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Forecasts for leverage heterogeneous autoregressive models with jumps and other covariates

Title
Forecasts for leverage heterogeneous autoregressive models with jumps and other covariates
Authors
Choi, Ji-EunShin, Dong Wan
Ewha Authors
신동완
SCOPUS Author ID
신동완scopus
Issue Date
2018
Journal Title
JOURNAL OF FORECASTING
ISSN
0277-6693JCR Link

1099-131XJCR Link
Citation
JOURNAL OF FORECASTING vol. 37, no. 6, pp. 691 - 704
Keywords
asymmetryimplied volatilityjumpLHARX modelrealized volatilityvolatility index
Publisher
WILEY
Indexed
SSCI; SCOPUS WOS scopus
Document Type
Article
Abstract
For leverage heterogeneous autoregressive (LHAR) models with jumps and other covariates, called LHARX models, multistep forecasts are derived. Some optimal properties of forecasts in terms of conditional volatilities are discussed, which tells us to model conditional volatility for return but not for the LHARX regression error and other covariates. Forecast standard errors are constructed for which we need to model conditional volatilities both for return and for LHAR regression error and other blue covariates. The proposed methods are well illustrated by forecast analysis for the realized volatilities of the US stock price indexes: the S&P 500, the NASDAQ, the DJIA, and the RUSSELL indexes.
DOI
10.1002/for.2530
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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