A Review and Synthesis of Research on Analysts' Valuation ...

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A Review and Synthesis of Research

on Analysts’ Valuation Process

Beyond Approaches and Models

Maria Dimitriou*

University of Macedonia, Greece

ABSTRACT

During the past few decades, accounting and finance researchers, both academic and investment

industry researchers have been interested in analysts’ valuation approaches and models

determining the intrinsic value of an ownership stake, analysts’ target price, earnings forecasts,

valuation errors and stock recommendation. This survey examines publicly available articles

based on accepted valuation theory, that explore this issue to determine researchers’ methods of

studying this process. This survey has found that few researchers study analysts’ valuation

processes from the sell-side analyst approach. Instead, many use the approach of empirical

studies (based on elements of analyst reports and interviews). This research suggests the need to

approach the valuation process from the sell-side analyst approach, for example, by investment

research report as it shares lots of information that better serves society and economies to grow.

Keywords: Security Analysis, Financial Analyst, Sell-side Equity Analyst, Equity Valuation,

Valuation Errors, Information Uncertainty, Stock Recommendations, Valuation Approaches,

Valuation Model.

————————————————

* Ph.D. Candidate in Field of Research: Financial Accounting with Information Systems, Department of Applied Informatics, School of Information Sciences, University of Macedonia, N. Egnatia Str. 156, 54006, Thessaloniki, Greece

E-mail: [email protected], [email protected], [email protected]

Website: https://www.linkedin.com/in/maria-dimitriou-1b238b63/, https://www.researchgate.net/profile/Maria_Dimitriou3

Identifiers: Web of Science Researcher ID Y-7232-2019, ORCID 0000-0002-6153-7122 https://publons.com/researcher/3121758/maria-dimitriou/, https://orcid.org/0000-0002-6153-7122/print

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Ανασκόπηση και Σύνθεση της

Έρευνας σχετικά με τη Διαδικασία

Αποτίμησης των Αναλυτών πέρα

από Προσεγγίσεις και Μοντέλα

Μαρία Δημητρίου *

Πανεπιστήμιο Μακεδονίας, Ελλάδα

ΠΕΡΙΛΗΨΗ

Τις τελευταίες δεκαετίες, οι ερευνητές στον τομέα της λογιστικής και της χρηματοοικονομικής, τόσο

οι ακαδημαϊκοί όσο και οι ερευνητές της βιομηχανίας επενδύσεων ενδιαφέρονται για τις

προσεγγίσεις και τα μοντέλα αποτίμησης των αναλυτών που καθορίζουν την εσωτερική αξία της

μετοχής μιας εταιρείας, την ενδεικτική τιμή-στόχο των αναλυτών, τις προβλέψεις κερδών, τα

σφάλματα αποτίμησης και τις συστάσεις μετοχών. Αυτή η έρευνα εξετάζει διαθέσιμα στο κοινό

άρθρα που βασίζονται σε αποδεκτή θεωρία αποτίμησης, τα οποία διερευνούν αυτό το ζήτημα για

τον προσδιορισμό των μεθόδων που χρησιμοποιούνται από τους ερευνητές για τη μελέτη αυτής της

διαδικασίας αποτίμησης των αναλυτών. Αυτή η έρευνα διαπίστωσε ότι λίγοι ερευνητές μελετούν τη

διαδικασία αποτίμησης των αναλυτών από την προσέγγιση του αναλυτή. Αντ 'αυτού, πολλοί

χρησιμοποιούν την προσέγγιση των εμπειρικών μελετών (βάσει στοιχείων των εκθέσεων των

αναλυτών και συνεντεύξεων). Η έρευνα αυτή υποδηλώνει την ανάγκη προσέγγισης της διαδικασίας

αποτίμησης από την προσέγγιση του αναλυτή, για παράδειγμα, από την ερευνητική έκθεση

επενδύσεων, καθώς μοιράζεται πολλές πληροφορίες που εξυπηρετούν καλύτερα την κοινωνία και

τις οικονομίες να αναπτυχθούν.

Λέξεις - Κλειδιά: Ανάλυση Μετοχής, Οικονομικός Αναλυτής, Χρηματοοικονομικός Αναλυτής,

Αποτίμηση Μετοχών, Σφάλματα Αποτίμησης, Πληροφορίες, Αβεβαιότητα, Συστάσεις/

Επενδυτικές Αποφάσεις, Προσεγγίσεις/ Μοντέλα Αποτίμησης.

———————————————— * Υπ. Διδ. στο Πεδίο Έρευνας: Χρηματοοικονομική Λογιστική με Πληροφοριακά Συστήματα, Τμήμα Εφαρμοσμένης Πληροφορικής, Σχολή Επιστημών Πληροφορίας, Πανεπιστήμιο Μακεδονίας, Εγνατία 156, 546 36, Θεσσαλονίκη, Ελλάδα

E-mail: [email protected], [email protected], [email protected]

Website: https://www.linkedin.com/in/maria-dimitriou-1b238b63/, https://www.researchgate.net/profile/Maria_Dimitriou3

Identifiers: Web of Science Researcher ID Y-7232-2019, ORCID 0000-0002-6153-7122 https://publons.com/researcher/3121758/maria-dimitriou/, https://orcid.org/0000-0002-6153-7122/print

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INTRODUCTION

In the past few decades, accounting and finance researchers, both academic and investment

industry researchers, have been interested in analysts’ valuations. Valuation is the estimation of

an asset’s value based either on variables perceived to be related to future investment returns or

on comparisons with similar assets. Valuation, including equity valuation, is most closely

associated with the valuation process. For one group of participants in the investment profession

-equity analysts - the valuation is particularly critical, for determining the value of an ownership

stake is at the heart of their professional activities and decisions (Jerald et al., 2007). Benjamin

Graham and David L. Dodd’s Security Analysis (1934) represented the first significant attempt to

organize knowledge in this area for the investment profession. Benjamin Graham is the father of

security analysis and future mentor to a well-known modern investor, Warren Buffett.

