The relevance of earning‐to‐price and ROE predictability for explaining Shenzhen stock exchange (SZSE), returns in China: A dynamic panel data approach

• Published date: 01 July 2021
• Author: Muhammad Usman Arshad
• Date: 01 July 2021
• DOI: http://doi.org/10.1002/jcaf.22503

Received: 21 April 2021 Accepted: 14 May2021

DOI: 10.1002/jcaf.22503

RESEARCH ARTICLE

The relevance of earning-to-price and ROE predictability for

explaining Shenzhen stock exchange (SZSE), returns

in China: A dynamic panel data approach

Muhammad Usman Arshad1,2

1School of Finance, Central University of

Finance and Economics, Beijing, China

2Department of Commerce, University of

Gujrat, Gujrat, Pakistan

Correspondence

MuhammadUsman Arshad, School of

Finance,Central University of Finance and

Economics,39 South College Road, Haid-

ianDistrict, Beijing 100081, P.R. China.

Email:usman.arshad@uog.edu.pk

Abstract

The fundamental valuation (FV) perspective has been extended to the Shenzhen

Stock Exchange (SZSE) in China by focusing on the role of forecasted earning-

to-price ratio and return on equity (ROE). Forecastingthe variables is being done

using a linear dynamic panel data technique. The findings of the two-step Gener-

alized Method of Moments (GMM) analysis indicate that the forecasted E/P ratio

and ROE significantly explain a portion of the variation in the SZSE stock return

and remain highly statistically significant after risk proxy variables are included.

Additionally, it confirms the existence of size, momentum, liquidity, and divi-

dend yield in the SZSE. This supports the usefulness of an FV perspective based

on the unique characteristics of the Chinese equity market in explaining stock

returns and their potential utility in forecasting future stock returns.

KEYWORDS

E/P Ratio, FRM, fundamental valuation approach, GMM, ROE, Shenzhen stock exchange

JEL CLASSIFICATION

G12, G15, G17

1 INTRODUCTION AND MOTIVATION

The efficient market theory and asset pricing models are

two of the most fundamental tenets of contemporary

finance theory. Despite widespread criticism of the asset

pricing models’ assumptions, it is paramount to restate

their theoretical and empirical implications to the field

of finance. Sharpe (1963,1964), Lintner (1965), and Black

(1972) developed the capital asset pricing model (CAPM),

which is a one-factor model in which beta can account for

asset return differences. The risk factor valuation approach

acknowledges the multidimensional nature of asset risk

and asserts that financial indicators capture a portion of

the systematic risk not captured by the CAPM. Fama and

French (1992,1993) pioneered this approach by develop-

ing a three-factor model based on the following variables:

CAPM beta, firm size, and firm value as formalized by

the book to market (BM), earnings to price, an asset to

price, and cash flow to price. The momentum effect, as pro-

posed by Jegadeesh and Titman (1993,2001), demonstrates

a strategy that induces to buy a stock that has a positive

historical return (win situation) and sell the stock which

has a negative historical return (loss situation) and provide

significant positive returns. Carhart (1997) added momen-

tum to Fama and French (1992) three-factor model, which

is now known as the four-factor model. Fama and French

(2015) transformed a five-factor model, which included

profitability and investment, into a three-factor model that

was more reliable and authenticated in capturing the vari-

ation in US stock returns.

Fama an d Frenc h (1992,2012) demonstrated that size

and BM as a value proxy were more predictive of future

94 © 2021 Wiley Periodicals LLC J Corp Account Finance. 2021;32:94–109.wileyonlinelibrary.com/journal/jcaf

ARSHAD 95

security returns than systematic risk (beta) estimates

prompted a large literature on the explanatory accuracy

of financial and accounting-based ratios. The role of

book-to-market and size as predictors of stock returns has

been explained primarily through the lens of a risk proxy

argument Al-Horani et al. (2003) and a market mispric-

ing argument (La Porta, 1996;Lakonishoketal.,1994).

Additionally, a new perspective has emerged from the

literature, which I refer to as the "fundamental valuation

(FV)" perspective (Berk, 1995,1997; Biddle & Hunt, 1999;

Clubb & Naffi, 2007; Cordeiro & André, 2018). This paper is

primarily concerned with the FV perspective.

