Implementing Residual Income Valuation With Linear Information Dynamics

1999 ◽  
Vol 74 (1) ◽  
pp. 1-28 ◽  
Author(s):  
James N. Myers
Keyword(s):  
Time Series ◽  
Firm Value ◽  
Residual Income ◽  
Accounting System ◽  
Information Dynamics ◽  
No Arbitrage ◽  
Book Value ◽  
Residual Income Valuation ◽  
Accounting Numbers ◽  
Linear Information

Residual income (RI) valuation is a method of estimating firm value based on expected future accounting numbers. This study documents the necessity of using linear information models (LIMs) of the time series of accounting numbers in valuation. I find that recent studies that make ad hoc modifications to the LIMs contain internal inconsistencies and violate the no arbitrage assumption. I outline a method for modifying the LIMs while preserving internal consistency. I also find that when estimated as a time series, the LIMs of Ohlson (1995), and Feltham and Ohlson (1995) provide value estimates no better than book value alone. By comparing the implied price coefficients to coefficients from a price level regression, I find that the models imply inefficient weightings on the accounting numbers. Furthermore, the median conservatism parameter of Feltham and Ohlson (1995) is significantly negative, contrary to the model's prediction, for even the most conservative firms. To explain these failures, I estimate a LIM from a more carefully modeled accounting system that provides two parameters of conservatism (the income parameter and the book value parameter). However, this model also fails to capture the true stochastic relationship among accounting variables. More complex models tend to provide noisier estimates of firm value than more parsimonious models.

Accounting Conservatism and the Valuation of Accounting Numbers: Evidence on the Feltham-Ohlson (1996) Model

2000 ◽  
Vol 15 (3) ◽  
pp. 271-292 ◽  
Author(s):  
Anwer S. Ahmed ◽  
Richard M. Morton ◽  
Thomas F. Schaefer
Keyword(s):  
Explanatory Power ◽  
Accounting Conservatism ◽  
Information Dynamics ◽  
Lower Growth ◽  
Book Value ◽  
Earnings Dynamics ◽  
Valuation Model ◽  
Accounting Numbers ◽  
Linear Information ◽  
Stock Market Valuation

We empirically investigate the effects of accounting conservatism on (1) the stock market valuation of operating assets in the context of the Feltham-Ohlson (1996) model and (2) the weight on operating assets in the Feltham-Ohlson abnormal operating earnings dynamics (hereafter referred to as the LIM conservatism parameter). Consistent with the Feltham-Ohlson (1996) model, we find that accounting-based conservatism proxies are positively related to the valuation weight on operating assets. Furthermore, the accounting-based conservatism proxies have incremental explanatory power even after controlling for (1) size, (2) book value (or sales) growth, and (3) leverage. These results are robust with respect to alternative empirical specifications of the valuation model and the choice of proxies for accounting conservatism. We also find, consistent with prior research but not with the Feltham-Ohlson model, that the sign of the LIM conservatism parameter is on-average negative. We provide evidence on the types of firms for which the linear information dynamics appears to hold better or worse. More specifically, the firms with negative values of the parameter are significantly smaller, less profitable and experiencing lower growth rates than firms with positive values of the parameter. Moreover, the relation between accounting-based conservatism proxies and the LIM conservatism parameter is fairly strong for the subsample of firms with high levels of profitability.

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

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 513
Author(s):  
Olga Fullana ◽  
Mariano González ◽  
David Toscano
Keyword(s):  
Time Series ◽  
Model Performance ◽  
Listed Firms ◽  
Valuation Model ◽  
Residual Income Valuation ◽  
Equity Value ◽  
Short Run ◽  
Time Series Approach ◽  
Linear Information

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.

scholarly journals Valuation properties of accounting numbers in Brazil

2004 ◽  
Vol 1 (3) ◽  
pp. 31-36
Author(s):  
Alexsandro Broedel Lopes
Keyword(s):  
Stock Exchange ◽  
Residual Income ◽  
Net Income ◽  
Book Value ◽  
Residual Income Model ◽  
Significant Difference ◽  
Accounting Numbers ◽  
Dividend Distribution ◽  
Comparable Performance ◽  
Income Model

This work investigates the valuation properties of accounting numbers in Brazil under three traditional frameworks: earnings capitalization, book value of equity and residual income. The sample was selected from companies traded at the São Paulo Stock Exchange (BOVESPA) from 1995 to 1999, dividing the sample in two groups: companies with preferred and with common shares. My results show that the earnings capitalization model did not perform well for common shares and have a better performance for preferred shares because of the mandatory dividend distribution as a percentage of net income in Brazil and because earnings have no use as information asymmetry reducers in Brazil. The book value model performed better for common shares while residual income had a comparable performance and seems to be the dominant accounting-based valuation model for common shares. For preferred shares the residual income model performs better. The residual income term alone presents no significant difference for the two sets of companies. For both set of companies accounting income did not incorporated economic income.

