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Autoregressive Models with Non-Causal ARCH Volatility | Synapse
March 3, 2026
Open Access
Autoregressive Models with Non-Causal ARCH Volatility
MB
Mauro Bernardi
University of Padua
GM
Gabriele Mingoli
Puntos clave
The analysis reveals distinct volatility characteristics of non-causal ARCH models, highlighting their complexity.
Key evidence includes significant deviations from traditional causal models in predicting financial data patterns.
An assessment employing autoregressive approaches illustrates non-causal effects on volatility dynamics across datasets.
These findings may improve financial modeling, though their application requires careful interpretation and validation.
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Bernardi et al. (Thu,) studied this question.
synapsesocial.com/papers/69a75f2ec6e9836116a2a612
https://doi.org/https://doi.org/10.2139/ssrn.6095631
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