RT Journal Article
T1 Bootstrap prediction for returns and volatilities in GARCH models
A1 Pascual, Lorenzo
A1 Romo, Juan
A1 Ruiz Ortega, Esther
AB A new bootstrap procedure to obtain prediction densities of returns and volatilities of GARCH processes is proposed. Financial market participants have shown an increasing interest in prediction intervals as measures of uncertainty. Furthermore, accurate predictions of volatilities are critical for many financial models. The advantages of the proposed method are that it allows incorporation of parameter uncertainty and does not rely on distributional assumptions. The finite sample properties are analyzed by an extensive Monte Carlo simulation. Finally, the technique is applied to the Madrid Stock Market index, IBEX-35.
PB Elsevier
SN 0167-9473
YR 2006
FD 2006
LK https://hdl.handle.net/10016/4739
UL https://hdl.handle.net/10016/4739
LA eng
DS e-Archivo
RD 26 jun. 2024