According to the book entitled “Equity Asset Valuation” (Jerald et.al., 2007), CFA Institute

Investment Series as well as book in a course in my master syllabus (M.Sc. Degree in Strategic

Managerial Accounting and Financial Management: Finance, for Business Executives,

Department of Accounting and Finance, University of Macedonia), analysts’ valuations based on

sound analysis and helps their clients achieve their investment objectives by enabling those

clients to make better buy and sell decisions; contribute to the efficient functioning of capital

markets (in providing analysis that leads to informed buy and sell decisions, analysts help make

asset prices better reflections of underlying values; when asset prices accurately reflect

underlying values, capital flows more quickly to its highest-value uses); and benefit the suppliers

of capital, including shareholders, by monitoring management’s performance. Additionally, it

provides valuation information and opinions, valuation judgments to a portfolio manager, or an

investment committee (Jerald et al., 2007). However, this study is not aimed to provide a

comprehensive view of every perspective of analysts’ valuations.

PURPOSE - CONTRIBUTION

The purpose of this study is to survey literature and provide a summary of research into analysts’

valuation process. In particular, two different approaches are used to examine analysts’ valuation

process and discuss the advantages and limitations of both approaches. We will pay special

attention to the most commonly used forms of equity valuation beyond approaches and models -

dividend discount, free cash flow, price/earnings models, and residual income models (often

known by trade names), and to the overlooked and unaddressed questions regarding analysts’

valuation process. Besides, as a result of this study, direction for future studies on analysts’

valuation process will be provided.

RESEARCH QUESTION/S

The specific research questions addressing the valuation process are:

• What kind of valuation process do analysts communicate?

• How can a valuation process be described?

• How are approaches, models, and other related valuation aspects treated/ communicated

by analysts?

The specific research questions, addressing the researches on analysts ‘valuation process, are:

• Are the academic and investment industry researchers implementing analysts’ valuation

process analysis or making an investment decision?

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• Are the academic and investment industry researchers communicating other issues on

analysts’ valuation process (financial accounting and other market-related information,

elements of analyst reports, interviews)?

• How does the valuation process by analysts influence the stock recommendation/decision

making?

DESIGN/METHODOLOGY/APPROACH

This project contains three sections. The first section provides descriptive information on the role

of analysts in capital markets and their valuation process through a format for a research report.

In the second and third sections, how researchers have examined analysts’ valuation process

beyond approaches and models is analyzed, and what we need to do, generally and specifically.

ANALYSTS’ ROLE AND VALUATION PROCESS

Analysts play an essential role in the capital market. Investment analysts work in a wide variety

of organizations and positions applying the tools of equity valuation to address a range of

practical problems. They play a critical role in collecting, organizing, analyzing, and

communicating corporate information, as well as in recommending appropriate investment

actions based on their analysis. In fulfilling this role, they help clients, investors, and company

management achieve their investment objectives and contribute to the efficient functioning of

capital markets. Analysts can contribute to the welfare of shareholders through monitoring the

actions of management. So, analysts must provide substantive and meaningful content. CFA

Institute members have an additional overriding responsibility to adhere to the CFA Institute

Code of Ethics and relevant specific Standards of Professional Conduct guiding the analyst to

independent, well-researched, and well-documented analysis (It is discussed more in Pinto, J. E.,

Henry, E., Robinson, T. R., Stowe, J. D., Cohen, A., 2007).

Finance theory and professional practice propose alternative approaches to the evaluation of a

company. In theory, valuation is a relatively simple process of discounting a firm’s expected cash

flows by investors required rates of return. In practice, valuation is highly complex because there

are numerous valuation models and techniques (Rawley and Benton, 2009). The traditional

distinction is between valuation based on the fundamentals of the company (future cash flows,

earnings and so on) and the market ratios approach, which is based on the market multiples of a

company. Penman (2001) gives a definition of the fundamental analysis as a five-step process

consisting of: 1) knowing the business through the strategic analysis; 2) analysing the accounting

and non-accounting information; 3) specifying, measuring and forecasting the value relevant

payoffs; 4) converting the forecast to a valuation; and 5) trading on the valuation.

While the valuation is the estimation of an asset’s value based either on variables perceived to be

related to future investment returns or on comparisons with similar assets, valuation - including

equity valuation - is most closely associated with valuation process (Pinto, J. E., Henry, E.,

Robinson, T. R., Stowe, J. D., Cohen, A., 2007). The valuation process is at the heart of equity

analysts’ professional activities and decisions. Each valuation that an analyst undertakes can be

viewed as a complex and, therefore, diverse process with the following five steps. Analysts’

valuations process includes:

Step 1: Understanding the business to be valued

Step 2: Forecasting company performance

Step 3: Selecting the appropriate valuation model for the valuation task

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Step 4: Converting forecasts to the valuation

Step 5: Making the investment decision (recommendation)

The goal of this process is to provide stock recommendations to their clients. These

recommendations include which stocks to buy, which stocks to sell, and which stocks to hold.

Therefore, writing an investment research report is an integral part of an analyst’s job.

Research reports share several common elements, whether a research report is for review by an

investment committee or a portfolio manager in an investment management firm, or distribution

to the retail or institutional clients of a brokerage firm. Most research reports cover the following

three broad areas: description (presentation of facts; this brings the reader up to date on the

company’s sales, earnings, new products, and the macroeconomic and industry contexts in which

the company operates); analysis and forecasts for the industry and company; and valuation and

recommendation (Pinto, J. E., Henry, E., Robinson, T. R., Stowe, J. D., Cohen, A., 2007). Table

1 provides us with a brief view of a format for analysts’ research reports.

Table 1. A Format for Research Reports. Source: Book entitled “Equity Asset Valuation”, pp.28 Section Purpose Content Comments

Table of

Contents

•Shows report’s organization

•Consistent with narrative in

sequence and language

This section is

typically used in very

long research reports

only.

