First published 10/3/2026, 12:36:15 PM · Last updated 10/3/2026, 12:36:15 PM

Volatility Modelling in GARCH Frameworks: A Comparative Analysis of Non-Gaussian Error Distributions with Skewed Parameters.

A journal article presenting a comparative study of non-Gaussian error distributions and skewed-parameter approaches for volatility modeling within GARCH frameworks. Publisher is listed as University of Alkafeel and no further details are included in the supplied excerpt.

Illustrative image: Faculty of Pharmacy - Alkafeel University — Ali Jalil22/Wikimedia Commons, CC BY-SA 4.0

Categories: science-and-space, economy-and-trade

Generated scores

Scores are based on the cited reporting and use a 1–10 scale. Read the methodology.

Confidence: 3/10How certain the assessment is based on the clarity and evidence in the cited reporting.
Geographic reach: 1/10How widely the event reaches, from a local area (1) to worldwide impact (10).
Global importance: 3/10The event's broader significance, from limited importance (1) to major global importance (10).
Impact magnitude: 2/10The scale or severity of the real-world impact, from minor (1) to extreme (10).
Positivity: 5/10How harmful or beneficial the event is, from strongly harmful (1) to strongly positive (10).
Urgency: 1/10How time-sensitive the event is, from low urgency (1) to immediate attention needed (10).

Why it matters

The paper provides a comparative analysis of methodological choices in GARCH volatility modeling as reported in the source.

Sources

Volatility Modelling in GARCH Frameworks: A Comparative Analysis of Non-Gaussian Error Distributions with Skewed Parameters.

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