RobGARCHBoot (version 1.0.0)

fitted_Vol: Estimated Volatility

Description

Using the robust estimated parameters of Boudt et al. (2013) and Truc<U+00ED>os et at. (2017), we obtain the estimated volatility.

Usage

fitted_Vol(theta,r)

Arguments

theta

Vector of robust estimated parameters obtained from ROBUSTGARCH function.

r

Vector of time series returns.

Value

The function returns the estimated volatility from 1 to T+1.

Details

More details can be found in Boudt et al. (2013) and Truc<U+00ED>os et at. (2017).

References

Boudt, Kris, Jon Danielsson, and S<U+00E9>bastien Laurent. Robust forecasting of dynamic conditional correlation GARCH models. International Journal of Forecasting 29.2 (2013): 244-257.

Truc<U+00ED>os, Carlos, Luiz K. Hotta, and Esther Ruiz. Robust bootstrap forecast densities for GARCH returns and volatilities. Journal of Statistical Computation and Simulation 87.16 (2017): 3152-3174.

Examples

# NOT RUN {
# Using the Bitcoin daily returns, we estimate the parameter of the GARCH model in a robust way
param = ROBUSTGARCH(returnsexample)
# With the estimated parameters, we estimate the volatiltiy in a robust way
vol = fitted_Vol(param, returnsexample)
# }