Summary

and

Investment

Conclusion

•Communicate the large picture

•Communicate major-specific

conclusions of the analysis

•Recommend an investment course

of action

•A capsule description of the

company

•Major recent developments

•Earnings projections

•Other major conclusions

•Valuation summary

•Investment action

This section is an

executive summary; it

may be called

‘‘Summary.’’

Business

Summary

•Present the company in more

detail

•Communicate a detailed

understanding of the company’s

economics and current situation

•Provide and explain specific

forecasts

•Company description to the

divisional level

•Industry analysis

•Competitive analysis

•Historical performance

•Financial forecasts

This summary reflects

the first and second

steps of the valuation

process. Financial

forecasts should be

explained adequately

and reflect the quality

of earnings analysis.

Risks •Alert readers to the risk factors in

investing in the security

•Possible negative industry

developments

•Possible adverse regulatory and

legal developments

•Possible negative company

developments

•Risks in the forecasts

•Other risks

Readers should have

enough information to

determine how the

analyst is defining and

assessing the risks

specific to investing in

security.

Valuation •Communicate a precise and

careful valuation

•Description of the model(s)

used

•Recapitulation of inputs

•Statement of conclusions

Readers should have

enough information to

critique the analysis.

Historical

and

Pro Forma

Tables

•Organize and present data to

support the analysis in the Business

Summary

This section is

generally a separate

section in more

extended research

reports only.

Many reports fold all

or some of this

information into the

Business Summary

section

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A key element of research reports supporting a recommendation is the valuation of the security.

In this process, equity valuation models help to specify what is to be forecasted, directs to the

information needed to make the forecast, and shows how to relate the forecasted data into an

intrinsic value estimate (Pinto, J. E., Henry, E., Robinson, T. R., Stowe, J. D., Cohen, A., 2007).

A valuation model is a mechanism that converts a set of forecasts of (or observations on) a series

of company and economic variables into a forecast of market value for the company’s stock.

Structures of valuation models often include many assumptions and parameters. Each valuation

model and technique have its strengths and weaknesses.

The valuation model can be considered a formalization of the relationship that is expected to

exist between a set of corporate and economic factors and the market’s valuation of these factors

(Elton, Gruber, Brown, & Goetzmann 2011). Barker, R (2001) argues that a good understanding

of valuation methods requires two main things: the first is an analytical review of the models, and

the second is an evaluation of the data that are available for the use of these models. It is because

of this; there is a significant relationship between the choice of valuation models and the

available data. Valuation, however, is relevant and critical to active investment strategies, risk

factors that objectively address the uncertainty associated with investing in the security (Pinto, J.

E., Henry, E., Robinson, T. R., Stowe, J. D., Cohen, A., 2007).

Literature suggests three major valuation model categories: 1. Asset-based Valuation, 2. Absolute

Valuation or Discounted Cash Flow models and 3. Relative Valuation or Price Multiple models.

Other methods, such as the yield-based valuation method, which focuses on dividend yield when

the investment priority is income, or option valuation models that explicitly consider

management flexibility in the value creation process, are not the subject of this paper. The broad

criteria for model selection are that the valuation model is consistent with the characteristics of

the company we value; appropriate given the availability and quality of data; and consistent with

the purpose of valuation, including the analyst’s ownership perspective (Pinto, J. E., Henry, E.,

Robinson, T. R., Stowe, J. D., Cohen, A., 2007). According to Bertinetti, G., Caveazzali E., &

Rigoni U. (2006), there are five valuation method classes including techniques.

Table 2. Valuation method classes including techniques. Source: Bertinetti, G., Caveazzali E., &

Rigoni U. (2006)

Analysts depend on accurate forecasts combined with an appropriate valuation model to construct

their valuations, obtaining a useful estimate of intrinsic value. The more information that is

known about the company, the industry, and the company’s position within the industry, the

more realistic and supportable the assumptions made in the projections will be. The analyst

integrates the analysis of industry prospects and competitive and corporate strategy with financial

statement analysis to formulate specific numerical forecasts of such items as sales and earnings.

Analysts may consider qualitative as well as quantitative factors in financial forecasting and

valuation. Qualitative factors and other considerations may affect a recommendation and merit

discussion. The quality of the analyst’s forecasts, the expectational inputs used in valuation

models, is a crucial element in determining investment success (Pinto, J. E., Henry, E., Robinson,

T. R., Stowe, J. D., Cohen, A., 2007).

Analysts may consider qualitative as well as quantitative factors in financial forecasting and

valuation. Qualitative factors and other considerations may affect a recommendation and merit

Method Class Method Technique

Net Assets based Methods (NAV) Embedded Value (EV) and Appraisal Value (AV)

Earnings-based Mehods Discounted Shareholder Profit (DSP), Discounted

Earnings (DE), Heuristic methods (WEV, RR)

Cash flows-based Methods

Dividend Discounted Model (DDM), Discounted

Cash Flows (DCF), Gordon Growth Model (GGM),

Adjusted Present Value (APV), HOLT-CFROI

“Hybrid” Methods Economic Value Added (EVA), Regulatory Asset

Based methods (RAB)

Market ratios Methods Comparable companies and comparable trades

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discussion. The quality of the analyst’s forecasts, the expectational inputs used in valuation

models, is a critical element in determining investment success (Jerald et al., 2007).

Schipper (1991) indicates that knowing how analysts use financial accounting information should

make accounting and finance academics more knowledgeable professors and thus more able to

teach future students.

THE APPROACH OF EMPIRICAL STUDIES

The approach of empirical studies (based on elements of analyst reports and interviews). Given

the valuation models used on sell‐side analysts' reports, accounting and finance researchers, both

academic and investment industry researchers, have a consistent methodology to measure their

accuracy, effectiveness, and predictive capability.

