Petr Vejmělka, Tomáš Cipra
Recursive Estimation of Volatility for High Frequency Financial Data
Číslo: 3/2021
Periodikum: Statistika
Klíčová slova: GARCH, high-frequency financial time series, recursive estimation, risk prediction, volatility
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Anotace:
The paper deals with recursive estimation of financial time series with conditional volatility. It surveys
the recursive methodology suggested in Hendrych and Cipra (2018) and adjusts it for various alternatives
of GARCH models which are usual in financial practice. Such a recursive approach seems to be suitable
for the dynamic estimation with high-frequency data. The paper verifies the applicability of recursive
algorithms of particular models to high-frequency data from the Czech environment, particularly in the context
of risk prediction.
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the recursive methodology suggested in Hendrych and Cipra (2018) and adjusts it for various alternatives
of GARCH models which are usual in financial practice. Such a recursive approach seems to be suitable
for the dynamic estimation with high-frequency data. The paper verifies the applicability of recursive
algorithms of particular models to high-frequency data from the Czech environment, particularly in the context
of risk prediction.