Residual Income Valuation Model Research Articles

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Different equity valuation models in theory provide identical estimates of equity intrinsic values if they are implemented with consistent assumptions. In practice, it is not unusual to obtain different value estimates from different models. Prior research on the comparison between multiples-based valuation model and flowsbased valuation models are quite limited. This research contributes to the literature by comparing the accuracy and reliability of three flows-based valuation models (discount dividend model, discounted free cash flow model, residual income valuation model) and multiples-based valuation model using one-year forward forecasted earning (PE1). For the analysis, all models are tested for bias, accuracy and explainability using t-tests, Wilcoxon tests and OLS regressions with a large sample of 40.547 observations from U.S public firms during the period from 2010 to 2020. Results show that PE1 value estimates are more accurate and reliable than that of flows-based models; and among flows-based models, residual income valuation model performs best. This research provides evidence for the performance and usage of such models to support sell-side equity analysts while making decisions of which model to use.

Modeling the Impact of Accounting Conservatism on Information Behaviour in Equity Valuation Based on PLS-SEM

Based on residual income valuation models, this study used PLS-SEM with a formative approach to investigate the moderating effects of conservative policies on the relation between accounting information of the current and lagged periods with the equity value of companies listed on the Tehran Stock Exchange. The sample consisted of 149 companies from 2012 to 2019. The moderating effect of conditional / unconditional accounting conservatism on the relation between current/lagged accounting information and equity value is insignificant at the 10% level. In contrast, conditional conservatism has a significant relation with current/lagged accounting information, current/lagged market information, and equity values. Unconditional conservatism has significant relation with current/lagged accounting information, lagged market information, and equity values. Unconditional conservatism, however, has no significant relation with the current market information. Referring to Ohlson's vision (1995) on the expected long-term convergence between book value and market equity value, this paper's findings show that the current/lagged book value constitutes the structure of linear dynamics used in the residual income valuation model; therefore, the dynamics in residual income evolve on the dynamics of book value and market equity value.

Bankruptcy Risk in Discounted Cash Flow Equity Valuation

We investigate the importance of bankruptcy risk in discounted cash flow (DCF) equity valuation. Our analyses first show how bankruptcy risk is incorporated in DCF valuation, where investment risk is captured by cash flow certainty equivalents. Within this general setting, we find that bankruptcy risk can be captured by discounting factors incorporating period-specific bankruptcy probabilities, allowing the numerators in a DCF valuation model to follow a binary random walk. Elaborating a model of this kind, we assess the value of the equity holders’ limited liability right (the equity holders’ right to hand over the firm to its creditors if bankruptcy occurs). Two valuation models commonly used in academic research and professional practice—the Dividend Discount Model (DDM) and the Residual Income Valuation (RIV) model—are addressed specifically. Our analyses show that bankruptcy probabilities are important for the estimation of the value drivers in both models. Even if bankruptcy probabilities are as low as 0.02, equity values might be severely exaggerated if bankruptcy risk is ignored in DDM or RIV. In particular, this holds for firms expected to have high future growth (conditioned on firm survival). For the RIV model to properly capture bankruptcy risk, we identify “bankruptcy event accounting principles” and an additional term that must be included in the model. We also show that bankruptcy risk under certain conditions can be handled through a specific calibration of the discounting rate/-s in all DCF models, allowing the value drivers—i.e., future dividends or residual income—to be forecasted conditioned on firm survival.

Global Diversification and the Cost of Equity

The conventional view in the standard finance textbooks is that organizational form does not matter for a firm’s cost of capital because firm diversification reduces only idiosyncratic risk and not systematic risk. In this study, we investigate the effect of global diversification on the ex-ante cost of equity implied by the residual income valuation model (Ohlson, Earnings, book value and dividends in security valuations. Contemporary Accounting Research, 11(2), 661–687, 1995), using a sample of US firms from 1997 to 2019. Employing the empirical approach developed in Easton et al. (Using forecasts of earnings to simultaneously estimate growth and the rate of return on equity investment. Journal of Accounting Research, 40(3), 657–676, 2002), our results suggest that global diversification reduces the cost of equity capital for both single-segment firms and multi-segment firms. Our results highlight the effect of global diversification on the equity risk reduction, which may explain the increasing proliferation of foreign operations among US firms — a trend that neither the cash flow effect nor the capital structure effect proposed in previous studies can explain.

Market share-prices versus their fundamental values: the case of the New York stock exchange

ABSTRACT The accounting valuation model suggests that the differences between predicted, and market shares-prices are considered as valuation errors while the finance valuation approach proposes that these differences are due to the sentiment of investors. In this paper, we use a new version of the residual income valuation model using American data to calculate the fundamental value of a stock and then examine whether price deviations from their fundamental values are due to macroeconomic or psychological factors. The results show that these differences are explained by important macroeconomic and psychological variables.

