Adaptive Inference in Heteroscedastic Fractional Time Series Models-Reference-Cited by-同舟云学术

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Adaptive Inference in Heteroscedastic Fractional Time Series Models

Published:2020-06-29 Issue:1 Volume:40 Page:50-65
ISSN:0735-0015
Container-title:Journal of Business & Economic Statistics
language:en
Short-container-title:Journal of Business & Economic Statistics

Author:

Cavaliere Giuseppe¹²,Nielsen Morten Ørregaard³⁴,Robert Taylor A. M.⁵

Affiliation:

1. Department of Economics, University of Bologna, Bologna, Italy

2. Department of Economics, Exeter Business School, Exeter, UK

3. Department of Economics, Queen’s University, Kingston, ON, Canada

4. CREATES, Aarhus University, Aarhus, Denmark

5. Essex Business School, University of Essex, Colchester, UK

Funder

Social Sciences and Humanities Research Council of Canada

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Social Sciences (miscellaneous),Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/07350015.2020.1773275

Reference61 articles.

1. Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility

2. Analysing inflation by the fractionally integrated ARFIMA-GARCH model

3. Econometric analysis of realized volatility and its use in estimating stochastic volatility models

4. Unit Root Testing with Unstable Volatility

5. Long-Memory Processes

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4. Forecasting Electricity Generation from a Renewable and Low‐Carbon Matrix Using the Stochastic Volatility Process;International Journal of Energy Research;2024-01

5. Time-Series Forecasting: Unleashing Long-Term Dependencies with Fractionally Differenced Data;2023 IEEE 64th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS);2023-10-05

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