Reconciling Value Estimates from the Discounted Cash Flow Value Model and the Residual Income Model

Author(s):  
Russell J. Lundholm ◽  
Terry O'Keefe
2015 ◽  
Vol 5 (2) ◽  
pp. 170-183 ◽  
Author(s):  
Ranjit Tiwari ◽  
Harish Kumar Singla

Purpose – 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. Design/methodology/approach – 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. Findings – 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. Research limitations/implications – 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. Originality/value – 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.


2012 ◽  
Vol 12 (1) ◽  
pp. 87
Author(s):  
Kim Hong ◽  
Fakhruddin Nasution

<span>The purpose of multi finance companies’ stock price valuation is to know their intrinsic <span>values by performing fundamental analysis using dividend discount model, free cash flow to the firm model, free cash flow to equity model, and residual income model. Research data uses secondary data in the period of 2006-2010 which consists of Indonesian Stock Price Composite Index (IHSG), and multi finance companies’ stock prices taken from Yahoo Finance; multi finance companies’ financial statements taken from Indonesian Stock Exchange (BEI) reports; multi finance industry data taken from Bapepam-LK. As a result of research, stock of ADMF is fair valued by using the analysis of dividend<br />discount model; undervalued by using the analysis of free cash flow to the firm and free cash flow to equity models; overvalued by using the analysis of residual income model. Stock of BFIN is undervalued by using the analysis of dividend discount, free cash flow to the firm, and free cash flow to equity models; overvalued by using the analysis of residual income model. Stock of MFIN is overvalued by using the analysis of dividend discount<br />and residual income models; undervalued by using the analysis of free cash flow to the firm and free cash flow to equity models. Statistic t-test shows that there are no significant differences to value stock prices using dividend discount, free cash flow to the firm, free cash flow to equity, and residual income models, therefore investment analyst or investor may use one of the chosen stock price valuation model.<br />Keywords: Multi finance companies, Fundamental analysis, Stock price valuation model, Intrinsic value, Required return, Investment risk<br /></span></span>


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