A New Investment Strategy with Economic Cycle Alternations Based on Residual Income Valuation Model: Empirical Results from Taiwan Stock Markets

The purpose of this research is an attempt to present a mixed model based on the residual income valuation model, where two new factors, business cycles and financial items, are added. We offer a practical investment opinion by which investors and fundamental analysts can either establish or adjust their portfolios if there is an effort made to reverse the present economic atmosphere due to the ongoing COVID-19 pandemic.We find that the items in financial reports don’t have the same impacts for different business cycles. However, tax has a significantly positive sign when economies are expanding or contracting.

A state space framework for the residual income valuation model of stock prices

We assess the empirical implications of the valuation model for equity prices developed in Ohlson (Contemp Account Res 11(2):661–687, 1995), by accounting for residual income information dynamics. A key assumption of the Ohlson (1995) residual income model stipulates that next period $$t+1$$ residual income is a linear function of current period t residual income and a latent variable referred to as ‘other information’. This ‘other information’, assumed known in the current period t, contains information on next period $$t+1$$ abnormal earnings not reflected in current period t abnormal earnings. Previous literature has proxied this ‘other information’ variable with consensus analysts’ forecasts of earnings. In this study, we propose to estimate this latent ‘other information’ variable using a state space framework. Our method obviates the need for analysts’ earnings forecasts. We estimate the valuation model, within the embedded state space framework, using the Kalman filter recursive procedure. We estimate the model across a sample of stocks in the Dow Jones 30 and S&P 500 indices. We compare the model performance to a benchmark two-step regression approach used in previous work. Performance yardsticks indicate that our state space estimation approach shows promise in valuing stocks and predicting next period $$t+1$$ residual income relative to the benchmark approach.

The Role of Assumptions in Ohlson Model Performance: Lessons for Improving Equity-Value Modeling

In this paper, we test whether the short-run econometric conditions for the basic assumptions of the Ohlson valuation model hold, and then we relate these results with the fulfillment of the short-run econometric conditions for this model to be effective. Better future modeling motivated us to analyze to what extent the assumptions involved in this seminal model are not good enough approximations to solve the firm valuation problem, causing poor model performance. The model is based on the well-known dividend discount model and the residual income valuation model, and it adds a linear information model, which is a time series model by nature. Therefore, we adopt the time series approach. In the presence of non-stationary variables, we focus our research on US-listed firms for which more than forty years of data with the required cointegration properties to use error correction models are available. The results show that the clean surplus relation assumption has no impact on model performance, while the unbiased accounting property assumption has an important effect on it. The results also emphasize the uselessness of forcing valuation models to match the value displacement property of dividends.

Investor sentiment effects on share price deviations from their intrinsic values based on accounting fundamentals

We investigate the existence of evidence of investor sentiment on share price deviations from their intrinsic values across two sentiment regimes of shares market: the low-to-normal and the excess one. We use the residual income valuation model to calculate the intrinsic values of shares based on accounting fundamentals and we suggest a panel data threshold model to capture the sentiment regimes of the market, using as threshold variable alternative investor sentiment indices. The suggested model enables us, first, to endogenously identify from the data the threshold value of a sentiment index triggering market sentiment regime shifts and, based on it, to examine if the effects of investor sentiment on share prices across the above two sentiment regimes are in accordance to the theory. Application of the model to UK data shows that investor sentiment influences positively share prices in the low-to-normal and negatively in the excess one. We also show that investor sentiment dominates risk premium effects on shares characterized by low book-to-market, and dividend- and earnings-to-price ratios. The above results are consistent with the predictions of the sentiment hypothesis.

The Role of a Latent Value-Relevant Measure in Tracking and Predicting Stock Returns: A FAVAR Approach

This paper attempts to estimate and study the role of 'other information', as posited in the residual income valuation model of Ohlson (1995), for tracking and predicting future returns of the S&P 500. 'Other information' is an unobserved variable and defined as a summary of value-relevant information about events and their effect on future profitability, which is captured in a company's current stock price and returns, but not yet reflected in a company's current financial statements. This suggests a potential to predict subsequent returns. Previous literature has found that traditional valuation metrics (e.g. B/P, E/P, and D/P ratios) have poor predictive power. In this study, we apply a factor augmented vector autoregression (FAVAR) to estimate this value-relevant latent variable and assess its predictive performance. The FAVAR is a suitable model because it enables us to analyze and quantify the linkages of stock market value, profitability, and unobserved factors that are broadly captured by big data. We use a two-step principal components estimation approach to extract the unobserved factors of 78 informational variables from financial market, accounting, investor and consumer sentiment, and macroeconomic data. Our analysis shows that, in comparison to competing measures, the estimated latent value-relevant variable can track contemporaneous stock returns and has statistically reliable power to predict both future real stock returns and excess returns over a Treasury Bill rate, both in- and out-of-sample.

