plot. Step 3. Create a varbacktest object. Step 4. Run a summary report. Step 5. Run all tests. Step 6. Run individual tests. Step 7. Create VaR backtests for multiple portfolios. Step 8. Display a summary report for both portfolios. Step 9. Run all tests for both portfolios. Step 1. Load the

to the Normal Distribution approach (seven (7) violations, blue stars) or the Historical Simulation method (eight (8) violations, red squares). Besides visual tools, you can use statistical tests for VaR backtesting. In Risk Management Toolbox™, a varbacktest object supports multiple statistical

functionality to assess the performance of the ES models in the test window. The esbacktest object does not require any distribution information. Like the varbacktest object, the esbacktest object only takes test data as input. The inputs to esbacktest include portfolio data, VaR data and corresponding VaR