Recursive Estimation of Volatility for High Frequency Financial Data

Statistika: Statistics and Economy Journal

Tomáš Cipra¹  Petr Vejmělka¹ 

[1] Charles University, Prague, Czech Republic;

关键词: garch;    high-frequency financial time series;    recursive estimation;    risk prediction;    volatility;   

DOI  :  

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown