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Unified Inference for Dynamic Quantile Predictive Regression

Christis Katsouris

arXiv 25 Sep 2023 · Econometrics

arXiv:2309.14160 · PDF · DOI · OpenAlex · Extracted main text

Abstract

This paper develops unified asymptotic distribution theory for dynamic quantile predictive regressions which is useful when examining quantile predictability in stock returns under possible presence of nonstationarity.

Citation extraction

45
references
65
in-text mentions
45
distinct cited
2
self-citations
5,310
main-text words

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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
1Liu, X., Long, W., Peng, L., and Yang, B (2023) A unified inference for predictive quantile regression1.00053100%
2Yang, B., Liu, X., Peng, L., and Cai, Z (2021) Unified tests for a dynamic predictive regression0.92843100%
3Kostakis, A., Magdalinos, T., and Stamatogiannis, M. P (2015) Robust econometric inference for stock return predictability0.64441100%
4Li, C., Li, D., and Peng, L (2017) Uniform test for predictive regression with ar errors0.64422100%
5Lee, J. H (2016) Predictive quantile regression with persistent covariates: Ivx-qr approach0.58531100%
6Chen, W. W., Deo, R. S., and Yi, Y (2013) Uniform inference in predictive regression models0.51121100%
7Fan, R. and Lee, J. H (2019) Predictive quantile regressions under persistence and conditional heteroskedasticity0.51121100%
8Kasparis, I., Andreou, E., and Phillips, P. C (2015) Nonparametric predictive regression0.51121100%
9Liu, X., Yang, B., Cai, Z., and Peng, L (2019) A unified test for predictability of asset returns regardless of properties of predicting variables0.51121100%
10Welch, I. and Goyal, A (2008) A comprehensive look at the empirical performance of equity premium prediction0.51121100%

Showing the top 10 of 45 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models0.40511