req.forecast: Realized extreme quantile forecasts
In lucatrapin/FinEx: Financial econometrics analysis with extreme value statistics
Description
Usage
Arguments
Value
Author(s)
References
Description
Computes one-day-ahead forecasats of Value at Risk (VaR) and Expected Shortfall (ES) for a fitted REQ model.
Usage
1
req.forecast(fit, x, alpha)
Arguments
fit
Output object of the arq() function.
x
Scalar with the realized measures used in the forecast.
alpha
Probability level for the computation of the risk measures.
Value
A matrix containing the VaR and ES forecasts at level alpha.
Author(s)
Luca Trapin
References
Bee, M., Dupuis, D. J., and Trapin, L. (2018). Realized extreme quantile: A joint model for conditional quantiles and measures of volatility with EVT refinements. Journal of Applied Econometrics, 33(3), 398-415.
lucatrapin/FinEx documentation built on Dec. 21, 2021, 11:52 a.m.
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Description Usage Arguments Value Author(s) References
Description
Computes one-day-ahead forecasats of Value at Risk (VaR) and Expected Shortfall (ES) for a fitted REQ model.
Usage
1 | req.forecast(fit, x, alpha)
|
Arguments
fit |
Output object of the |
x |
Scalar with the realized measures used in the forecast. |
alpha |
Probability level for the computation of the risk measures. |
Value
A matrix containing the VaR and ES forecasts at level alpha.
Author(s)
Luca Trapin
References
Bee, M., Dupuis, D. J., and Trapin, L. (2018). Realized extreme quantile: A joint model for conditional quantiles and measures of volatility with EVT refinements. Journal of Applied Econometrics, 33(3), 398-415.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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