Economics, Econometrics and Finance
5 years ago

New method guarantees accurate confidence intervals for financial predictions.

arXiv (Cornell University)
Score Permutation Based Finite Sample Inference for Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Models
Balázs Csanád Csáji

Paper Summary

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The researchers developed a new method called ScoPe to create confidence regions for GARCH models without making additional assumptions. By perturbing the score function with randomly permuted residuals, ScoPe produces exact confidence regions with no need for extra assumptions about moments. This method was tested on simulated and stock market data, showing its effectiveness compared to other approaches like asymptotic theory and bootstrap methods.