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Improving the accuracy: volatility modeling and forecasting using high-frequency data and the variational component
Kumar, Manish - In: Journal of industrial engineering and management : JIEM 3 (2010) 1, pp. 199-220
simple and threshold jumps and continuous variation yields a substantial improvement in volatility forecasting or not. The …
Persistent link: https://www.econbiz.de/10011899155
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Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction
Duong, Diep; Swanson, Norman R. - 2013
forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen … evidence on the predictive content of realized measures of jump power variations (including upside and downside risk, jump …
Persistent link: https://www.econbiz.de/10009771770
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Forecasting Nigerian stock market returns using ARIMA and artificial neural network models
Isenahd, Godknows M.; Olubusoye, Olusanya E. - In: CBN journal of applied statistics 5 (2014) 2, pp. 25-48
The study reports empirical evidence that artificial neural network based models are applicable to forecasting of stock … the artificial neural network based models outperformed the ARIMA based model in forecasting future developments of the … can be used as predictors for forecasting future values of the stock market returns given that the returns has memory of …
Persistent link: https://www.econbiz.de/10011488820
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Forecasting stock market dynamics using bidirectional long short-term memory
Park, Daehyeon; Ryu, Doojin - In: Romanian journal of economic forecasting 24 (2021) 2, pp. 22-34
Persistent link: https://www.econbiz.de/10012587123
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The memory of beta
Becker, Janis; Hollstein, Fabian; Prokopczuk, Marcel; … - In: Journal of banking & finance 124 (2021), pp. 1-13
Persistent link: https://www.econbiz.de/10012816442
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Conditional heteroskedasticity in the volatility of asset returns
Ding, Yashuang - 2021
Persistent link: https://www.econbiz.de/10013262866
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An application of a random level shifts model to the volatility of Peruvian stock and exchange rate returns
Ojeda Cunya, Junior Alex; Rodriguez, Gabriel - In: Macroeconomics and finance in emerging market economies 9 (2016) 1/3, pp. 34-55
Persistent link: https://www.econbiz.de/10011583531
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The memory of beta factors
Becker, Janis; Hollstein, Fabian; Prokopczuk, Marcel; … - 2019
Researchers and practitioners employ a variety of time-series processes to forecast betas, using either short-memory models or implicitly imposing infinite memory. We find that both approaches are inadequate: beta factors show consistent long-memory properties. For the vast majority of stocks,...
Persistent link: https://www.econbiz.de/10012105362
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DCC-HEAVY : a multivariate GARCH model with realized measures of variance and correlation
Xu, Yongdeng - 2019
This paper proposes a new class of multivariate volatility model that utilising high-frequency data. We call this model the DCC-HEAVY model as key ingredients are the Engle (2002) DCC model and Shephard and Sheppard (2012) HEAVY model. We discuss the models' dynamics and highlight their...
Persistent link: https://www.econbiz.de/10012009351
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A multivariate volatility vine copula model
Brechmann, E. C.; Heiden, M.; Okhrin, Y. - In: Econometric reviews 37 (2018) 1/5, pp. 281-308
Persistent link: https://www.econbiz.de/10012038690