Class VarBacktest

java.lang.Object

com.quantfinlib.risk.VarBacktest

public final class VarBacktest
extends Object

VaR model validation: do the exceptions (losses beyond VaR) occur at the promised rate, and independently?

• Kupiec POF — likelihood-ratio test that the exception frequency matches 1 - confidence (two-sided: both too many and too few exceptions reject). χ²(1).
• Christoffersen independence — LR test that exceptions do not cluster (a model that is right on average but wrong in crises fails here). χ²(1).
• Conditional coverage — the joint test (POF + independence), χ²(2), with the exact p-value e^{-LR/2}.

A p-value below the chosen significance (e.g. 0.05) rejects the model.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static final record	VarBacktest.VarBacktestResult

Method Summary

Modifier and Type	Method	Description
static VarBacktest.VarBacktestResult	test(double[] returns, double[] varForecasts, double confidence)
static VarBacktest.VarBacktestResult	test(double[] returns, double constantVar, double confidence)	Backtests a constant VaR (positive loss fraction) against realized returns.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

test

public static VarBacktest.VarBacktestResult test(double[] returns,
 double constantVar,
 double confidence)

Backtests a constant VaR (positive loss fraction) against realized returns.

test

public static VarBacktest.VarBacktestResult test(double[] returns,
 double[] varForecasts,
 double confidence)

Parameters:

returns - realized periodic returns

varForecasts - VaR forecast for each period as a positive loss fraction, aligned with returns

confidence - the VaR confidence level (e.g. 0.95, 0.99)