Recursive Estimation of Volatility for High Frequency Financial Data

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.