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Modeling and forecasting realized volatility in German-Austrian continuous intraday electricity prices
Ciarreta, Aitor; Muniain, Peru; Zarraga, Ainhoa - In: Journal of forecasting 36 (2017) 6, pp. 680-690
Persistent link: https://www.econbiz.de/10011861404
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Forecasting and trading high frequency volatility on large indices
Liu, Fei; Pantelous, Athanasios A.; Mettenheim, … - In: Quantitative finance 18 (2018) 5, pp. 737-748
Persistent link: https://www.econbiz.de/10011907914
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Forecasting realized volatility : a Bayesian model-averaging approach
Liu, Chun; Maheu, John M. - In: Journal of applied econometrics 24 (2009) 5, pp. 709-733
Persistent link: https://www.econbiz.de/10003931571
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The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets
Busch, Thomas; Christensen, Bent Jesper; Nielsen, … - In: Journal of econometrics 160 (2011) 1, pp. 48-57
Persistent link: https://www.econbiz.de/10009242554
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Modeling and forecasting realized volatility : getting the most out of the jump component
Clements, Adam; Liao, Yin - 2013
Persistent link: https://www.econbiz.de/10009789511
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The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets
Busch, Thomas (contributor);  … - 2006
Persistent link: https://www.econbiz.de/10003341264
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Application of Persistent Homology in Forecasting Realized Volatility
Gobato Souto, Hugo - 2023
effectively incorporate persistent homology (PH) into neural network models to increase their forecast accuracy in predicting …), NBEATSx-VP demonstrates a minimum 9% improvement in forecast precision compared to benchmark models. Considering Quasi …
Persistent link: https://www.econbiz.de/10014353686
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Application of Persistent Homology in Forecasting Realized Volatility
Gobato Souto, Hugo - 2023
effectively incorporate persistent homology (PH) into neural network models to increase their forecast accuracy in predicting …), NBEATSx-VP demonstrates a minimum 9% improvement in forecast precision compared to benchmark models. Considering Quasi …
Persistent link: https://www.econbiz.de/10014354048
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Forecasting Realized Volatility : Does Anything Beat Linear Models?
R. Branco, Rafael; Rubesam, Alexandre; Zevallos, Mauricio - 2023
We evaluate the performance of several linear and nonlinear machine learning (ML) models in forecasting the realized volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a dataset that includes past values of the RV and...
Persistent link: https://www.econbiz.de/10014354851
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Forecasting exchange rate volatility : is economic policy uncertainty better?
Ruan, Qingsong; Zhang, Jiarui; Lv, Dayong - In: Applied economics 56 (2024) 13, pp. 1526-1544
Persistent link: https://www.econbiz.de/10014473121