Robust econometric inference for stock return predictability

Alexandros Kostakis, Tassos Magdalinos, Michalis P. Stamatogiannis

Research output: Contribution to journalArticle

39 Citations (Scopus)
80 Downloads (Pure)

Abstract

This study examines stock return predictability via lagged financial variables with unknown stochastic properties. We propose a novel testing procedure that (1) robustifies inference to regressors’ degree of persistence, (2) accommodates testing the joint predictive ability of financial variables in multiple regression, (3) is easy to implement as it is based on a linear estimation procedure, and (4) can be used for long-horizon predictability tests. We provide some evidence in favor of short-horizon predictability during the 1927-2012 period. Nevertheless, this evidence almost entirely disappears in the post–1952 period. Moreover, predictability becomes weaker, not stronger, as the predictive horizon increases.
Original languageEnglish
Pages (from-to)1506-1553
Number of pages48
JournalReview of Financial Studies
Volume28
Issue number5
Early online date17 Dec 2014
DOIs
Publication statusPublished - 1 May 2015

Fingerprint

Inference
Stock return predictability
Predictability
Econometrics
Testing
Financial variables
Multiple regression
Persistence
Predictive ability

Keywords

  • stock return predictability
  • local asymptotic
  • persistent regressor
  • robust inference

Cite this

Kostakis, A., Magdalinos, T., & Stamatogiannis, M. P. (2015). Robust econometric inference for stock return predictability. Review of Financial Studies, 28(5), 1506-1553. https://doi.org/10.1093/rfs/hhu139

Robust econometric inference for stock return predictability. / Kostakis, Alexandros; Magdalinos, Tassos; Stamatogiannis, Michalis P.

In: Review of Financial Studies, Vol. 28, No. 5, 01.05.2015, p. 1506-1553.

Research output: Contribution to journalArticle

Kostakis, A, Magdalinos, T & Stamatogiannis, MP 2015, 'Robust econometric inference for stock return predictability', Review of Financial Studies, vol. 28, no. 5, pp. 1506-1553. https://doi.org/10.1093/rfs/hhu139
Kostakis, Alexandros ; Magdalinos, Tassos ; Stamatogiannis, Michalis P. / Robust econometric inference for stock return predictability. In: Review of Financial Studies. 2015 ; Vol. 28, No. 5. pp. 1506-1553.
@article{977fab8b9f5a438ba1f673320033de30,
title = "Robust econometric inference for stock return predictability",
abstract = "This study examines stock return predictability via lagged financial variables with unknown stochastic properties. We propose a novel testing procedure that (1) robustifies inference to regressors’ degree of persistence, (2) accommodates testing the joint predictive ability of financial variables in multiple regression, (3) is easy to implement as it is based on a linear estimation procedure, and (4) can be used for long-horizon predictability tests. We provide some evidence in favor of short-horizon predictability during the 1927-2012 period. Nevertheless, this evidence almost entirely disappears in the post–1952 period. Moreover, predictability becomes weaker, not stronger, as the predictive horizon increases.",
keywords = "stock return predictability, local asymptotic, persistent regressor, robust inference",
author = "Alexandros Kostakis and Tassos Magdalinos and Stamatogiannis, {Michalis P.}",
year = "2015",
month = "5",
day = "1",
doi = "10.1093/rfs/hhu139",
language = "English",
volume = "28",
pages = "1506--1553",
journal = "Review of Financial Studies",
issn = "0893-9454",
publisher = "Oxford University Press",
number = "5",

}

TY - JOUR

T1 - Robust econometric inference for stock return predictability

AU - Kostakis, Alexandros

AU - Magdalinos, Tassos

AU - Stamatogiannis, Michalis P.

PY - 2015/5/1

Y1 - 2015/5/1

N2 - This study examines stock return predictability via lagged financial variables with unknown stochastic properties. We propose a novel testing procedure that (1) robustifies inference to regressors’ degree of persistence, (2) accommodates testing the joint predictive ability of financial variables in multiple regression, (3) is easy to implement as it is based on a linear estimation procedure, and (4) can be used for long-horizon predictability tests. We provide some evidence in favor of short-horizon predictability during the 1927-2012 period. Nevertheless, this evidence almost entirely disappears in the post–1952 period. Moreover, predictability becomes weaker, not stronger, as the predictive horizon increases.

AB - This study examines stock return predictability via lagged financial variables with unknown stochastic properties. We propose a novel testing procedure that (1) robustifies inference to regressors’ degree of persistence, (2) accommodates testing the joint predictive ability of financial variables in multiple regression, (3) is easy to implement as it is based on a linear estimation procedure, and (4) can be used for long-horizon predictability tests. We provide some evidence in favor of short-horizon predictability during the 1927-2012 period. Nevertheless, this evidence almost entirely disappears in the post–1952 period. Moreover, predictability becomes weaker, not stronger, as the predictive horizon increases.

KW - stock return predictability

KW - local asymptotic

KW - persistent regressor

KW - robust inference

U2 - 10.1093/rfs/hhu139

DO - 10.1093/rfs/hhu139

M3 - Article

VL - 28

SP - 1506

EP - 1553

JO - Review of Financial Studies

JF - Review of Financial Studies

SN - 0893-9454

IS - 5

ER -