A Comparative Analysis of Accounting-Based Valuation Models

2016 ◽  
Vol 32 (4) ◽  
pp. 561-575 ◽  
Author(s):  
Kung-Cheng Ho ◽  
Shih-Cheng Lee ◽  
Chien-Ting Lin ◽  
Min-Teh Yu
Keyword(s):  
Stock Prices ◽  
The Other ◽  
Residual Income ◽  
Switching Regression ◽  
Book Value ◽  
Earnings Growth ◽  
Valuation Model ◽  
Pricing Errors ◽  
Residual Income Valuation ◽  
Average Probability

We empirically compare the reliability of the dividend (DIV) model, the residual income valuation (CT, GLS) model, and the abnormal earnings growth (OJ) model. We find that valuation estimates from the OJ model are generally more reliable than those from the other three models, because the residual income valuation model anchored by book value gets off to a poor start when compared with the OJ model led by capitalized next-year earnings. We adopt a 34-year sample covering from 1985 to 2013 to compare the reliability of valuation estimates via their means of absolute pricing errors ( MAPE) and corresponding t statistics. We further use the switching regression of Barrios and Blanco to show that the average probability of OJ valuation estimates is greater in explaining stock prices than the DIV, CT, and GLS models. In addition, our finding that the OJ model yields more reliable estimates is robust to analysts-based and model-based earnings measures.

scholarly journals A Comparison of Equity Valuation Models: Empirical Evidence from a Sample of UK Companies

2019 ◽  
Vol 4 (2) ◽  
pp. 105
Author(s):  
Ja Ryong Kim
Keyword(s):  
Time Series ◽  
Stock Price ◽  
Residual Income ◽  
Main Question ◽  
Book Value ◽  
Pricing Errors ◽  
The Future ◽  
The Uk ◽  
Errors Analysis ◽  
Practical Implications

This paper aims to answer one main question: can the superior models in accounting field be superior in finance field? That is, can models that generate a better approximation to stock price also generate higher returns in the future? To answer this question, I conduct pricing errors analysis and time-series returns analysis. The most important finding is models that approximate stock price better tend to produce higher returns in the future; implying findings in accounting literature have practical implications to analysts and investors. The consistent rankings of models are observed throughout the research: forward earnings multiples perform the best, followed by fundamental valuation models and historical earnings multiples, and book value and sales multiples worst. However, multiples are ranked rather as a group in the UK. Interestingly, residual income models produce similar returns to forward earnings multiples, but the accuracy of their estimates varies depending on their terminal value assumptions.

scholarly journals Cluster analysis of share price: How firm characteristics relate to accounting metrics

2021 ◽  
Vol 11 (4) ◽  
pp. 8-25
Author(s):  
Mfon Akpan ◽  
Guneet Dhillon ◽  
Kim Trottier
Keyword(s):  
Cluster Analysis ◽  
Firm Value ◽  
Share Price ◽  
High Tech ◽  
Firm Characteristics ◽  
Book Value ◽  
Accounting Numbers ◽  
Net Assets ◽  
Retained Earnings ◽  
The Relationship

The purpose of this paper is to improve our understanding of the relationship between share price and accounting information. Much of the literature utilizes the earnings number to reflect firm value. However, the revenue number seems more relevant for high tech firms (Xu, Cai, & Leung, 2007), and cash flow figures are more informative for internet companies (Romanova, Helms, & Takeda, 2012). We build on this notion that share price may map out to different accounting numbers for different firms. We collect 629 accounting metrics for 3,365 firms in the U.S. and estimate their correlation with the firms’ share price. We analyze these correlations and find that many firms exhibit a low correlation between share price and earnings. Other accounting numbers are important for these firms, including book value of net assets, retained earnings, stock options, gain or loss items, special or non recurring items, and dividend rates. We are curious to learn what causes firms to anchor onto different metrics, therefore perform a cluster analysis to group similar firms together along three key accounting metrics. We examine the composition of each cluster and find that capital structure, dividend patterns, the persistence of operations, age, and industry can influence which accounting number is correlated with firm value. We encourage other researchers to continue this exploration as there are many interesting questions to answer.

