Improving forecasts with the co-range dynamic conditional correlation model

DOI10.1016/J.JEDC.2019.103736OpenAlexW2970386939MaRDI QIDQ2338532

Marcin Fałdziński, Piotr Fiszeder

Publication date: 21 November 2019

Published in: Journal of Economic Dynamics \& Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jedc.2019.103736

zbMATH Keywords

simulation studyGARCH modelvolatility modelscovariance forecastingcurrency ratesrange-based models

Mathematics Subject Classification ID

Game theory, economics, finance, and other social and behavioral sciences (91-XX)

Cites Work

• Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
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• ARCH models and financial applications
• Multivariate GARCH estimation via a Bregman-proximal trust-region method
• Generalized autoregressive conditional heteroscedasticity
• A multivariate conditional autoregressive range model
• Multivariate rotated ARCH models
• Evaluating Volatility and Correlation Forecasts
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• Model selection tests for nonlinear dynamic models
• Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range
• Handbook of Volatility Models and Their Applications
• Modeling and Forecasting Realized Volatility

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