A State Space Framework for the Residual Income Valuation Model of Stock Prices

We assess the empirical implications of the valuation model for equity prices developed in Ohlson (1995), by accounting for residual income information dynamics. A key assumption of the Ohlson (1995) residual income model stipulates that next period t + 1 residual income is a linear function of current period t residual income and a latent variable referred to as ‘other information’. This ‘other information’, assumed known in the current period t, contains information on next period t+1 abnormal earnings not reflected in current period t abnormal earnings. Previous literature has proxied this ‘other information’ variable with consensus analysts’ forecasts of earnings. In this study, we propose to estimate this latent ‘other information’ variable using a state space framework. Our method obviates the need for analysts’ earnings forecasts. We estimate the valuation model, within the embedded state space framework, using the Kalman filter recursive procedure. We estimate the model across a sample of stocks in the Dow Jones 30 and S&P 500 indices. We compare the model performance to a benchmark two-step regression approach used in previous work. Performance yardsticks indicate that our state space estimation approach shows promise in valuing stocks and predicting next period t+1 residual income relative to the benchmark approach.

An empirical assessment of proposed solutions for resolving scale problems in value relevance accounting research

AbstractWe implement the most common empirical specifications, with different approaches to control for scale problems, used in studies on the value relevance of accounting information. We study whether the results offered by these specifications are consistent with the residual income valuation model and with the Burgstahler and Dichev option‐style valuation framework. Undeflated and per‐share specifications offer results that are more in line with both benchmarks. Other deflated specifications and approaches deviate, to different extents, from the expectations of both frameworks. We interpret these deviations as signs of misspecification.

The pricing accuracy of alternative equity valuation models: Scandinavian evidence

AbstractIn many decision contexts, there is a need for benchmark equity valuations, based on simplified modeling and publicly available information. Prior research on U.S. data however shows that the accuracy of such valuation models can be low and sensitive to the choice of model specifications and value driver predictions. In this paper, we test the applicability and pricing accuracy of three fundamental valuation (dividend discount, residual income, and abnormal earnings growth) models, all based on forecasts of company dividends, earnings, and/or equity book values. Extending prior research, we apply these models to Scandinavian firms with accounting data from the period 2005–2014, explicitly testing two approaches for the prediction of the value drivers—exogenously forecasted numbers versus projected historical numbers. Given access to the forecasted value drivers, the dividend discount model comes out as the most accurate valuation model. In particular, this holds in a comparison between the most parsimonious model specifications. The residual income valuation model generates the best pricing accuracy given the prediction of value drivers based on historical financial numbers. Notably, we observe pricing errors that in general are lower than what has been reported in prior U.S.‐based research for the dividend discount and the residual income valuation models. The pricing accuracy of the abnormal earnings growth models is surprisingly weak in the Scandinavian setting. However, these models improve somewhat after a couple of complexity adjustments, in particular with value driver predictions based on the projected history setting.

Can a Hybrid Method Improve Equity Valuation? An Empirical Evaluation of the Ohlson and Johannesson (2016) Model

ABSTRACT This paper investigates the validity and usefulness of “hybrid” valuation models. We recast the model in Ohlson and Johannesson (2016) as a hybrid of the Dividend Discount Model and an earnings-based price multiple model, and develop a new hybrid model that generalizes the Residual Income Valuation Model. After validating the theoretical properties of these models' unique parameters, we assess the usefulness of the hybrid models in two applications. In application one, we find that intrinsic values from the hybrid models are more accurate than those from common discounted models or price multiple models. These improvements are attributable to the hybrid models' ability to incorporate stock price and more realistic assumptions about growth. In application two, we find that the implied cost of equity from the hybrid models better captures systematic risks and key idiosyncratic risks, and captures expected returns. These results demonstrate the validity and usefulness of hybrid valuation models. JEL Classifications: G12; G14; G17; G31; M41. Data Availability: The data used are publicly available from the sources cited in the text.

The Cross-Section of Expected Stock Returns: New Evidence from an Emerging Market

ABSTRACTOver 300 factors have been found to explain the cross-section of expected stock returns. Empirical studies also show that findings from multifactor asset-pricing models have not been consistent in an emerging market. Using DuPont analysis and a residual income valuation model for 284 nonfinancial companies on Ho Chi Minh Stock Exchange during the period 2008–2014, findings suggest that the return on equity and its change are informative for stock returns in Vietnam. In addition, the level of capital turnover, financial cost ratio (FCR), and changes in capital and in the FCR contain incremental explanatory power for stock returns.

