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The Generalized Fisher Transformation: Finite-Sample Properties and Inference

Ilya Archakov, Peter Reinhard Hansen

arXiv 11 Jun 2026 · Econometrics

arXiv:2606.13864 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We study the finite-sample behavior of the Generalized Fisher Transformation (GFT), the parametrization of a correlation matrix $C$ by $γ(C)=\operatorname{vecl}\log C$. The GFT coordinates extend Fisher's transformation to dimension $n>2$: for elliptical data their finite-sample distributions are close to Gaussian. More strikingly, the coordinates are nearly uncorrelated and their covariance is largely invariant to $C$. This approximate orthogonality and invariance make GFT-based inference far better behaved in finite samples than inference based on sample correlations or element-wise Fisher transformed correlations, yielding estimation errors that are approximately Gaussian, weakly dependent, and nearly pivotal.

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Archakov, I. and P. R. Hansen (2021) A new parametrization of correlation matrices self0.9285380%
2McCracken, M. W. and S. Ng (2016) FRED-MD: A monthly database for macroeconomic research0.7373367%
3Fisher, R. A (1921) On the 'probable error' of a coefficient of correlation deduced from a small sample0.51121100%
4Andersen, T. G., T. Bollerslev, F. X. Diebold, and H. Ebens (2001) The distribution of realized stock return volatility0.40511100%
5Andersen, T. G., T. Bollerslev, F. X. Diebold, and P. Labys (2001) The distribution of realized exchange rate volatility0.40511100%
6Archakov, I., P. R. Hansen, and Y. Luo (2024) A new method for generating random correlation matrices self0.40511100%
7Fisher, R. A (1915) Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population0.40511100%
8Hansen, P. R. and Y. Luo (2023) Robust estimation of realized correlation: New insight about intraday fluctuations in market betas self0.40511100%
9Hotelling, H (1953) New light on the correlation coefficient and its transforms0.40511100%
10Browne, M. W. and A. Shapiro (1986) The asymptotic covariance matrix of sample correlation coefficients under general conditions0.000220%

Showing the top 10 of 15 scored citations.