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Record W37093154 · doi:10.1089/jicm.2022.0730

PRICE-EARNINGS RATIO, DIVIDEND YIELD, AND MARKET-TO-BOOK RATIO TO PREDICT RETURN ON STOCK MARKET: EVIDENCE FROM THE EMERGING MARKETS

2008· article· en· W37093154 on OpenAlexaboutno aff
Güler Aras, Mustafa Kemal Yılmaz

Bibliographic record

VenueJournal of global business and technology · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsDividend yieldPredictabilityEconomicsPredictive powerFinancial economicsStock marketEarnings yieldEmerging marketsEconometricsDividendStock (firearms)EarningsEarnings per sharePrice–earnings ratioDividend policyFinanceStatisticsMathematics

Abstract

fetched live from OpenAlex

ABSTRACT This study examines the predicability of stock returns in the 12 emerging stock markets by using price-earnings ratio, dividend yield, and market-to-book ratio as predictive variables during the period of 1997-2003. We analyse the predicability by deriving a new index value using the proper combination of these predictive variables and multi-regression models. We find that the predictability of stock returns in the emerging markets is variant. The market-to-book ratio stands to reveal significant results in terms of predicting stock returns for a one-year period among others for most of the emerging market countries. The dividend yield comes in at second place. The results of the validation tests also show that the forecasting power of the estimated model is fairly good. Finally, these evidences support the individual predictive power of some, but not all financial variables in the stock market. This causes much discussion on the effectiveness of the stock market. INTRODUCTION Economists and financial practitioners have sought to identify variables that predict stock returns in the market for the last two decades. They have looked at various metrics as future predictors of share price performance. They have found size, interest rate, beta, market-to-book ratio (MtB), price-earnings ratio (PfE), and dividend yield (DY) to be rather good indicators among many others. The aim of this study is to examine the ability of the MtB, P/E, and DY to forecast market returns in an integrated form. The use of MtB is motivated by the findings of Fama and French (1992) that shows the MtB ratio of individual stocks has the ability to explain cross-sectional variation in stock returns. We have also included a dividend and earning yield measure as independent variables in our estimation. Intuitively, P/E ratio, MtB ratio, and the DY could be viewed as a multiple that the market attaches to earnings, book value and dividend respectively. In determining market prices and earnings, book value and dividend would be useful for predicting the behaviour of future stock prices or returns. Thus, one would be able to construct profitable trading strategies based on earnings, book value, and dividend. According to the mispricing view, P/E effect states that stocks with low P/E ratios (or high EfP ratios) earn significantly higher returns than stocks with high P/E ratios (or low E/P ratios). Thus, there is an inverse relation between the P/E ratio and portfolio returns, and an investor could achieve systematically higher returns by investing the right stock having low P/E ratio. Then, the P/E could be a suitable fundamental variable to explain the cross-section of returns in the stock market. Similarly, the MtB effect states that securities with high ratios between its market value and its book or equity value, persistently obtain lower returns than those securities with low MtB ratios. One explanation for the market-to-book ratio's ability to predict returns is that book value proxy for future cash flows. Dividing current market price by a cash flow proxy produces a variable that is correlated with future returns. This correlation is greater when better-expected cash flow proxies be used. Coming to the DY, a high DY is a signal that the market is undervalued. The predictive power of DY stems from the role of dividends in capturing the permanent component of prices, whereas the P/E ratio is predictive due to earnings being a good measure of business conditions, which captures counter-cyclical risk aversion. On the other hand the DY, in some studies, is defined to be somewhat better at explaining variation in real returns on the value-weighted index. The slightly better ability of DY to explain value-weighted index returns may be related to the fact that a large fraction of the firms in the market do not pay dividends in the last years. However, in finite samples, using only dividends may be problematic because they are often manipulated, smoothed, or set to zero, making them potentially poor indicators of the true value-relevant cash flows in the future. …

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.020
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.476

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0030.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.221
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations28
Published2008
Admission routes1
Has abstractyes

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