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Forecasting Markov-switching dynamic, conditionally heteroscedastic processes

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Publication:1770072
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DOI10.1016/j.spl.2004.02.004zbMath1096.62090OpenAlexW2107691814WikidataQ57941856 ScholiaQ57941856MaRDI QIDQ1770072

Xianqiang Yang

Publication date: 7 April 2005

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10036/29296

zbMATH Keywords

ARCHARFIMAstandard errorsMarkov-switchingpoint predictions


Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20)


Related Items

A regime switching long memory model for electricity prices, Directional Congestion and Regime Switching in a Long Memory Model for Electricity Prices


Uses Software

  • Ox


Cites Work

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  • Fractionally integrated generalized autoregressive conditional heteroskedasticity
  • Autoregressive conditional heteroskedasticity and changes in regime
  • Long memory processes and fractional integration in econometrics
  • Conditional Heteroskedasticity in Asset Returns: A New Approach
  • AN INTRODUCTION TO LONG-MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING
  • A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
  • A comparison of the forecast performance of Markov‐switching and threshold autoregressive models of US GNP
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