Bradshaw, M. T. (2001) investigate whether the degree of assessed overpricing or underpricing

implied by target prices is related to the favorableness of stock recommendations. His study

examines a sample of 103 sell‐side analysts' reports to document the frequency with which

analysts disclose target prices as justifications for their stock recommendations. He finds that

analysts use target price justifications in over two‐thirds of the sample reports, and higher target

prices are associated with more favorable stock recommendations. The most favorable

recommendations (and target prices) are more likely to be justified by price‐earnings ratios and

expected growth, while the least favorable recommendations are more likely to be justified with

other qualitative statements. Further evidence suggests that analysts compute target prices using

price‐multiple heuristics such as “Price/Earnings to Growth.” However, in reports that do not

disclose target prices, estimates of target prices based on these heuristics are unable to justify the

stock recommendations. Several explanations are proposed, including self‐selection biases

implying analysts do not disclose target prices when the disclosure would not support the

recommendation or when analysts are less sure about underlying earnings forecasts.

Demirakos, E., Strong, N., & Walker, M. (2010) investigate whether the choice of valuation

model affects the forecast accuracy of the target prices that investment analysts’ issue in their

equity research reports, controlling for factors that influence this choice. They examine 490

equity research reports from international investment houses for 94 UK-listed firms published

over the period July 2002–June 2004. They use four measures of accuracy. Based on during the

12-month forecast horizon and absolute forecast error, price-to-earnings outperform discounted

cash flow models, while based on met on the last day of the 12-month forecast horizon and the

forecast error of target prices that are not met at the end of the 12-month forecast horizon, the

difference in valuation model performance is insignificant. However, after controlling for

variables that capture the difficulty of the valuation task, the performance of DCF models

improves in all specifications, and, based on the forecast error of target prices that are not met at

the end of the 12-month forecast horizon, they outperform price-to-earnings models. These

findings are robust to standard controls for selection bias.

Imam, Shahed, Barker, Richard, and Clubb, Colin (2008) examine the use of valuation models by

UK investment analysts. The study is based on, first, semi-structured interviews with 35 sell-side

analysts from 10 leading investment banks and with seven buy-side analysts from 3 asset

management firms and, second, content analysis based on 98 equity research reports for

FTSE-100 companies covered by the sell-side interviewees. They observe that analysts perceive

the discounted cash flow (and to some extent ‘sophisticated’ models in general) to have become

significantly more critical than prior survey evidence suggests, although they also find the

(somewhat paradoxical) continued importance of ‘unsophisticated’ valuation multiples, notably

the price/earnings ratio.

Imam, S., Barker., R., & Clubb, C. (2008) examine the use of valuation models by UK

investment analysts. The study is based on, first, semi-structured interviews with 35 sell-side

analysts from 10 leading investment banks and with seven buy-side analysts from 3 asset

management firms and, second, content analysis based on 98 equity research reports for

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FTSE-100 companies covered by the sell-side interviewees. They observe that analysts perceive

the discounted cash flow (and to some extent ‘sophisticated’ models in general) to have become

significantly more critical than prior survey evidence suggests, although they also find the

(somewhat paradoxical) continued importance of ‘unsophisticated’ valuation multiples, notably

the price/earnings ratio.

Imam, S., Barker, R., & Clubb, C. (2008) find perceived limitations in the technical applicability

of the discounted cash flow model, which causes analysts to rely on practice upon valuation

multiples and subjective judgment of whether the market price ‘feels right.’ They also find that

contextual factors, notably the analysts' need for their research to be credible to buy-side clients,

cause the use of subjective, unsophisticated methods of valuation to be played down. Given the

inherent flexibility of the discounted cash flow model, coupled with its ostensible credibility, it

becomes the natural vehicle for conveying the analyst's research, even though it is very rarely

relied upon to determine target prices and investment recommendations. They conclude that,

while the literature has focused on the technical merits of alternative valuation models, analysts'

actual usage of valuation models also requires an understanding of social and economic context

and motivations.

Price to earnings and discounted cash flow are two popular valuation methodologies used by

equity research analysts to derive target price forecasts. Recent studies in developed markets

show that analysts using a sophisticated model like discounted cash flow model produce more

accurate target price forecasts as compared to heuristics driven models like price-to-earnings.

Samie, A., S. (2016) investigate if analysts using a discounted cash flow model outperform

analysts using price-to-earnings in an emerging market institutional set up by an in-depth analysis

of 392 equity research reports is conducted to understand the dominant valuation model used by

analysts to derive target price forecasts. Research reports with explicit mention of valuation

methodology (price-to-earnings or discounted cash flow) to derive target price forecasts are used.

Multivariate ordinary least squares and logit regression analysis has been conducted to

investigate if analysts using discounted cash flow methodology outperform analysts using

price-to-earnings to derive target price forecasts. They find that analysts using price-to-earnings

produce significantly better short-term results than analysts using discounted cash flow, i.e.,

when target price accuracy is measured anytime during the forecast horizon of 12 months.

However, they claim that there is no significant difference in target price performance or target

price forecast error of price-to-earnings and discounted cash flow when analyst performance is

measured at the end of the forecast horizon. In contrast to results from developed markets, their

study does not find evidence of superior target price performance of discounted cash flow. On the

contrary, their results suggest that price-to-earnings outperforms discounted cash flow on the

short-term measure of target price accuracy. Their study shows that the price-to-earnings model,

which captures market moods and sentiments effectively, is more suitable in dynamic, emerging

markets like India.

Glaum, M., & Friedrich, N. (2006) present the results of a series of interviews given by financial

analysts specializing in the European telecommunications industry. Their objective is to gain an

insight into their approaches to analysis and valuation (information sources, valuation methods,

determinants of recommendations). They also consider whether analysts' approaches have

changed since the high-tech bubble. They find that today, they rely much more on the discounted

cash flow analysis method than at the end of the 1990s when the valuation was based mainly on

multiples. In line with this, analysts have changed their focus from revenue-oriented measures

towards an assessment of profitability and cash flow generation. Further, analysts claim to have

become more diligent and more critical in their analysis.

