the value relevance of comprehensive income545222/fulltext01.pdfmaster thesis: department of...

UPPSALA UNIVERSITY

Department of Business Studies

Master Thesis

Spring Semester 2012

Authors: Elena Ringström

and Jörgen Ekström

Supervisor: Katarzyna Cieslak

Date of submission: May 25, 2012

The value relevance of comprehensive income

ors: Elena Ringström

Jörgen Ekström

1

Abstract

Master thesis: Department of Business Studies at Uppsala University

Authors: Elena Ringström and Jörgen Ekström

Title: The value relevance of comprehensive income

Background: In this study, we look at the effects of the adoption of the revised IAS 1 rules, which

has been in effect since January 1, 2009. The revised IAS 1 requires that all changes in equity,

excluding changes in equity arising from transactions with owners, should be recognized in

comprehensive income statement. Revised IAS 1 requires companies to report total comprehensive

income that is a sum of net income and other comprehensive income. Total comprehensive income

includes all unrealized gains and losses recognized under IFRS. Before the amendment, some of the

unrealized gains and losses were shown in a statement of changes in equity but not in the income

statement.

Research problem: We hope to answer the question whether inclusion of the components of other

comprehensive income provides investors with useful information. We investigate if stock prices

have an association with the components of other comprehensive income. We investigate how

effective are attempts of IASB to increase the relevance of accounting information about corporate

income. We hope that results from the study will be of interest to the standard-setter.

Research design: In this study, we use data from annual reports and year-end reports for companies

listed on the Large and Mid Cap segment at NASDAQ OMX Stockholm and that covers the years

2009 to 2011. We use two regression models to test value relevance of components of other

comprehensive income.

Empirical findings: We have found some evidence that the share price statistically relates to such

component of comprehensive income as the change of the fair value of cash flow hedges. This can

also be interpreted as that the change of the fair value of cash flow hedges has some value

relevance. We also found some evidence that the share price significantly associates with winning

cash flow hedging position. We did not find that the share price associates with some other

components of other comprehensive income.

Keywords: Value relevance, Comprehensive income, Components of other comprehensive income,

Revised IAS 1, Fair value.


Jörgen Ekström

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Table of contents

Abstract ................................................................................................................................................ 1

Table of contents .................................................................................................................................. 2

1. Introduction ...................................................................................................................................... 3

1.1 Background ................................................................................................................................ 3

1.2 Research problem ....................................................................................................................... 5

2. Theory .............................................................................................................................................. 8

2.1 Theoretical framework ............................................................................................................... 8

2.1.1 Income concepts .................................................................................................................. 8

2.1.2 Clean surplus accounting .................................................................................................... 9

2.2 Previous research ..................................................................................................................... 10

3. Method ........................................................................................................................................... 14

3.1 Data collection and sample ...................................................................................................... 14

3.2 Research design........................................................................................................................ 16

4. Empirical analysis .......................................................................................................................... 22

4.1 Regression model 1 .................................................................................................................. 22

4.2 Regression model 2 .................................................................................................................. 25

5. Discussion and conclusions ........................................................................................................... 29

5.1 Discussion ................................................................................................................................ 29

5.2 Conclusions, limitations and further research .......................................................................... 31

6. References ...................................................................................................................................... 32


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“Information is a source of learning. But unless it is organized, processed, and available to the

right people in a format for decision making, it is a burden, not a benefit.”- William Pollard (n.d.)

1. Introduction

1.1 Background

From January 1, 2009, The International Accounting Standards Board (IASB) implemented revised

IAS 1 that has changed a presentation of the income statement. According to the revised IAS 1,

listed companies have to report on comprehensive income, in addition to net income. Total

comprehensive income is a sum of net income and other comprehensive income. It should be noted

that total comprehensive income includes all unrealized gains and losses recognized under IFRS

regulation (Kabir and Lasward, 2011, p. 270). These unrealized gains and losses mainly arise from

the fair value changes in the balance sheet accounts. Comprehensive income is ‘all-inclusive’

income that is also known as ‘clean surplus’ income. In contrast, before the amendment, listed

companies had to do some certain transactions into equity and show them in the statement of

changes in equity instead of the income statement. These transactions were known as ‘dirty surplus’

components of (non – all – inclusive) income (Pronobis and Zülch, 2011). Lönnqvist (2011)

confirms that, before the amendment, some revaluation changes in fair values were recognized in

the statement of changes in equity because of the precautionary principle since these revaluations

could be difficult to realize.

In this study, we look at the effects of the adoption of the revised IAS 1 standard that was caused by

the convergence project between IASB and Financial Accounting Standards Board (FASB). IASB

has decided to revise IAS 1 regarding the presentation of comprehensive income similar to make it

similar to SFAS 130 that was issued by FASB in 1997 (IFRS Foundation, 2011, p. IN3 A552).

