DQ: Dynamic quantile test

In steinarv/quantileVaR: Quantile regression for estimating value at risk and backtesting.

Description

Backtest a series of Value at Risk forecasts using the Dynamic Quantile Test of Engle and Manganelli Define a variabele HIT_t = Y_t < VAR_t - prob Then it should not be possbile to predict HIT_t based on information known at time = t-1.
This may be tested with a regression:
HIT_t = b1 + b2*VAR_t + b3*VAR_t-1 + .... + bn*VAR_t-x + bn+1*HIT_t-1 + ..... + bn+z*Y_t .....
None of the included variables should be significant in explaining HIT_t

Usage

DQ(Y, VAR, prob, intercept=T, nVAR=0, nHIT=c(1,2,3,4), nY=F)

Arguments

Y	A series of observed values.
VAR	A series of predicted Value at Risk estimates.
prob	The probability level for which one do not expect the series to exceed the VaR estimate.
intercept	Logical, should an intercept be included in the regression
nVAR	Which lagged VaR estimates should be included in the regression. FALSE means that no lagged values are included. A single numeric, n, gives all lagged values between 1 and n. An array with numerics, c(x,y,z,...) includes lag x,y,z,..
nHIT	Which lagged HIT variables should be included in the regression. FALSE means that no lagged values are included. A single numeric, n, gives all lagged values between 1 and n. An array with numerics, c(x,y,z,...) includes lag x,y,z,..
nY	Which lagged values of the observed series should be included in the regression. FALSE means that no lagged values are included. A single numeric, n, gives all lagged values between 1 and n. An array with numerics, c(x,y,z,...) includes lag x,y,z,..

Value

Returns a list with the value of the coefficients of the regression, the test observator of Engle and Manganelli (2004) and the probability level of observering those coefficients given that their "true" conterparts all are zero.

Author(s)

Steinar Veka

References

Robert F. Engle and Simone Manganelli CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles Journal of Business & Economic Statistics Vol. 22, No. 4 (Oct., 2004), pp. 367-381 Published by: American Statistical Association Article Stable URL: http://www.jstor.org/stable/1392044

steinarv/quantileVaR documentation built on May 30, 2019, 10:46 a.m.