Fernandez, P. (2002) describes the four main groups comprising the most widely used company

valuation methods: balance sheet-based methods, income statement-based methods, mixed

methods, and cash flow discounting based methods. The methods that are conceptually “correct”

are those based on cash flow discounting. He will briefly comment on other methods since -even

though they are conceptually “incorrect”- they continue to be used frequently. He also presents a

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real-life example to illustrate the valuation of a company as the sum of the value of different

businesses, which is usually called the break-up value. The last section is a list that contains the

most common errors that the author has detected in the more than one thousand valuations he has

had access to in his capacity as a business consultant or teacher.

A simple valuation model is presented in which a firm can invest in projects with positive net

present values for a limited number of years. Although prior models have made this assumption,

the model of Danielson M. G. (1998) can be simplified to a concise, easy-to-use form. The model

can facilitate a broad understanding of the expectations implied by a firm's stock price—for

example, growth patterns consistent with a firm's price to earnings ratio—which can guide

in-depth analysis of prices.

Frankel, R. & Lee, C. M. (1998) test the residual income model of Ohlson (1995) operationalized

with analysts’ earnings forecasts. They find that the model predicts abnormal returns over one-,

two, and three-year holding periods. Specifically, a portfolio constructed by taking a long

position in the most undervalued quintile of firms and a short position in firms in the most

overvalued quintile produces cumulative returns of 3.1%, 15.2%, and 30.6%, over one-, two-,

and three-year holding periods. Herzberg (1998) shows that Frankel and Lee's results can be

improved further by using more refined model estimation procedures.

More academic research compares the Cash Flow Discount and various Residual Income models.

The evidence regarding the relative superiority of these models is mixed. Bernard, V. L. (1995),

Penman, S. H., & Sougiannis, T. (1998), Frankel, R. & Lee, C. M. (1998) and Francis, J., Ohlson,

P., & Oswald, D. (2000) find that the Residual Income valuation models predict or explain stock

prices better than the models based on discounting short-term forecasts of dividends or cash

flows (Rawley and Benton, 2009).

On the other hand, provide studies by Stober, T. L. (1996), Dechow, P. M., Hutton, A. P., &

Sloan, R. G. (1999), Myers, S. C. (1999) and Callen, J. L. & Morel, M. (2000) evidence that the

Residual Income model is of limited empirical validity. Demirakos, E., Strong, N., & Walker, M.

(2004) assert that analysts use the Discounted Cash Flow model most widely in practice, but that

the Residual Income valuation model is gaining popularity. Penman, S. P. (2001) advocates the

Residual Income valuation model in preference to the Discounted Cash Flow model. Copeland,

T., Koller, T. & Murrin, J. (2000) recommended using either the Discounted Cash Flow model or

the Residual Income valuation model.

According to Bancel, F., & Mittoo, U. (2014), “the Discounted Cash Flow and Relative

Valuation Approach are equally popular methods. In order to do relative valuation correctly, we

need to understand the fundamentals of discounted cash flows valuation. About 80 percent of

experts use both Discounted Cash Flow and Relative Valuation, and less than 40 percent use the

free cash flow to the equity method. less than 22 percent of experts use Discounted Cash Flow

growth models, and rarely use Economic Value-Added models.” They also found that most

experts use more than one valuation method. They use two valuation methods to calculate the

value of a company. The combination of the Discounted Cash Flow and Residual Income

valuation approaches is the most popular used by over 67 percent of respondents. The

prominence of the Discounted Cash Flow and Residual Income valuation approaches reflects

their dominance in textbooks and CFA curriculum’ (Bancel, F., & Mittoo, U., 2014).

While Relative Valuation or Price Multiple models are used extensively in practice, there exists

little published academic research documenting the relative superiority of different multiples.

Most commonly used is, however, the earnings multiple approaches (Demirakos, E., Strong, N.,

& Walker, M., 2002). In many situations, multiple methodologies are used to eliminate outliers

and derive as accurate an estimate of values as possible. In the survey, conducted by Groenewald,

J, Human, M., Gumel, F., & Agarwal, V. (2012), the price/earnings multiple is the most

frequently used valuation multiple in the application of the market approach. Also, the market

value of invested capital to earnings before interest, taxes, depreciation, and amortization ratio is

prevalent when valuing using multiples. There were also few adjustments made by financial

analysts to observed comparable company multiples. According to Groenewald, J. (2012), ‘All

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respondents indicated that they consider making adjustments in determining appropriate

multiples in terms of the market approach. Although the adjustments are frequently or always

considered, whether an adjustment will be applied will depend on the facts and circumstances of

the specific valuation’.

Penman, S. H., & Sougiannis, T. (1998) and Francis, J., Ohlson, P., & Oswald, D. (2000)

compared the bias and accuracy of the dividend discount model, discounted cash flow model, and

Edwards-Bell-Ohlson residual income model in explaining the relation between value estimates

and observed stock prices. Both studies report that, with non-price-based terminal values,

residual income model outperforms a discounted cash flow model and dividend discount model.

Courteau, L., Kao, J. L., & Richardson, G. D. (2000) primary explore whether, over a five-year

valuation horizon, dividend discount model, discounted cash flow model and

Edwards-Bell-Ohlson residual income model, are empirically equivalent when Penman's (1998)

theoretically "ideal" terminal value expressions are employed in each model. Using Value Line

terminal stock price forecasts at the horizon to proxy for such values, they find empirical support

for the prediction of equivalence between these three price-based valuation models. Secondary,

they demonstrate that, within each class of the discounted cash flow and residual income model

valuation models, the model that employs Value Line forecasted price in the terminal value

expression would generate the lowest pricing errors, compared to models that employ

non-price-based terminal value under an arbitrary growth assumption. Results indicate that, for

both discounted cash flow and residual income model, price-based valuation models outperform

the corresponding non-price-based models by a wide margin. They also revisit the issue of the

apparent superiority of the residual income model and find that this result does not hold in a level

playing field where an approximation of typical terminal values is employed. The price-based

residual income model is marginally outperformed by the price-based discounted cash flow and

dividend discount models in terms of pricing errors, as well as its ability to explain the current

market price.

