance companies. Separate accounts hold policyholder assets that appear on both sides of the balance sheet. Adjusting this changes how leverage is calculated for insurers. If you're not analyzing insurance companies specifically, leave this at 40%.

5. Rankings Table (Main Section)

The rankings list every bank in the selected region/country, ranked by SRISK by default. In the Global view, each institution name is preceded by a small colored dot indicating its region (red for Asia, blue for Europe, green for Americas, orange for Africa); hover over the dot to see the region name. The SRISK% column uses heat-mapped backgrounds on the V-Lab red sequential scale, with darker red indicating a higher share of systemic risk. All table rows highlight with a pink hover effect for easy tracking. On desktop, banks appear in a sortable table with clickable column headers. On mobile, each bank appears as a card with metrics listed vertically, and sorting uses a dropdown menu. Here is how to use it:

• Sorting by Any Column

  On desktop, click any column header to sort by that metric; click again to reverse the order. On mobile, use the 'Sort by' dropdown to choose a metric. Sort by SRISK% to see relative importance, by LRMES to find most market-sensitive banks, or by Lvg to find most leveraged.

• Date Picker

  The date picker above the rankings lets you view rankings as of any historical date. Navigate back to see how systemic risk looked before past crises or during periods of interest.

• Selecting a Bank for the Chart

  Click any bank (row on desktop, card on mobile) to select it. The time series chart above will expand (if collapsed) and show that bank's historical data. Select different banks to compare them visually.

Table Column Reference

Each column shows a different risk metric. Definitions are also in the Essential Concepts section above:

• SRISK ($ m)

  Capital shortfall in millions of dollars. Positive = needs capital. The main ranking metric. Banks at the top of the table pose the most systemic risk.

• SRISK%

  This bank's share of total system risk, displayed with a heat-mapped red background (darker red indicates higher SRISK%). If five banks have 80% combined, the system is concentrated. If 50 banks each have 2%, risk is distributed.

• Marginal SRISK

  How much of the bank's SRISK is due to the crisis scenario specifically (vs. already being undercapitalized today). High marginal SRISK means the bank only becomes vulnerable during stress.

• LRMES

  Expected stock loss if the market falls by the selected threshold. A bank with 70% LRMES would lose 70% of market value during a crisis. High LRMES banks amplify market downturns.

• Beta

  How much the stock moves relative to the market. Beta of 1.5 means if market moves 1%, this stock moves 1.5%. Higher beta = more volatile, more systematic risk exposure.

• Cor

  Correlation with the market index (0 to 1). Most banks show 0.5-0.9. Higher correlation means less diversification benefit; the bank moves with the market.

• Vol

  Annualized standard deviation of returns. 30% volatility means annual returns typically fall within plus or minus 30% of the mean about 68% of the time. Higher volatility means more uncertain value and more risk.

• Lvg

  Current quasi-leverage (total assets / market equity). Leverage of 20 means $20 of assets for every $1 of market cap. Updates daily as stock prices change. Higher = less cushion to absorb losses.

• Stressed Lvg

  Projected leverage after crisis losses. Example: a bank at 15x leverage with 60% LRMES would see equity drop by 60%, pushing leverage to 37.5x. The gap between current Lvg and Stressed Lvg shows how much the crisis would amplify the bank's fragility.

Reading the Rankings Table

The rankings table shows which banks pose the greatest systemic risk. Banks near the top have the highest SRISK values and would need the most emergency capital during a crisis.

What Drives High SRISK

Three factors combine to determine a bank's SRISK:

• Size

  Larger banks naturally have higher SRISK because their failure would require more capital to address. A $2 trillion bank failing matters more than a $20 billion bank.

• Leverage (Lvg Column)

  Banks with high leverage have less equity cushion. Look at the Lvg column: banks above 20x are highly leveraged. These banks lose proportionally more equity in downturns.

• Market Sensitivity (LRMES Column)

  Banks with high LRMES fall harder than the market. An LRMES of 80% means the bank loses 80% of its value when the market falls by the selected threshold. These banks amplify crises.

What the Numbers Mean

• Positive SRISK

  The bank would need this much emergency capital during a crisis. A bank with $50B SRISK would need $50 billion in new capital (or bailout) to remain solvent.

• Negative SRISK (or Not Listed)

  The bank would still have adequate capital after absorbing crisis losses. These banks are relatively safer. They don't appear in the positive-only rankings but may appear in full data downloads.

• SRISK% (First Column After Name)

  Shows this bank's share of total system risk with a heat-mapped red background for quick visual comparison. If the top 5 banks account for 50% of total SRISK%, the system is heavily concentrated. Watch for concentration patterns.

How the Data Is Calculated

SRISK combines two data sources: daily stock prices (for market-based risk measures) and quarterly balance sheets (for leverage calculations).

• Update Schedule

  Rankings are recalculated every Saturday morning. The 'Last Updated' date in the header shows when the current data was calculated. Between updates, values remain fixed even as markets move.

• Why 40% Default?

