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Jump variation estimation with noisy high frequency financial data via wavelets
Zhang, Xin; Kim, Donggyu; Wang, Yazhen - In: Econometrics 4 (2016) 3, pp. 1-26
This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...
Persistent link: https://www.econbiz.de/10011755339
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Jump variation estimation with noisy high frequency financial data via wavelets
Zhang, Xin; Kim, Donggyu; Wang, Yazhen - In: Econometrics : open access journal 4 (2016) 3, pp. 1-26
This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...
Persistent link: https://www.econbiz.de/10011568279
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Range-based volatility estimation and forecasting
Benčík, Daniel - 2014
In this paper, we analyze new possibilities in predicting daily ranges, i.e. differences between daily high and low prices. We empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to simple daily ranges and explore the use of these more...
Persistent link: https://www.econbiz.de/10011340612
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Conditional variance forecasts for long-term stock returns
Mammen, Enno; Nielsen, Jens Perch; Scholz, Michael; … - In: Risks 7 (2019) 4, pp. 1-22
squared return prediction errors gives an adequate approximation of the unobserved realised conditional variance for both the …
Persistent link: https://www.econbiz.de/10013200531
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Range-based volatility estimation and forecasting
Benčík, Daniel - 2014
In this paper, we analyze new possibilities in predicting daily ranges, i.e. differences between daily high and low prices. We empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to simple daily ranges and explore the use of these more...
Persistent link: https://www.econbiz.de/10010461231
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Conditional variance forecasts for long-term stock returns
Mammen, Enno; Nielsen, Jens Perch; Scholz, Michael; … - In: Risks : open access journal 7 (2019) 4/113, pp. 1-22
squared return prediction errors gives an adequate approximation of the unobserved realised conditional variance for both the …
Persistent link: https://www.econbiz.de/10012127861
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Range-based Volatility Estimation and Forecasting
Bencik, Daniel - Institut ekonomických studií, Univerzita Karlova v Praze - 2014
In this paper, we analyze new possibilities in predicting daily ranges, i.e. differences between daily high and low prices. We empirically assess efficiency gains in volatility estimation when using range-based estimators as opposed to simple daily ranges and explore the use of these more...
Persistent link: https://www.econbiz.de/10011099986
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Bayesian predictive distributions of oil returns using mixed data sampling volatility models
Virbickaite, Audrone; Nguyen, Hoang; Tran, Minh-Ngoc - 2023
such as Generalized Autoregressive Conditional Heteroskedastic (GARCH), Generalized Autoregressive Score (GAS), and … relevant financial/macroeconomic news into asset price movements. For inference and prediction, we employ an innovative … inclusion of exogenous variables is beneficial for GARCH-type models while offering only a marginal improvement for GAS and SV …
Persistent link: https://www.econbiz.de/10014331159
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Bayesian predictive distributions of oil returns using mixed data sampling volatility models
Virbickaite, Audrone; Nguyen, Hoang; Minh-Ngoc Tran - 2023
such as Generalized Autoregressive Conditional Heteroskedastic (GARCH), Generalized Autoregressive Score (GAS), and … relevant financial/macroeconomic news into asset price movements. For inference and prediction, we employ an innovative … inclusion of exogenous variables is beneficial for GARCH-type models while offering only a marginal improvement for GAS and SV …
Persistent link: https://www.econbiz.de/10014252427
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Forecasting financial and macroeconomic variables using data reduction methods: New empirical evidence
Kim, Hyun Hak; Swanson, Norman R. - In: Journal of Econometrics 178 (2014) P2, pp. 352-367
prediction model specification methods, and that using “hybrid” combination factor/shrinkage methods often yields superior …-spread variables in nonlinear prediction model specification. …
Persistent link: https://www.econbiz.de/10011052271