Panda, S. (2013) uses a valuation model based on the Discounted Cash Flow Method that

calculates the quarterly intrinsic values of selected Indian stocks for the year 2010. The

calculated intrinsic values are compared with the corresponding market values in order to know

whether the model is capable enough to capture the market price or not. Welch’s t-test is

conducted to check the significance level between the two values and robustness of the model.

Selected “A” category companies are taken for the study, and the period of the study is from 1st

January 2001 to 31st December 2010.

In evaluating how much attention and weight to give to a recommendation of analyst reports, the

researchers examine the risk and return prospects, the prospects for both the industry and the

company, the quality of the valuation and recommendation, the historical, descriptive statistics

about the industry and company.

Since this approach does not provide enough evidence for researchers to conclude the

information that they can get from sell-side analysts’ reports in doing valuations, a different

approach, such as the approach of sell-side analysts for direct observation.

Schipper (1991), Brown (1993), and mainly Bradshaw (2011) suggest further research indirectly

observing the analysts’ decision process of analysis in contrast to examine correlations between

financial inputs, outputs, and conditioning variables to understand the analysis process and bases

for recommendations. In this project, we consider this type of approach as an approach of

sell-side analysts used to study analysts’ valuations process.

THE APPROACH OF SELL-SIDE ANALYST (AND MOTIVATION)

There are several ways a researcher can adapt to the sell-side analyst approach study analysts’

valuation process. They include practical tests of combining several valuation models, case

studies, real-life examples to value firms, projects, and portfolios. However, few studies have

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attempted to use such a direct approach to observe analysts’ valuation process. Investment

research reports are another category that can be found in international competitions like CFA

Institute Research Challenge and recently, Ben Graham Center’s stock pricing competition.

Fernandez, P. (2001) focuses on equity valuation using multiples. His necessary conclusion is

that multiples nearly always have broad dispersion, which is why valuations performed using

multiples may be highly debatable. He revises the 14 most popular multiples and deals with the

problem of using multiples for valuation: their dispersion. One thousand two hundred multiples

from 175 companies illustrate the dispersion of multiples of European utilities, English utilities,

European constructors, hotel companies, telecommunications, banks, and Internet companies. He

also shows that Earnings before interest, taxes, depreciation, and amortization and Profit after

Tax (the most commonly used parameters for multiples) were more volatile than equity value. He

also provides additional evidence of the analysts' recommendations for Spanish companies: less

than 15% of the recommendations are to sell. However, multiples are useful in a second stage of

the valuation: after performing the valuation using another method, a comparison with the

multiples of comparable firms enables us to gauge the valuation performed and identify

differences between the firm valued and the firms it is compared with.

Bhojraj, S. & Lee, C. M., C. (2002) present a general approach for selecting comparable firms in

market-based research and equity valuation. Guided by valuation theory, they develop a

“warranted multiple” for each firm and identify peer firms as those having the closest warranted

multiple. They test this approach by examining the efficacy of the selected comparable firms in

predicting the future (one- to three-year-ahead) enterprise-value-to-sales and price-to-book ratios.

Their tests encompass the general universe of stocks as well as a sub-population of so-called

“new economy” stocks. They conclude that comparable firms selected in this manner offer sharp

improvements over comparable firms selected based on other techniques.

Among many others show Basu, S. (1977), Lakonishok, J., Shleifer, A. & Vishny, R., W. (1994),

and Dreman, D. (1998) that low price/earnings stocks earn positive abnormal returns relative to

the market and high price/earnings stocks negative abnormal returns. Peavy, J. W., & Goodman,

D. A. (1983) find the same using industry relative price/earnings ratios. Peters, J. M. (1991) test

the Price/Earnings to Growth ratio approach and finds significant higher returns for low

Price/Earnings to Growth stocks than for high Price/Earnings to Growth stocks. Peavy, J. W., &

Goodman, D. A. (1983), again, among many others, find that low Price to Book Ratio (or low

book-to-market ratio) stocks perform better than stocks with high such ratios.

Fama and French (1992) and Dreman (1998), again among many others, find that low Price to

Book Ratio (or low book-to-market ratio) stocks perform better than stocks with high such ratios.

Capaul, C., Rowley, I., & Sharpe, W. (1993) extend the analysis of Price to Book ratios across

international markets and conclude that low multiple stocks earn abnormal returns in every

market they analyzed. The results of studies on the price to sales ratio and price to cash flow ratio

and even price to dividend yield ratio are no different (Dreman, D., 1998).

According to Damodaran A. (2002), “Discounted Cash Flow model is the foundation on which

all other approaches are built upon.” Luehrman (1997) states that in the 1970s-discounted cash

flow analysis emerged as best practice for valuing corporations. He states that with today’s

improved computers and data, he states that the Discounted Cash Flow model would work better

than ever, but other valuation methodologies improve through this way too. He also states that:

Companies will routinely use more than one formal valuation methodology, and the Discounted

Cash Flow model will remain the foundation of most formal valuation analyses.

DeFond, M. L., & Hung, M. (2003) investigate the recent trend in analysts disseminating

operating cash flow forecasts. They find that analysts tend to forecast cash flows for firms were

accounting, operating, and financing characteristics suggest that cash flows are useful in

interpreting earnings and assessing firm viability. Specifically, they find that analysts tend to

forecast cash flows for firms with

1. substantial accruals,

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2. more heterogeneous accounting choices relative to their industry peers,

3. high earnings volatility,

4. high capital intensity, and

5. poor financial health.

These findings are consistent with financial analysts responding to market-based incentives to

provide market participants with value-relevant information.

Mear, R., & Firth, M. (2012) attempt to test the relevance of accounting and other market-related

information in a risk-assessment task by a laboratory experiment using the Brunswik lens model

framework, estimates of ex-ante risk on thirty stocks were regressed against nine

company-specific cues and one industry variable. The results provide substantial evidence that

publically available accounting and financial data convey information relevant for security risk

evaluation.

