Forecasting realized volatility: a review (Q1622112)

scientific article; zbMATH DE number 6976417

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English	Forecasting realized volatility: a review	scientific article; zbMATH DE number 6976417

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instance of

scholarly article

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title

Forecasting realized volatility: a review (English)

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author

Dong Wan Shin

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published in

Journal of the Korean Statistical Society

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publication date

12 November 2018

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zbMATH Keywords

asymmetry

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HAR model

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long-memory

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market microstructure noise

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realized covariance

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realized variance

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heterogeneous autoregressive (HAR) model

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covariance matrix

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MaRDI profile type

Publication

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full work available at URL

https://doi.org/10.1016/j.jkss.2018.08.002

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cites work

High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data

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Out of sample forecasts of quadratic variation

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The Distribution of Realized Exchange Rate Volatility

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Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities

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Realized volatility forecasting and market microstructure noise

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Realized Volatility

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Modelling and forecasting noisy realized volatility

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Lassoing the HAR Model: A Model Selection Perspective on Realized Volatility Dynamics

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Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise

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Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading

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Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models

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An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: asymptotic distribution theory

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Estimating the quadratic covariation matrix from noisy observations: local method of moments and efficiency

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Exploiting the errors: a simple approach for improved volatility forecasting

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The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets

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On the Modelling and Forecasting of Multivariate Realized Volatility: Generalized Heterogeneous Autoregressive (GHAR) Model

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An integrated heteroscedastic autoregressive model for forecasting realized volatilities

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Forecasts for leverage heterogeneous autoregressive models with jumps and other covariates

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Pre-averaging estimators of the ex-post covariance matrix in noisy diffusion models with non-synchronous data

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The Volatility of Realized Volatility

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Forecasting realized volatility using a long-memory stochastic volatility model: estimation, prediction and seasonal adjustment

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A multiple indicators model for volatility using intra-daily data

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Multi-Scale Jump and Volatility Analysis for High-Frequency Financial Data

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Predicting volatility: getting the most out of return data sampled at different frequencies

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Volatility forecasting and microstructure noise

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The Model Confidence Set

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The Benefits of Bagging for Forecast Models of Realized Volatility

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A CUSUM test for a long memory heterogeneous autoregressive model

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Infinite-order, long-memory heterogeneous autoregressive models

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A CUSUMSQ test for structural breaks in error variance for a long memory heterogeneous autoregressive model

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Estimation of structural mean breaks for long-memory data sets

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Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity

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Microstructure noise in the continuous case: the pre-averaging approach

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Q3774629

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Unified discrete-time and continuous-time models and statistical inferences for merged low-frequency and high-frequency financial data

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Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?

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The functional central limit theorem and structural change test for the \(\mathrm{HAR}(\infty)\) model

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Realized Volatility: A Review

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A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries

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Do we need the constant term in the heterogenous autoregressive model for forecasting realized volatilities?

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Vast volatility matrix estimation for high-frequency financial data

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Quasi-maximum likelihood estimation of volatility with high frequency data

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Efficient estimation of stochastic volatility using noisy observations: a multi-scale approach

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Estimating covariation: Epps effect, microstructure noise

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A Tale of Two Time Scales

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Identifiers

zbMATH Open document ID

1406.62129

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Mathematics Subject Classification ID

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10.1016/J.JKSS.2018.08.002

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Sitelinks

Mathematics(1 entry)

mardi Publication:1622112