Forecasting earnings and returns: a review of recent advancements

Jeremiah Green; Wanjia Zhao

doi:10.1016/j.jfds.2022.04.004

Forecasting earnings and returns: a review of recent advancements

Jeremiah Green
, Wanjia Zhao

Research output: Contribution to journal › Review Article › Research › peer-review

8 Citations (Scopus)

Abstract

We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting earnings and returns presents difficult challenges. In the context of these challenges, we discuss recent papers that confront the challenges and present promising advancements and paths for future research.

Original language	English
Pages (from-to)	120-137
Number of pages	18
Journal	Journal of Finance and Data Science
Volume	8
DOIs	https://doi.org/10.1016/j.jfds.2022.04.004
Publication status	Published - Nov 2022
Externally published	Yes

Keywords

Earnings
Forecasting
Machine learning
Measurement error
Returns
Uncertainty

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10.1016/j.jfds.2022.04.004Licence: CC BY-NC-ND

619809778-oaFinal published version, 415 KBLicence: CC BY-NC-ND

Cite this

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title = "Forecasting earnings and returns: a review of recent advancements",

abstract = "We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting earnings and returns presents difficult challenges. In the context of these challenges, we discuss recent papers that confront the challenges and present promising advancements and paths for future research.",

keywords = "Earnings, Forecasting, Machine learning, Measurement error, Returns, Uncertainty",

author = "Jeremiah Green and Wanjia Zhao",

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year = "2022",

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doi = "10.1016/j.jfds.2022.04.004",

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AU - Zhao, Wanjia

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AB - We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting earnings and returns presents difficult challenges. In the context of these challenges, we discuss recent papers that confront the challenges and present promising advancements and paths for future research.

KW - Earnings

KW - Forecasting

KW - Machine learning

KW - Measurement error

KW - Returns

KW - Uncertainty

UR - https://www.scopus.com/pages/publications/85130865456

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DO - 10.1016/j.jfds.2022.04.004

M3 - Review Article

AN - SCOPUS:85130865456

SN - 2405-9188

VL - 8

SP - 120

EP - 137

JO - Journal of Finance and Data Science

JF - Journal of Finance and Data Science

ER -

Forecasting earnings and returns: a review of recent advancements

Abstract

Keywords

Access to Document

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