Dreman, D. N., & Berry, M., A. (1995) offered a perspective on analyst earnings forecast errors

and their implications for security analysis. Among other arguments, they contended that the

errors are too large to be reliably used by investors, the forecasts are less accurate than forecasts

by time-series models, the errors are increasing over time, the analysts' forecasts are too

optimistic, and the investment community relies too heavily on analyst forecasts. Brown, L. D.

(1996) provides an alternative perspective on these issues. The argument is that analysts' forecast

errors are within 3 percent of an appropriate benchmark (namely, stock price), that their forecasts

generally are significantly more accurate than forecasts by naive or sophisticated time-series

models, that analyst forecast errors have not been increasing over time, that analysts have been

too pessimistic in recent years, and that the investment community relies too little on analysts'

forecasts by placing too much weight on forecasts made by time-series models.

Mikhail, M. B., Walther, B. R., & Willis, R. H. (1999) investigate if earnings forecast accuracy

matters to security analysts by examining its association with analyst turnover. Controlling for

the firm‐ and time‐period effects, forecast horizon, and industry forecasting experience, they find

that an analyst is more likely to turn over if his or her forecast accuracy is lower than his peers.

They find no association between an analyst's probability of turnover and his absolute forecast

accuracy. They also investigate another observable measure of the analyst's performance, the

profitability of his stock recommendations. There is no statistical relationship between the

absolute or relative profitability of an analyst's stock recommendations and his or her probability

of turnover. They interpret their findings as indicating that forecast accuracy is important to

analysts.

Empirical evidence in Kim, M. & Ritter, J. R. (1999) and Liu, J., Nissim, D., & Thomas, J.

(2002) suggest that in the earnings multiple approaches forward earnings perform better than

historical earnings. Liu, J., Nissim, D., & Thomas, J. (2002) show that in terms of accuracy

relative to current prices, the performance of forwarding earnings is followed by that of historical

earnings, cash flow, book value, and finally sales. Furthermore, find Liu, J., Nissim, D., &

Thomas, J. (2002) that contrary to the popular view that different industries have different ‘best’

multiples, the previous rankings are observed consistently for almost all industries examined.

Studies over many decades and in different countries have shown that low multiple stocks (value

stocks) perform better than high multiple stocks (growth stocks). Plenborg, T., & Pimentel, R. C.

(2016) identify a more effective way to handle each implementation issue in order to enhance the

accuracy of valuation outputs. By synthesizing the main empirical findings and thereby

identifying best practices when applying market multiples, and they expect to help analysts,

portfolios managers, and investment bankers make more informed decisions when accessing a

firm’s value.

Skantz, T. R., & Marchesini, R. (1992) use a discount cash flow model to value liquidating firms

where the cash flows and growth patterns are known. They conclude that the market appears to

value stocks by discounting expected cash flows using a risk-adjusted required rate of return. The

uniqueness of their sample, however, generalizes to going concern companies difficult.

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Penman, S. H. (1998) lays out alternative equity valuation models that involve forecasting for

finite periods and shows how they are related to each other. He contrasts dividend discounting

models, discounted cash flow models, and residual income models based on accrual accounting.

Penman shows that some models that are different yield the same valuation. He gives the general

form of the terminal value calculation in these models and shows how this calculation serves to

correct errors in the model. Penman also shows that all models can be interpreted as providing a

specification of the terminal value for the dividend discount model. In so doing, he shows how

one calculates the terminal value for the dividend discount formula. The calculation involves

weighting forecasted stocks and flows of value with weights determined by a parameter that can

be discovered from pro forma analysis.

A simple study of the dividend discount model was conducted by Sorensen, E. H., and

Williamson, D. A. (1985), who valued 150 stocks from the S&P 400 in December 1980. They

use the difference between the market price and the intrinsic value obtained from the model to

form five portfolios based upon the degree of under- and overvaluation. They make reasonably

broad assumptions by testing the dividend discount model:

1. the average of the earnings per share between 1976 and 1980 is used as the sustainable

earnings per share,

2. the cost of equity is estimated using the CAPM,

3. the extraordinary growth period is assumed to be five years for all stocks,

4. the I/B/E/S consensus forecasts of earnings growth are used as the growth rate for this

period,

5. the stable growth rate is assumed to be 8% for all stocks, and

6. the payout ratio is assumed to be 45% for all stocks.

Sorensen, E. H., and Williamson, D. A. (1985) also test whether the investment performance

could be increased by using more sophisticated models and tests; therefore, one-, two-, and

three-stage dividend discount models. They conclude that model performance improves as model

sophistication increases.

Bond, S. R., and Cummins, J. G. (2004) investigate the empirical relationship between

company investment and measures of uncertainty, controlling for the effect of expected future

profitability on current investment decisions. They consider three measures of uncertainty

derived from

1. the volatility in the firm's stock returns;

2. disagreement among securities analysts in their forecasts of the firm's future profits; and

3. the variance of forecast errors in analysts' forecasts of the firm's future profits.

Bond, S. R., and Cummins, J. G. (2004) consider two controls for expected profitability:

1. a standard measure of Brainard-Tobin's q constructed from the firm's stock market

valuation; and

2. an alternative measure of the q ratio constructed from discounted forecasts of the firm's

future profits.

Their sample consists of publicly traded U.S. companies that were tracked by two or more

securities analysts for at least four consecutive years between 1982 and 1999.

The results show that all three measures of uncertainty are positively correlated and appear to

pick up underlying movements in uncertainty. When they consider these measures individually,

they find a significantly negative long-run effect of higher uncertainty on capital accumulation,

which is robust to the inclusion of either of our controls for expected profitability. When they

consider our uncertainty measures jointly, they find that the level of disagreement among analysts

provides the most informative indicator for identifying this long-run effect of uncertainty on

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capital accumulation. Besides, they find a significantly negative short-run interaction term

between share price volatility and current sales growth, consistent with the idea that investment

will respond less to a given demand shock at higher levels of uncertainty. These effects of

uncertainty on investment are shown to be quantitatively, as well as statistically significant.