Berk (1995,1997) proposed the FV perspective on

expected returns, hypothesizing that size, as formalized

through market capitalization, will be negatively related

to expected future stock returns because market value is

higher for firms having lower opportunity cost/required

rate of return. Berk (1995) demonstrated that size (market

capitalization) alone is unlikely to be a good predictor of

future stock returns, implying that BM as a measure of firm

value may be a more accurateproxy for profit expectations.

Clubb and Naffi (2007) extend the perspective of the FV

approach on expected future equity returns by considering

the importance of return on equity (ROE) and firm stock

returns as indicators of the BM changes when the rela-

tionship between accounting earnings and clean surplus

holds (Vuolteenaho, 1999,2002). They argue that the pre-

dictive ability of a current BM for expected equity returns

is increased by including estimation of the forecasted book

to market (FBM) and return on equity (FROE) as an addi-

tional explanatory variable.

Hu et al. (2019) demonstrated that Chinese stock mar-

ket regulations differ significantly from those in the United

States and other developed and developing economies.

They acknowledged that it is treated as an orderly market,

with a strict initial public offering (IPO) process, a predom-

inance of individual investors who investexclusively in “A”

class stocks, asymmetric information predominates in the

market, and the government determines the market’ssize.

Due to the unique market characteristics, several studies

that have been conducted used the earning to price (E/P)

ratio as a value measure. Cakici et al. (2017), Hsu et al.

(2018), Zhang et al. (2018), and Jianan Liu et al. (2019)all

documented a significant effect, while Chen et al. (2010)

and Hu et al. (2019) and reported an insignificant presence

of value measure.

The preceding work provides evidence that the pre-

dictability power of E/P as a superior component of value

measure and forecasted ROE to explain the stock variation

in SZSE has been ignored, based on the relationship’snon-

existence between firm financial indicators and its risk.

The current study makes three significant contributions to

the literature by focusing exclusively on this subject. First,

the author extends Clubb and Naffi (2007) FV perspective

by asserting how the predictability of ROE and future

earnings to price capture the stock returns variation in

addition to current earnings to price under the scope of

unique features of the Chinese equity market. Second,

the author contributes to the body of Chinese evidence

on stock return cross-sections by considering the impact

of both fundamental and risk-valuation variables in pro-

viding context for the Shenzhen Stock Exchange’s (SZSE)

cross-section of returns. Thirdly, this study contributes

to statistical analysis by incorporating Driscoll and Kraay

standard errors (DKSE), and Panel Corrected standard

errors (PCSE) under static panel estimation and system

GMM under dynamic panel estimation to examine the

SZSE market’s cross-sectional variation.

Finally, the fundamental approach variables (E/P, EPF,

and ROEF) were estimated using a robustness testto deter-

mine the consistency of the variables used in the funda-

mental and risk valuation (RV) approaches. Traditional

pricing models have been used to explain variations in the

SZSE market return and the formation of the following

variables: beta, size, E/P (instead of the more traditional

use of BM for the value component), momentum, dividend

yield, and liquidity. Both, fundamental and risk valuation

perspective are closely relevant, assuming that stocks are

rationally Priced. The primary distinction between these

perspectives is that FV is not predicated on the notion that

a variable must capture a specific risk factor to be useful as

a predictor of future returns.

The remainder of this study follows this pattern. Sec-

tion 2will discuss the literature review and hypothesis

development, which will help the author design a funda-

mental analysis. Section 3discusses the research method-

ology and design, including the population and sample

size, variable and model descriptions, and data analysis

technique. The results and discussion are discussed in

Section 4, while the conclusion and recommendation are

discussed in Section 5. Section 6discusses the limitations of

the study and establishes a direction for future research.

2 PREVIOUS RESEARCH AND

HYPOTHESIS DEVELOPMENT

Fama an d French (1992) concluded in their seminal article

that systematic risk, as quantified by beta, did not play a

statistically significant role in explaining expected future

equity returns. However, both size and BM were found

to be significantly related to future returns, both inde-

pendently and in combination. Additionally, they recom-

mended that BM’s relevance for forecasting future stock

returns could result from its relevance as a distress risk

measure or indicator that elucidates market irrationality