Value-relevance of disclosure: risk factors and risk management in Brazilian firms

ABSTRACT This study investigated whether the disclosure in accounting reports of information on risk and its management affects, at the margin, firm valuations in the Brazilian capital market. It questioned the existence of value relevance in the disclosure of information related to risk factors and risk management structures. The importance of the topic arises from the documentation that disclosure on risk factors plays a statistically significant role in valuing firms in a context marked by economic and political uncertainty, as is the case of the Brazilian market. The findings confirmed that information about risk shows informational relevance for firm valuations. Information on risk management in a firm, in turn, was not shown to be significant in terms of affecting company share valuations. The investigation of detailed reports with different risk factors indicated that individualized information shows different degrees of relevance for company valuations. It is inferred that the disclosure of risk factors affects the perception of investors, who also base their estimates of return on the availability and detail of such information. It is also observed that information on risk management structure was not shown to be value relevant; moreover, few firms published information on the establishment of this type of entity in their management structures. The residual income valuation (RIV) model (Ohlson, 1995) was applied using regressions with panel data estimation related to the three years covering 2012 to 2014. The sample, which was randomly delimited, was formed of 100 companies. The data on disclosure of risk and disclosure of risk management were collected from the companies’ Reference Forms, available from the website of the São Paulo Stock, Commodities, and Futures Exchange (BM&FBOVESPA). As an impact on the area of knowledge, broader discussions are expected regarding the utility of disclosure on the topic related to risk factors and the existence of a specific body responsible for risk management in firms, according to investors’ perceptions. It also contributes by providing evidence about the quality of disclosure related to risk (factors and management) and the perception of the capital market regarding the informativeness and relevance of such elements.

Impact of Corporate Disclosure on Cost of Equity Capital in Vietnam

The objective of the paper is to test the impact of corporate disclosure on the cost of equity capital for firms listed on Vietnam’s stock market. We use the Botosan (1997) scoring methodology and the residual income valuation model to measure disclosure level and the implied cost of equity capital. Our findings suggest that, taking into account other determinants, disclosure has a significant reducing impact on the cost of equity capital.

Relevância da informação contábil em empresas dos Brics e EUA

A busca por informações contábeis relevantes tem sido intensa pelos órgãos normalizadores nos últimos anos, os quais têm buscado estabelecer normas que tornem a informação contábil relevante e possa ser utilizada de forma segura no processo decisório, principalmente considerando as decisões relacionadas ao mercado de capitais. Nessa linha, James Ohlson propôs modelos de avaliação de empresas baseados em números contábeis. O objetivo deste estudo é verificar as diferenças na Relevância da Informação Contábil no mercado de capitais dos países Brasil, Rússia, Índia, China e África do Sul (BRICS) e Estados Unidos da América (EUA), a partir dos dados disponíveis nas Bolsa de Valores destes países, por meio dos modelos Residual Income Valuation (RIV) e Abnormal Earnings Growth (AEG) propostos por Ohlson (1995; 2005). Por meio da Regressão com Dados em Painel, concluiu-se que as variáveis de cada país apresentam comportamento diferente no tocante a influência das mesmas no mercado de capitais, pois além de apresentarem coeficientes distintos, houve extensa variação do R2, sendo 0,02 no Brasil, para o modelo AEG e 0,79 na China para o modelo RIV. Quanto à verificação de qual modelo (RIV ou AEG) melhor se adapta à realidade de cada país, observou-se que no Brasil e África do Sul o modelo AEG apresentou maior ajuste, já na Rússia e China o modelo RIV foi mais adequado, tanto para variáveis defasadas pelo Preço em t-1, quanto para as não defasadas, pois conta com R2 mais expressivo e valor mais baixo para Critério de Informação de Akaike. Para os EUA e Índia, para variáveis não defasadas, o AEG é o melhor modelo para Índia e RIV para os EUA. Já com variáveis defasadas, o resultado se inverte.

Are Top Management Networking Skills Valuable? An Empirical Investigation of US Companies in the Context of Residual Income Valuation Model

This study investigates the impact of networking skills on company value by using the residual income model. We examine U.S. companies that constitute Standard and Poor’s 1500 index for the period 2002-2015 and we provide evidence that networking skills are significant part of company value. The evidence is robust after taking account of endogeneity. This study links the value relevance concept with social capital and provides support to resource dependence theory and social exchange theory.

Inferring Aggregate Market Expectations from the Cross-Section of Stock Prices

Motivated by the residual income valuation model of Ohlson (1995), we introduce a new approach to forecasting market returns that combines the cross-section of dividends, earnings, and book values to explain current stock prices and extract aggregate expected returns. Our measure of market return expectations is strongly correlated with popular ex ante equity premium measures and business cycle variables. It portends a significant fraction of the time-series variation in stock market returns at horizons of one month to two years. Consistent with the theory on which our measure is based, the predictability that we uncover is particularly strong at longer return forecasting horizons, where it dominates that afforded by popular predictive variables, achieving an out-of-sample R2 of 12.6% at the annual horizon.