About vs. Demo: This demo folder now uses a standardized launch page. Start with About Demo, then choose the run mode that fits your class.

Risk Management • Browser • 30-40 min

Counterparty Risk

The **mark-to-market adjustment** for counterparty default risk. It represents the expected loss from counterparty default.

Open About Demo Read README View Course Path

Calculate Credit Valuation Adjustment (CVA) and Debt Valuation Adjustment (DVA) for counterparty risk exposure.

Exposure Parameters

Risk Parameters

Counterparty Risk Results

Expected Exposure

$5.0M

CVA

$400K

DVA

$0

Adjusted Value

$9.6M

Key Concepts

  • CVA: Mark-to-market adjustment for counterparty default risk
  • DVA: Accounting adjustment for own credit risk
  • EE: Expected Exposure = Notional × Exposure Factor
  • LGD: Loss Given Default (recovery rate = 1 - LGD)

Formula: CVA = EE × PD × LGD

Standard demo guide

Use this demo in a logical learning sequence

Starts immediately in browser with no installs, no API keys, and classroom-safe defaults.

What this demo is about

The **mark-to-market adjustment** for counterparty default risk. It represents the expected loss from counterparty default.

Learning objectives

  • Explain the main risk decision that Counterparty Risk is designed to support.
  • Change input assumptions and predict how the output should respond before running the demo.
  • Interpret the result in plain language, not just as a number, chart, or AI recommendation.

Run mode and expectations

  • Supported modes: Browser
  • Starts immediately in browser with no installs, no API keys, and classroom-safe defaults.

Step 1: Inputs

  • Start with the default assumptions, then change one variable at a time so students can isolate cause and effect.
  • Treat each input as a lever that changes the scenario, baseline, or business context behind the result.

Step 2: Decision buttons

  • Use the main run or simulate action to compute the scenario after inputs are set.
  • Use export or reset actions, when present, to compare runs or return to a classroom-safe baseline.

Step 3: Outputs and what to notice

  • Read the top-line result first, then look for supporting metrics, tables, or narratives that explain why it changed.
  • Students should explain whether the output is descriptive, predictive, simulated, or recommended.
  • Look for counterparty profile, exposure, credit signal, and mitigation action
  • Observe how concentration and credit deterioration change risk posture

Available run modes

  • Browser: available for this demo.

How to proceed

  1. Choose the run mode that fits the class: Browser.
  2. Review the default assumptions before changing anything.
  3. Change one or two inputs, then use `Run the main action`.
  4. Read the output first, then compare any supporting metrics, charts, or AI text.
  5. Capture one insight, one limitation, and one action recommendation.