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Long Memory, Realized Volatility and Heterogeneous Autoregressive Models
Author(s) -
Baillie Richard T.,
Calonaci Fabio,
Cho Dooyeon,
Rho Seunghwa
Publication year - 2019
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/jtsa.12470
Subject(s) - stylized fact , long memory , autoregressive model , econometrics , volatility (finance) , autoregressive fractionally integrated moving average , realized variance , setar , star model , mathematics , autoregressive integrated moving average , economics , statistics , time series , keynesian economics
The presence of long memory in realized volatility ( RV ) is a widespread stylized fact. The origins of long memory in RV have been attributed to jumps, structural breaks, contemporaneous aggregation, nonlinearities, or pure long memory. An important development has been the heterogeneous autoregressive ( HAR ) model and its extensions. This article assesses the separate roles of fractionally integrated long memory models, extended HAR models and time varying parameter HAR models. We find that the presence of the long memory parameter is often important in addition to the HAR models.