Judgment can spur long memory

We arrive at this conclusion by using a new family of models—the Long Memory Dynamic Judgmental Protocol (LMDJP)—where robust filtering and fractionally integrated auto-regressions are combined in an environment characterized by several players—namely, Forecast Producer, Forecast User, and Reality. Namely, we show that if judgment is parametrized as a deformation Likelihood function according to Lq-Likelihood methods, such a deformation affects (sometimes dramatically) the Power Spectrum, consequently inducing over-rejection in formal tests for no LM-effects based on the last. Our simulated and empirical evidence reveals that knowledge of the fractional integration parameter matters for the p-values of tests for spurious LM and, secondly, that the role of LM in belief formation is ambiguous.

Authors

Publication Details

Journal
Journal of Economic Dynamics and Control
Published
2024-11-28
DOI
https://doi.org/10.1016/j.jedc.2024.105005
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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article

Judgment can spur long memory

Emilio Zanetti Chini
Journal of Economic Dynamics and Control
Financial Risk and Volatility Modeling
article

Judgment can spur long memory

Emilio Zanetti Chini
article en

Abstract

We arrive at this conclusion by using a new family of models—the Long Memory Dynamic Judgmental Protocol (LMDJP)—where robust filtering and fractionally integrated auto-regressions are combined in an environment characterized by several players—namely, Forecast Producer, Forecast User, and Reality. Namely, we show that if judgment is parametrized as a deformation Likelihood function according to Lq-Likelihood methods, such a deformation affects (sometimes dramatically) the Power Spectrum, consequently inducing over-rejection in formal tests for no LM-effects based on the last. Our simulated and empirical evidence reveals that knowledge of the fractional integration parameter matters for the p-values of tests for spurious LM and, secondly, that the role of LM in belief formation is ambiguous.

Journal of Economic Dynamics and ControlVol. 170
Openalex Percentile: Top 71%
Financial Risk and Volatility Modeling
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