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Fourier DCC-GARCH/Evidence
Method evidence record

Fourier DCC-GARCH

The Fourier DCC-GARCH model extends Engle's Dynamic Conditional Correlation GARCH framework by embedding Fourier trigonometric terms in the conditional mean or variance equations. This allows the model to approximate smooth, gradual structural shifts in volatility dynamics and inter-asset correlations without requiring knowledge of the number or timing of break points.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Fourier Dynamic Conditional Correlation GARCH Model
Taxonomic method record · regression-model / econometrics
  • Engle, R. (2002). Dynamic conditional correlations: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business and Economic Statistics, 20(3), 339-350. · URL
  • Nazlioglu, S., Gormus, N. A., & Soytas, U. (2016). Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission analysis. Energy Economics, 60, 168-175. · DOI 10.1016/j.eneco.2016.09.009
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Curated claims

Claims persisted in the evidence ledger, each with its own assessment.

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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketDCC-GARCH modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketEGARCH modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketFourier GARCH Modelmachine-suggested · Relational suggestion, not evidence.Same method familyGARCH Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketVector Autoregressionmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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