Predictive density estimators for daily volatility based on the use of realized measures

DOI10.1016/j.jeconom.2008.12.015zbMath1429.62465OpenAlexW2103194941MaRDI QIDQ302179

Valentina Corradi, Norman R. Swanson, Walter Distaso

Publication date: 4 July 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2008.12.015

zbMATH Keywords

diffusionskernelsmicrostructure noiseintegrated volatilityrealized volatility measures

Mathematics Subject Classification ID

Density estimation (62G07) Applications of statistics to actuarial sciences and financial mathematics (62P05) Stochastic models in economics (91B70)

Related Items (9)

Nonparametric kernel density estimation near the boundary ⋮ Out of sample forecasts of quadratic variation ⋮ Asymptotic inference about predictive accuracy using high frequency data ⋮ Forecasting volatility with support vector machine-based GARCH model ⋮ Robust bootstrap forecast densities for GARCH returns and volatilities ⋮ Realized volatility forecasting and market microstructure noise ⋮ Likelihood-based scoring rules for comparing density forecasts in tails ⋮ Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction ⋮ Specification and structural break tests for additive models with applications to realized variance data

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