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Cited by 44Financial Risk and Volatility ModelingMarket Dynamics and VolatilityEconomics of Agriculture and Food Markets

The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.

The role of sudden variance shifts in predicting volatility in bioenergy crop markets under structural breaks

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Hasanov, Akram Shavkatovich, Burkhanov, Aktam Usmanovich, Usmonov, Bunyod, Khajimuratov, Nizomjon Shukurullaevich, Khurramova, Madina Mansur qizi·2024·Energy
DOI 10.1016/j.energy.2024.130535
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Abstract

Forecasting bioenergy feedstock commodity volatility has received significant attention due to its importance in biofuel production and household consumption. Several extreme events, including the COVID-19 pandemic, have sparked interest in studying the role of structural breaks on volatility modeling and prediction in these markets. This study extensively examines the prediction performance of econometric models at multiple horizons using a rolling-window approach, with and without accommodating structural changes. We exploit the ICSS algorithm to determine the in-sample estimation windows to accommodate structural breaks. We extend the procedure beyond GARCH-class models. Also, the detected break information defines the regime dummies. The study innovatively evaluates the prediction performance of specific GARCH-class models by incorporating binary variables for sudden shifts in unconditional variance. Our findings reveal that accounting for the endogenously detected structural breaks through the dummy variables leads to considerable forecast accuracy gains.

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Crossref · 10.1016/j.energy.2024.130535

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69 of 69 references verified0 citation errors · 0 not checkable

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Research works printed but not linked: 3

  1. Hasanov, 2012, Modeling inflation volatility: evidence from two post-Soviet economies, Int J Stat Sci, 12, 9
  2. Hosszejni, 2022, Efficient bayesian inference for stochastic volatility (SV), The "stochvol" R package version 3.2.0
  3. Sansó, 2004, Testing for change in the unconditional variance of financial time series, Rev Econ Financ, 4, 32

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Metadata

Authors
Hasanov, A. S., Burkhanov, A. U., Usmonov, B., Khajimuratov, N. S., & Khurramova, M. M. Q.
Affiliations
  • Monash University Malaysia (MY)
  • Tashkent State University of Economics (UZ)
Corresponding author
Hasanov, Akram Shavkatovich
ORCID
Venue
Energy
Publisher
Elsevier BV
Published
2024-04
Volume
293
Pages
130535
ISSN
0360-5442 (ISSN-L)
DOI
10.1016/j.energy.2024.130535
OpenAlex
W4391642684
Cited by
43
References
69
Citations by year
2026: 1 · 2025: 4 · 2024: 38
FWCI
15.37
Type
journal article
Language
en
Open access
Licence
Locations
  • Energy (publishedVersion, cc-by)
  • Monash University Research Portal (Monash University) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
Monash University Malaysia (B-2-2020)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Finance › Financial Risk and Volatility Modeling
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Market Dynamics and Volatility
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economics of Agriculture and Food Markets
Keywords
volatility forecasting, structural breaks, ICSS algorithm, GARCH models, rolling window forecasting, COVID-19 market impact

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