  The 40% market decline matches the severity of the 2008-2009 financial crisis. This is not a prediction; it is a stress test asking 'what if 2008 happened again?' You can adjust this to model milder or more severe scenarios.

Understanding the Model Types

• MES (Dynamic MES for US Financials)

  Covers US financial institutions using the S&P 500 as the market index. Uses Dynamic Conditional Beta with analytical LRMES calculation that updates daily. The standard choice for routine monitoring of US banks.

• MESSIM (Simulation-Based MES)

  Covers US financial institutions using Monte Carlo simulation with 10,000 scenarios. More accurate tail risk estimation but updates weekly rather than daily. Crisis threshold fixed at 40% due to simulation complexity. Best for detailed tail risk analysis.

• GMES and DMES (Global and Domestic)

  GMES covers worldwide institutions using each bank's local market index with asynchronous trading adjustments for different time zones. DMES analyzes banks within a single country using that country's domestic index. Both use Dynamic Conditional Beta with daily updates.

Common Questions

Why did a bank's SRISK jump dramatically between weeks?

SRISK can jump for two reasons. First, stock price changes: when a bank's stock drops, its market value falls and leverage rises (same debt, less equity), causing SRISK to spike. Second, balance sheet updates: when new quarterly data is released, changes in debt levels or book equity can shift SRISK even if the stock price is stable. Check both the stock chart and whether the jump coincides with quarterly reporting dates.

Why doesn't Bank X appear in the rankings?

Banks with negative SRISK (adequate capital even after crisis losses) do appear in the table, but if sorted by SRISK descending (the default), they will be at the bottom. Scroll down, change the sort order, or use the search box to find them by name or ticker. Also check that you have the correct region and country filters selected.

Why is there no time series data for a particular bank?

Time series require sufficient historical data. Recently listed banks, banks that changed names or merged, or thinly traded stocks may have gaps. The chart shows whatever data is available; missing periods appear as gaps in the line.

Why are European and US banks calculated differently?

European banks report under IFRS accounting standards; US banks use GAAP. Due to differences in how assets are measured, a 5.5% capital ratio under IFRS is economically equivalent to 8% under GAAP. V-Lab applies the appropriate ratio by region automatically (Europe defaults to 5.5%, all other regions to 8%). In Global view, use the 'Customize' button to edit per-region capital requirements, or the 'Reset' button to restore defaults.

Understanding the Limitations

• What SRISK Doesn't Capture

  SRISK measures expected capital shortfall in a crisis, not probability of failure. High SRISK does not mean a bank is likely to fail. It means the bank would need significant capital if a crisis occurred. Conversely, low SRISK doesn't guarantee safety, as banks can fail for non-market reasons (fraud, operational risks) not captured in stock prices.

• Quarterly vs. Daily Data

  V-Lab uses quasi-leverage, which combines market equity (updated daily) with balance sheet debt (updated quarterly). So leverage changes daily as stock prices move, but the debt component only updates with new quarterly filings. A bank's reported leverage here may differ from its book leverage.

• Correlation During Crises

  Correlations estimated from normal periods may understate how banks move together during crises. The model uses dynamic correlation estimates that adapt, but extreme events can still exceed model expectations.

Frequently Asked Technical Questions

Quick Start: First 60 Seconds

• 1. Check the Header

  Look at the total capital shortfall number at the top. This is the total bailout cost if a crisis hit today. Note whether it seems high relative to historical values.

• 2. Scan the Top of the Rankings Table

  The banks at the top have the highest SRISK. Note the names: these are the most systemically important. Look at the SRISK% column to see how much of total risk each bank represents.

• 3. Click a Bank to See Its History

  Select any bank in the rankings. The time series chart expands and shows that bank's SRISK over time. Look for trends: is risk rising or falling? Were there spikes during past crises?

• 4. Sort by Different Columns

  Sort by LRMES to see which banks are most market-sensitive. Sort by Lvg to see most leveraged. Compare the different rankings to understand what drives each bank's risk.

• 5. Test Different Scenarios

  Change the crisis threshold from 40% to 50% and watch the total shortfall increase. This shows how sensitive the system is to crisis severity.

Tips for Effective Analysis

• Watch for Changes Over Time

  Use the 'View changes' toggle to compare two dates. Banks with rapidly increasing SRISK may be emerging risks even if their current level isn't the highest.

• Use Multiple Metrics

  Don't rely on SRISK alone. A bank with high SRISK but low LRMES is large and leveraged but stable. A bank with high LRMES is volatile even if current SRISK is moderate.

• Check Concentration

  Add up SRISK% for the top 5 banks. If they account for 50%+ of total risk, the system is concentrated. Distributed risk (many banks each with small shares) is generally safer.

• Visit V-Lab's Welcome Page for Context

  The Analysis page shows individual banks; the Welcome page shows country totals and comparisons. Use both together. To navigate to the Welcome page, click the previous entry in the breadcrumbs at the top of the page (below the navigation bar). High country totals might be driven by one dominant bank or many smaller ones.