What are the core steps in a Monte Carlo VaR calculation?

Question

AcadiFi · Accepted Answer

Monte Carlo VaR is a process for generating a portfolio loss distribution. First define the risk factors, such as equity returns, rates, spreads, or FX moves. Next estimate their distribution and dependence structure. Then simulate many joint scenarios, revalue the portfolio under each scenario, calculate profit or loss, sort the losses, and read the relevant percentile.

Suppose Alder Ridge Risk simulates 20,000 one-day scenarios for a portfolio worth $42 million. Each scenario creates a vector of factor moves. The system reprices the positions, compares the simulated value with today's value, and stores the loss. If the 99 percent VaR is needed, the analyst ranks the losses and reads the loss level exceeded in about 1 percent of scenarios.

```mermaid
flowchart TD
  A[Define risk factors] --> B[Estimate distributions and dependence]
  B --> C[Simulate scenarios]
  C --> D[Revalue portfolio]
  D --> E[Sort losses]
  E --> F[Read VaR percentile]
```

The common mistake is to simulate returns but never perform proper portfolio revaluation. For linear books, approximations may work. For derivatives, full or careful approximation-based revaluation is usually critical. On the exam, also state the horizon, confidence level, data source, modeling assumption, and validation step, because those choices usually explain why two reasonable VaR answers differ materially. Practice more in our FRM question bank.

What are the core steps in a Monte Carlo VaR calculation?

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