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The purpose of this paper is to examine the roles of earnings and book value (BV) in equity valuation.

The authors apply model’s explanatory power to analyze the roles of accounting data and test the hypotheses empirically with a sample of Chinese listed companies between 2004 and 2010.

The authors find that impact of accounting data on equity value is also dependent on profitability, but the behavior is non-monotonic. In the intermediate-profitability range, explanatory power of both earnings capitalization model and balance sheet model reach the peak, there are no significant differences between them. In the low-profitability range (small or negative profitability), explanatory power of balance sheet model is larger than earnings capitalization model. In the high-profitability range, explanatory power of balance sheet model is less than earnings capitalization model.

The results support that the role of BV is more stable in equity valuation. Moreover, this outcome provides reference for improving existing valuation model and setting accounting standard, and provides some empirical evidence for the practical application of BV in equity valuation.

Existing studies treat earnings as main variable of equity valuation, and BV is only added as a supplement. This paper compares roles of accounting earnings and BV in equity valuation, especially investigates the influence of BV in equity valuation, and fills up the deficiency in the related literature.

Early theoretical work on equity valuation suggests that equity prices are determined by variables such as dividends and growth in dividends. However, these “traditional” views have been challenged by recent studies that seem to indicate that equity prices are determined by book value and discounted future abnormal earnings. This paper employs panel data methodology and equity prices from Athens Stock Exchange empirically to compare the performance of the traditional and the more recent models of equity valuation. The results show that the performance of the Ohlosn (1995) model is quite similar to that of the traditional models even though in some cases Ohlson’s model performance appears to be superior.

The purpose of this paper is to survey the accounting concepts of valuation and the direction of accounting research in terms of development of valuation models. It also simulates some of the models. Moreover, the Dividend Discount Model, a financial model, is the foundation of a number of accounting based models and is discussed.

The objectives are achieved by surveying the literature for accounting models and empirical evidence for the model. The methodology also incorporates simulating the models under different conditions to find out the valuation predicted.

It was found out that the accounting models predict that accrual principles play a role in increasing the discrepancy between the book value and the market value of equity. Some of the recent valuation models, like the Feltham–Ohlson linear information model, incorporate accrual principles like conservatism. Though the empirical evidences are mixed for these models, it provides a theoretical framework to incorporate accrual principles in the accounting valuation models.

This paper provides practitioners with a snapshot of different models and their limitations.

This paper provides a comprehensive picture of the state of accounting valuation models and provides input for further development of these models.

This paper aims to propose an account of the use of numbers and mathematical formulae and, more generally, of the quantitative aspects in the qualitative equity valuation model of the American investor Philip A. Fisher who is considered to be one of the fathers of the qualitative equity valuation models.

A Conceptual analysis was conducted (Glasersfeld, 1992) of the four volumes published by Fisher between 1954 and 1980 (1958, 1960, 1975, 1980) in relation to his equity valuation process. On the basis of this analysis, a modelization of this author’s perspective on quantitative instruments was built.

A modelization to use quantitative data in a qualitative equity valuation model that is sufficiently detailed and useful for an asset manager is proposed.

What is propose is a qualitative analysis of quantitative elements in the thought of a qualitative author on the subject of equity valuation. It is believed that this paper could be of interest to all those who use or are involved in the development of qualitative models of equity valuation or business valuation. This work is also an example of how conceptual analysis – generally employed in the field of mathematics education research – can be used to build descriptive models of decision-making processes of individual investors, models designed to enable the reproduction/approximation of the conceptual operations of the investor.

The purpose of this paper is to focus on valuation practices applied by analysts to derive target price forecasts in Asian emerging markets. The key objective of this study is to understand valuation model preference of analysts and to compare the predictive utility of target price forecasts derived through heuristics-driven price-to-earnings (PE) model and theoretically sound discounted cash flow (DCF) model.

Each research report in the sample of 502 research reports has been studied in detail to understand the dominant valuation model (PE or DCF) applied by analyst to derive target price forecasts. These research reports have been issued on stocks trading in seven emerging markets including India, Malaysia, Indonesia, Taiwan, Philippines, Korea and Thailand during a six-year period starting 2008. Standard OLS and logit regression analysis has been performed to derive empirical findings.

The study finds that lower regulatory and reporting standards prevailing in emerging markets have no significant bearing on analyst choice of valuation model (PE or DCF). Time-series analysis suggests that emerging market analysts did not rely upon the usage of DCF model and preferred PE model during and immediately after the financial crisis of 2008. Multivariate regression results show weak evidence that PE model produces better results than DCF model after adjusting for the complexities associated with analyzing emerging market equities. The results imply that PE model, to some degree, is better equipped to capture market moods and sentiment in dynamic emerging markets rather than theoretically sound DCF model.

Most past studies on valuation model practices have focused on developed markets and this study provides a fresh perspective on analyst valuation model practices and performance in a new institutional setting of Asian emerging markets. The marginally better predictive utility of PE model as compared to DCF model is possibly a feature limited to Asian emerging markets.

Being a developing nation with huge opportunity of growth prospects the assessment of valuation models becomes important to have a more realistic value estimate. The purpose of this paper is to empirically examine the comparative accuracy and explanatory performance of discounted cash flow (DCF) and residual income model (RIM) valuation models for the Indian chemical industry and come up with a composite valuation model.