The Ohlson Model: Contribution to Valuation Theory, Limitations, and Empirical Applications

2000 ◽  
Vol 15 (3) ◽  
pp. 337-367 ◽  
Author(s):  
Kin Lo ◽  
Thomas Lys
Keyword(s):  
Empirical Studies ◽  
Residual Income ◽  
Valuation Theory ◽  
Limited Evidence ◽  
Information Dynamics ◽  
Profound Impact ◽  
Empirical Validity ◽  
Valuation Model ◽  
Residual Income Valuation ◽  
Key Features

The work of Ohlson (1995) and Feltham and Ohlson (1995) had a profound impact on accounting research in the 1990s. In this paper, we first discuss this valuation framework, identify its key features, and put it in the context of prior valuation models. We then review the numerous empirical studies that are based on these models. We find that most of these studies apply a residual income valuation model without the information dynamics that are the key feature of the Feltham and Ohlson framework. We find that few studies have adequately evaluated the empirical validity of this framework. Moreover, the limited evidence on the validity of this valuation approach is mixed. We conclude that there are many opportunities to refine the theoretical framework and to test its empirical validity. Consequently, the praise many empiricists have given the models is premature.

Residual Income Compensation Plans and Deferred Taxes

2010 ◽  
Vol 22 (1) ◽  
pp. 103-114 ◽  
Author(s):  
Nicole Bastian Johnson
Keyword(s):  
Investment Model ◽  
Financial Accounting ◽  
Residual Income ◽  
Investment Incentives ◽  
Deferred Taxes ◽  
Incentive Alignment ◽  
Compensation Plans ◽  
Book Value ◽  
Performance Metric ◽  
Accounting Numbers

ABSTRACT: Residual income is a popular performance metric that is often calculated from financial accounting numbers. Practitioners argue that financial accounting earnings and book value suffer from various biases and should be adjusted prior to the residual income calculation so that the resulting residual income metric will have better incentive properties, but they often disagree about what the adjustments should be. Using the criterion that a residual income performance metric should align owner and managerial investment incentives, I develop a simple investment model to show how financial accounting choices and adjustments must be chosen jointly to achieve incentive alignment. In particular, I examine conflicting recommendations from the practitioner literature about the proper adjustment for deferred taxes and show that more than one adjustment method can achieve incentive alignment if paired with the correct depreciation schedule. Further, I show that relationships among accounting variables introduce constraints that make some policies or adjustments more difficult to work with. The paper concludes with a brief discussion about how the use of sub-optimal adjustments can negatively influence the manager’s investment incentives.

Stationarity and Cointegration Tests of the Ohlson Model

2000 ◽  
Vol 15 (2) ◽  
pp. 141-160 ◽  
Author(s):  
Daqing D. Qi ◽  
Y. Woody Wu ◽  
Bing Xiang
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Empirical Studies ◽  
Market Value ◽  
Residual Income ◽  
Series Data ◽  
Book Value ◽  
Cointegration Tests ◽  
Significant Difference ◽  
Out Of Sample

This paper investigates the time-series properties of the Ohlson (1995) model and examines their implications for empirical studies that use time-series data but do not explicitly account for such properties. Based on a sample of 95 firms with complete data from 1958 to 1994, we show that the null hypothesis that market value and book value are nonstationary cannot be rejected for most of the sample firms. More importantly, book value and residual income do not cointegrate with market value for 80 percent of the sample firms. We demonstrate the importance and relevance of the time-series properties of the model to OLS regressions by showing that the OLS out-of-sample forecasts of market value are significantly more accurate and less biased for the cointegrated firms than for the non-cointegrated firms. We also explore methods to improve the specification of OLS regressions based on the Ohlson (1995) model and suggest that scaling the variables with lagged market value can significantly alleviate the problem with nonstationarity of the unsealed time-series data. While the generality of our results is limited by the survivorship bias of our sample, we believe that our paper has some important implications for studies motivated by the Ohlson (1995) model. First, because market value and book value are nonstationary and book value and residual income do not cointegrate with market value for most firms, the other information variable has to be nonstationary so that a linear combination of the independent variables can cointegrate with market value. Second, direct tests of the Ohlson (1995) model through OLS regressions using time-series data are questionable because they are likely to be misspecified. This may partially explain the underestimation of market value widely documented by previous studies and the significant difference between parameters predicted by the Ohlson (1995) model and estimated from OLS regressions. Third, our results also suggest that scaling the data with lagged market value can mitigate the problems with nonstationarity. For studies using unsealed time-series data, a cointegration test should be conducted first and a sensitivity analysis based on the cointegrated sub-sample should be performed to examine whether the results based on the full sample are robust.

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