An Equivalent Form of the Residual Income Valuation Model

2004 ◽  
Author(s):  
Richard P. Brief
Keyword(s):  
Equivalent Form ◽  
Residual Income ◽  
Valuation Model ◽  
Residual Income Valuation

Unrecorded Intangible Assets: Abnormal Earnings and Valuation

2007 ◽  
Vol 21 (1) ◽  
pp. 23-41 ◽  
Author(s):  
Mark Kohlbeck ◽  
Terry D. Warfield
Keyword(s):  
Banking Industry ◽  
Intangible Assets ◽  
Residual Income ◽  
Equity Valuation ◽  
Analysis Framework ◽  
Valuation Model ◽  
Residual Income Valuation ◽  
The Impact

We use the unique banking industry setting to demonstrate the impact of unrecorded intangible assets on abnormal earnings and equity valuation in the context of the residual income valuation model. We show that the persistence of bank abnormal earnings and, consequently, the pricing multiples on bank abnormal earnings, vary with the level of unrecorded intangible assets. Our evidence suggests that unrecorded intangible assets are important in understanding the persistence and valuation of abnormal earnings in the banking industry. The analysis framework introduced in this paper could also be used to examine the valuation impacts of intangible assets in other industries.

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.

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.

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