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Nonlinear EGARCH model/Evidence
Method evidence record

Nonlinear EGARCH model

The Nonlinear EGARCH model extends Nelson's (1991) Exponential GARCH by allowing the news impact function to take a flexible nonlinear form, capturing asymmetric and nonlinear responses of conditional volatility to past shocks. It is widely used in financial econometrics to model leverage effects and complex volatility dynamics in asset returns.

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Source record

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Nonlinear Exponential Generalized Autoregressive Conditional Heteroscedasticity Model
Taxonomic method record · regression-model / econometrics
  • Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. · DOI 10.2307/2938260
  • Engle, R. F., & Ng, V. K. (1993). Measuring and testing the impact of news on volatility. Journal of Finance, 48(5), 1749–1778. · DOI 10.1111/j.1540-6261.1993.tb05127.x
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Related methods

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Taxonomic bucketARCH modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketEGARCH modelmachine-suggested · Relational suggestion, not evidence.Same method familyGARCH Modelmachine-suggested · Relational suggestion, not evidence.Same method familyStochastic Volatility Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketTGARCH modelmachine-suggested · Relational suggestion, not evidence.

Evidence status

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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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