Infinite-order, long-memory heterogeneous autoregressive models

DOI10.1016/j.csda.2013.08.009zbMath1506.62086OpenAlexW1966922585MaRDI QIDQ1623535

Dong Wan Shin, Eun-Ju Hwang

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2013.08.009

zbMATH Keywords

least squares estimatorrealized volatilityasymptotic propertyHAR-RV modelprediction mean-squared error

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (12)

Forecasting realized volatility: a review ⋮ Dynamic behavior of volatility in a nonstationary generalized regime-switching GARCH model ⋮ Tests for structural breaks in memory parameters of long-memory heterogeneous autoregressive models ⋮ Do we need the constant term in the heterogenous autoregressive model for forecasting realized volatilities? ⋮ Vector error correction heterogeneous autoregressive forecast model of realized volatility and implied volatility ⋮ Cointegrated dynamics for a generalized long memory process: application to interest rates ⋮ Bayesian estimation of Gegenbauer long memory processes with stochastic volatility: methods and applications ⋮ Detecting structural breaks in realized volatility ⋮ The functional central limit theorem and structural change test for the \(\mathrm{HAR}(\infty)\) model ⋮ An integrated heteroscedastic autoregressive model for forecasting realized volatilities ⋮ Forecasting the realized variance of the log-return of Korean won US dollar exchange rate addressing jumps both in stock-trading time and in overnight ⋮ A CUSUMSQ test for structural breaks in error variance for a long memory heterogeneous autoregressive model

Cites Work

• The Model Confidence Set
• Predicting volatility: getting the most out of return data sampled at different frequencies
• A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries
• Strong consistency of the stationary bootstrap under \(\psi\)-weak dependence
• Modelling and forecasting noisy realized volatility
• The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets
• Some mixing properties of time series models
• Consistent autoregressive spectral estimates
• A new weak dependence condition and applications to moment inequalities
• On same-realization prediction in an infinite-order autoregressive process.
• Long memory and nonlinearities in realized volatility: a Markov switching approach
• Autoregressive approximation in nonstandard situations: the fractionally integrated and non-invertible cases
• The Benefits of Bagging for Forecast Models of Realized Volatility
• The Volatility of Realized Volatility
• WEAK DEPENDENCE: MODELS AND APPLICATIONS TO ECONOMETRICS
• AUTOMATIC INFERENCE FOR INFINITE ORDER VECTOR AUTOREGRESSIONS

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