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  • Search: subject:"Long-memory stochastic volatility model"
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Year of publication
Subject
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ARCH model 1 ARCH-Modell 1 Asymptotic normality 1 Bias reduction 1 Estimation theory 1 High Frequency Data 1 Least absolute deviation estimator 1 Long Memory Stochastic Volatility Model 1 Long-memory stochastic volatility model 1 Realized Volatility 1 Risikomaß 1 Risk measure 1 Sample quantile 1 Sampling 1 Sampling window method 1 Schätztheorie 1 Seasonal Adjustment 1 Stichprobenerhebung 1 Stochastic process 1 Stochastischer Prozess 1 Value-at-Risk 1 Volatility 1 Volatilität 1 local Whittle estimation 1 long memory stochastic volatility model 1
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Online availability
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Free 1 Undetermined 1
Type of publication
All
Book / Working Paper 2 Article 1
Type of publication (narrower categories)
All
Article in journal 1 Aufsatz in Zeitschrift 1
Language
All
English 2 Undetermined 1
Author
All
Deo, Rohit 1 Frederiksen, Per 1 Ho, Hwai-chung 1 Hurvich, Clifford 1 Lu, Yi 1 Nielsen, Morten Ørregaard 1
Institution
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EconWPA 1 School of Economics and Management, University of Aarhus 1
Published in...
All
CREATES Research Papers 1 Econometrics 1 Journal of econometrics 1
Source
All
RePEc 2 ECONIS (ZBW) 1
Showing 1 - 3 of 3
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Sample quantile analysis for long-memory stochastic volatility models
Ho, Hwai-chung - In: Journal of econometrics 189 (2015) 2, pp. 360-370
Persistent link: https://www.econbiz.de/10011504558
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Bias-reduced estimation of long memory stochastic volatility
Frederiksen, Per; Nielsen, Morten Ørregaard - School of Economics and Management, University of Aarhus - 2008
We propose to use a variant of the local polynomial Whittle estimator to estimate the memory parameter in volatility for long memory stochastic volatility models with potential nonstation- arity in the volatility process. We show that the estimator is asymptotically normal and capable of...
Persistent link: https://www.econbiz.de/10005440062
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Forecasting Realized Volatility Using a Long Memory Stochastic Volatility Model: Estimation, Prediction and Seasonal Adjustment
Deo, Rohit; Hurvich, Clifford; Lu, Yi - EconWPA - 2005
We study the modeling of large data sets of high frequency returns using a long memory stochastic volatility (LMSV) model. Issues pertaining to estimation and forecasting of large datasets using the LMSV model are studied in detail. Furthermore, a new method of de-seasonalizing the volatility in...
Persistent link: https://www.econbiz.de/10005556335
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