Empirical accounting research provides surprisingly little evidence on whether accounting

earnings numbers capture cross‐sectional differences in risk that are associated with

cross‐sectional differences in share prices. Baginsk, S. P., and Wahlen, J. M. (2002) address two

questions regarding the risk‐relevance of accounting numbers:

1. Are accounting‐related risk measures (i.e., the systematic risk and total volatility in a

firm's time‐series of residual return on equity) associated with the market's assessment

and pricing of equity risk?

2. If so, then are these accounting‐related risk measures incrementally associated with the

market's assessment and pricing of equity risk beyond other observable factors, such as

those in the Fama and French (1992) three‐factor model?

So, they develop an accounting‐fundamentals‐based measure of the market's pricing of risk—the

difference between actual share price and a residual income valuation model estimate of share

value using risk‐free rates of return. Their results show that both systematic risk and total

volatility in residual return on equity partially explain this pricing differential and that the

explanatory power of total volatility is incremental to the Fama and French (1992)

factors—market beta, firm size, and the market‐to‐book ratio.

As we can see, studies using the approach of sell-side analysts can provide us with the more

helpful information in studying analysts’ valuations that we cannot get from using an approach of

empirical studies. That information can help us to address issues such as how do analysts use

financial information to generate valuations and stock recommendations. However, investment

research reports of valuation models are rare in the academic literature, and we still need to

consider limitations that this approach has. For example, assumptions and limitations regarding

the application of valuation methods are significant concerns for firms’ valuation studies.

Furthermore, we did not find any study that uses an investment research report as a method to

examine the valuation process from the approach of sell-side analysts.

The possible explanation of having no researcher uses this approach is that the investment

research reporting is a complicated and time-consuming process. Besides that, it is challenging to

find analysts that are willing to cooperate with researchers to go through the investment research

report process except for competition concepts like CFA research challenge and recently Ben

Graham Center’s stock pricing competition.

CONCLUSION/ DISCUSSION

In conclusion, we have learned a lot about analysts’ valuation process. We are now able to

differentiate the empirical studies (based on elements of analyst reports and interviews) and

sell-side analyst approaches used to study analysts’ valuation process. We also addressed the

advantages and limitations associated with both empirical studies and sell-side analyst

approaches. As a result of this study, we conclude that both approaches are helpful in and

required for examining and studying analysts’ valuation processes; using only one of the two

approaches is not enough for us to have a clear understanding of analysts’ valuation process.

To date, researchers have conducted a considerable amount of studies with empirical studies

approach. Researchers are encouraged to switch their focuses to the use of a sell-side analyst

approach in examining the valuation process. For those that are going to observe analysts’

valuation process from the sell-side analyst approach, a few more methods that have not yet been

practiced may be considered. They are included: investment research reports beyond valuation

models that can be found in international competitions like CFA Institute Research Challenge

and recently, Ben Graham Center’s stock pricing competition regarding their decision-making

process.

page 15 from 21

Both above, create challenges for academic research. This potential is not yet been adequately

explored. We must prepare to meet the challenges and respond to opportunities for this trend.

Given this theoretical difference between the methods, perhaps the paper could investigate better

whether different approaches to valuation can have a different impact on the output of the

valuation process conducted by practitioners.

Several tests and observations on how different valuation methods and practices forecast the

share price, calculate the forecast error (i.e. the difference between the actual and the predicted

price) and affect the accuracy of target prices, are offered since personal attempt and experience

with conducting investment research report in the same way that it is approaching from the

professionals, by competing in the CFA Institute Research Challenge representing University of

Macedonia (four months of full-time research during my master). It has received excellent

reviews, mentoring by an experienced professional. Any effort from researchers into improving

the limitations that previous studies have encountered is strongly encouraged. I hope that this

paper can make a positive contribution to this direction.

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ACKNOWLEDGMENT

This research was published, presented, and discussed at the 5th Spring Conference of the

Multinational Finance Society. It is a postprint. The implementation of the Ph.D. thesis or related

research papers was supported by the State Scholarships Foundation-IKY (seventeen months).

The participation with research paper to scientific conference was supported by the University of

Macedonia’s Unit of Special Account for Research Funds-ELKE followed the decision of the

Faculty Assembly. The planning and presentation of the Ph.D. Thesis supervised by 3-faculty

member advisory committee (1. assoc. professor Stavropoulos A.-supervisor, 2. assist. professor

Dassilas A. who replaced professor Negakis C. who replaced professor Vazakidis A., 3. professor

Refanidis I.) with four annually and five more quarterly progress reports, MSc Thesis supervised

by professor Dimitrios Papadopoulos, BSc Thesis supervised by professor Despina

Makridou-Boussiou. The Chartered Financial Analyst Society provided the support that was the

CFA Research Challenge, the related meetings and a book on equity asset valuation. The

Multinational Finance Society and the Hellenic Finance and Accounting Association provided

the support that was Tutorial Sessions, Panel Sessions “Improving Research in Accounting and

Finance,” Keynote Speeches, and Discussion Sessions at their Conferences. Participants at the

conferences of the Multinational Finance Society (professor Anna Giannopoulou-Merika - Deree

College, Greece, which indicated the attendance of the Conference entitled «26th EFMA», assoc.

professor Neofytos Lampertidis - Technological University, Cyprus), at the conferences of the

Hellenic Finance and Accounting Association (prof. Michalis Bekiaris - University of the

Aegean, Greece), at two other international conferences (professor Dimitrios Koysenidis -

Aristotle University of Thessaloniki, Greece, professor Pavlos Malindretos) and at an

international university competition / local CFA Research Challenge (Mr. Dimitris Karydas –

CFA mentor, Mr. Ioannis Ritsios- CFA chair, professor Ioannis Lazaridis, and lecturer Simos

Papadopoulos – faculty advisors, Panel of Experts or Examination Committee, Participants),

provided the written reports or discussions on the author’s previous research papers. Reviewers in

the Multinational Finance Journal (professor Theodossiou P. - Editor-in-Chief and the Referees)

provided the written reports on the author’s previous research article.

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