Rustam Ibragimov, Jihyun Kim, Anton Skrobotov
arXiv 1 Jun 2020 · Econometrics · publishedEconometric Theory (2023) · 2 citations (OpenAlex)
arXiv:2006.01191 · PDF · DOI · OpenAlex · Extracted main text
We propose two robust methods for testing hypotheses on unknown parameters of predictive regression models under heterogeneous and persistent volatility as well as endogenous, persistent and/or fat-tailed regressors and errors. The proposed robust testing approaches are applicable both in the case of discrete and continuous time models. Both of the methods use the Cauchy estimator to effectively handle the problems of endogeneity, persistence and/or fat-tailedness in regressors and errors. The difference between our two methods is how the heterogeneous volatility is controlled. The first method relies on robust t-statistic inference using group estimators of a regression parameter of interest proposed in Ibragimov and Muller, 2010. It is simple to implement, but requires the exogenous volatility assumption. To relax the exogenous volatility assumption, we propose another method which relies on the nonparametric correction of volatility. The proposed methods perform well compared with widely used alternative inference procedures in terms of their finite sample properties.
appendix boundary found by appendix_titled_section at “Online Supplementary Material” · 55% of the source is main text. Read the extracted text to check this.
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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Choi, Jacewitz \ Park (2016) `A reexamination of stock return predictability', Journal of Econometrics 192, 168–189 | 1.000 | 21 | 5 | 100% |
| 2 | Hansen (1995) `Regression with nonstationary volatility', Econometrica 63, 1113–1132 | 0.874 | 5 | 2 | 100% |
| 3 | Kim \ Meddahi (2020) Volatility regressions with fat tails | 0.843 | 3 | 3 | 100% |
| 4 | Phillips (1987) `Towards a unified asymptotic theory for autoregression', Biometrika 74, 535–547 | 0.811 | 4 | 2 | 100% |
| 5 | Campbell \ Yogo (2006) `Efficient tests of stock return predictability', Journal of Financial Econometrics 81, 27–60 | 0.737 | 3 | 2 | 100% |
| 6 | Chen \ Deo (2009) `Bias reduction and likelihood-based almost exactly sized hypothesis testing in predictive regressions using the restricted like… | 0.737 | 3 | 2 | 100% |
| 7 | Phillips \ Magdalinos (2009) `Econometric inference in the vicinity of unity' | 0.737 | 3 | 2 | 100% |
| 8 | Embrechts, Klüppelberg \ Mikosch (1997) Modelling Extremal Events for Insurance and Finance, Springer | 0.644 | 4 | 1 | 100% |
| 9 | Phillips \ Magdalinos (2007) `Limit theory for moderate deviations from a unit root', Journal of Econometrics 136, 115–130 | 0.644 | 4 | 1 | 100% |
| 10 | So \ Shin (1999) `Cauchy estimators for autoregressive processes with applications to unit root tests and confidence intervals', Econometric Theo… | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 66 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Robust Cauchy-Based Methods for Predictive Regressions | 0.981 | 18 | 6 |