To achieve the objective of the study the authors first determine the intrinsic values using both the models. Comparisons of the models are based on prediction errors and the explanatory performance of market value on value estimates. The study uses panel regression to forecast estimates of earnings and measure explanatory performance. The authors examine the ability of the value estimates to explain cross-sectional variation in the observed market values. The study also uses GMM method for deriving robust estimators. Variables for the study are collected from the CMIE’s prowess data base (release 4). The authors consider all 1,075 BSE listed chemical companies for the purpose of the study. The study uses annual data points starting from 31 March 2002 to 31 March 2011.

The comparative framework shows that both Residual Income model and Composite Valuation model are superior to Discounted cash flow model and are equally likely. But since composite value estimates considers all bonafide informations of individual models, the estimates of Composite Valuation model becomes more reliable.

The study only compares and combines the two most widely used valuation models around the world. Future studies can be conducted using the third widely used valuation models, i.e. multiples and see the level of accuracy of individuals as well as the composite model.

As a concern very few research has been conducted in this area in India. This paper provides practitioners with a snapshot of the applicability of DCF and RIM valuation models. And also shows how a composite value estimate can improve accuracy.

This paper aims to empirically investigate the market-to-book/return on equity valuation model.

The authors use a worldwide commodities sector panel of 6,323 firms from 69 countries with annual observations from 1999 to 2010 to estimate panel ordinary least squares (OLS), instrumental variables (IV) and quantile regressions. They also measure the impact of return on equity on market-to-book uncovering value versus growth and positive versus negative profitability dimensions.

The new evidence is that the impact of return on equity on market-to-book is time-varying and declining across the years in the sample. There is positive and strong persistence in the market-to-book of companies in this sector worldwide, but value stocks are more persistent than growth stocks. The coefficient of return on equity is positive at the 10th percentile of the market-to-book, but it becomes negative for growth stocks at 90th percentiles. Conditional on negative profitability, the coefficient of return on equity on market-to-book is negative for growth stocks. The effect of the S&P500 volatility index (VIX) is negative, significant and large in magnitude, but declines in absolute value, as the quantiles increase toward the upper 90th percentile.

The commodities sector is important for countries that depend on it for development.

The paper provides a rich panel data approach, and the market-to-book/return on equity valuation model is naturally applied to the commodities sector, as this sector tends to have more tangibles relative to intangibles.

The purpose of this study is to investigate the role of book values, earnings, and future earnings in equity valuation by time, life cycle stage, and market uncertainty using samples of USA and Japanese companies.

This study employs Lubberink and Willett (2021) methodology in using log-linear models to estimate the value relevance of accounting numbers and follows Schaberl (2016) approach to measure %incremental value relevance. The study also includes future earnings in a basic valuation model (Ohlson, 1995) to explore the extent to which stock prices are forward looking.

This study finds a significant increase by time in the relative value relevance of a combined model with book values and earnings and a combined model with future earnings for both countries. However, the incremental value relevance of book values, earnings, and future earnings remain stable over time. The results by life cycle stage indicate that incremental value relevance of future earnings and earnings are more (less) pronounced for firms in the intro (mature) life cycle stage while the incremental value relevance of book values is highest for firms in the decline stage for both countries. The results by market uncertainty indicate that firms with high market uncertainty display higher incremental value relevance of book values for both countries. The results on future earnings are mixed as USA (Japan) firms with high (low) market uncertainty display more (less) incremental value relevance of future earnings.

The findings in this study enhance the merits of two basic financial statements (balance sheet and income statement) in a firm's equity valuation for potential investors and existing shareholders and document an additional role of future earnings information in reflecting a firm's stock price, which is beyond what book values and current earnings have already contributed.

This is the first study that uses log-linear models to estimate the value relevance of accounting numbers and investigates value relevance of accounting information in three views: time, life cycle stage, and market uncertainty.

This paper aims to investigate the relevance of two groups of valuations models as follows: the accounting models based on the residual income (RIM) and the standard market model, on equity price, return and volatility relevance.

The models are tested on companies traded on Palestine exchange from 2009 to 2018, using panel regression analysis. Two-price and two-return models derived from RIM to compare with the market model and four volatility models.

The standard RIM outperformed other models in equity price modeling. The dividend discount model (DDM) outperformed the rest of the models in terms of return estimation. However, the authors find that the market model can explain equity variance better than RIM and DDM models.

For investors, market beta does not necessarily capture all relevant factors of value and traditional financial statements are still important in providing relevant information and different models are used for different values perspectives (price, return and volatility).

Previous studies focus on comparing the price and return relevance of accounting-based models (RIM and cash flow models). Three aspects differentiate this paper and contribute to its originality, namely, the uniqueness of the context, incorporating the market model into the picture along with the accounting-based models and adding Volatility dimensions of relevance.

Outlines the valuation models of Ohlson (1995) and Feltham and Ohlson (1995), which relate share prices to accounting data, and develops a version which substitutes net value added for earnings. Tests it on 1978‐1995 US data and shows that it is better than the conventional model at explaining price. Recommends that future capital market research should consider net value added as an alternative to earnings for wealth measurement.