FASB introduced the definition of comprehensive income in the Statement of Financial Accounting

Concepts No. 5 “Recognition and Measurement in Financial Statements of Business Enterprises” as

“the change in equity (net assets) of an entity during a period from transactions and events and

circumstances from non-owner sources. Comprehensive income includes all changes in equity

during a period except those resulting from investments by owners and distributions to owners”

(Schroeder, Clark, and Cathey, 2001, p. 111).


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The revised IAS 1 follows FASB’s definition of comprehensive income and suggests that all

changes in equity, excluding changing in equity arising from transactions with owners, are

recognized in comprehensive income statement (IFRS Foundation, 2011, p. IN13 A553 f.). Other

comprehensive income includes incomes and expenses that are not recognized in the profit or loss

as permitted or required by other IFRSs (IAS 1, 2011, p. 7). Other comprehensive income includes

unrealized gains and losses resulting from changes in fair values of assets/liabilities such as:

changes in revaluation amount of property, plant and equipment (IAS 16)

changes in fair value of intangible assets (IAS 38)

actuarial gains and losses on defined benefit plans (IAS 19)

gains and losses from translating the financial statements of a foreign operation (IAS 21)

changes in fair value of available-for-sale financial instruments (IFRS 9)

changes in fair value of a hedging instruments in a cash flow hedge (IAS 39)

According to US GAAP, other comprehensive income includes foreign currency items, minimum

pension liability adjustments, unrealized gains and losses on certain investments in debt and equity

securities. In addition, according to SFAS 130 the components of other comprehensive income can

be reported in three ways as below the total for net income in an income statement, a separate

statement that starts with net income, or in a statement of changes in equity (Schroeder et. al, 2001,

pp. 115-117). However, revised IAS 1 does not permit reporting of other comprehensive income in

a statement of changes in equity (IFRS Foundation, 2011, p. IN13 A553 f.). It implies that there are

some differences in components and presentation of other comprehensive income between IFRS

and US GAAP. Consequently, prior research on total and other comprehensive income conducted in

Anglo-Saxon countries cannot be fully generalized to reporting of comprehensive income in

European countries and according IAS 1.

The ideas of clean surplus relation have influenced this new way of reporting (Kanagaretnam,

Mathieu, and Shehata, 2009; Smith, 2006, p. 280). Clean surplus relation proposes that gains and

losses should not be recognized directly in equity (Sundgren, Nilsson H. and Nilsson S., 2007, p.

37). That can be interpreted as clean surplus relation suggests that all gains and losses (even

unrealized) should be recognized in the statement of profit and loss. Before the amendment of IAS

1, some non-owner changes in equity could be recognized in equity which was not consistent with


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clean surplus relationship (Smith, 2006, p. 280). Hence, one can suggest that since the previous way

of reporting of income violated clean surplus relation, it was called in the literature as ‘dirty

surplus’ income.

For example, before the introduction of comprehensive income, if there was an increase of the

carrying amount of item of property, plant and equipment (IAS 16), it was credited to revaluation

reserve in equity but was not recognized in the statement of profit and loss. This was because of the

precautionary principle in order to separate short-term revaluation fluctuations from operating

profit. However, it was a departure from clean surplus relation (Sundgren et. al., 2007, p. 86). After

the amendment, if there is a revaluation increase it shall be credited to a revaluation reserve and

recognized as “other comprehensive income” in the statement of comprehensive income. If there is

a revaluation decrease of property, plant and equipment items it shall be debited to the revaluation

reserve and recognized as a negative number in other comprehensive income to the amount of any

credit balance earlier existing in the revaluation reserve relative to the same asset (Melville, 2011, p.

81).

This accounting procedure attempts to signal that unrealized revaluation gains in other

comprehensive income are not converted to cash and consequently cannot be paid as a dividend

(Melville, 2011, p. 81). It can be interpreted in this way that IAS 1 tries to follow clean surplus

relation when showing unrealized gains and losses in the income statement as other comprehensive

income. At the same time, the separate post of other comprehensive income attempts to point out to

the users that these gains and losses are not “real” enough to recognize them in net income.

1.2 Research problem

IASB states that the main purpose of the extension of the income concept was to provide users of

financial statements with more relevant information (IAS 1, 2011). FASB confirms that reporting of

comprehensive income would help investors and other users of financial reports in evaluating of

firms’ financial performance and their future cash flows (Schroeder et. al., 2001, p. 116).

Furthermore, the position of comprehensive income signals to investors that it contains valuable

information (Schroeder et. al., 2001, p. 118). The regulator by requiring that comprehensive income

should be presented in the income statement wants to communicate to the capital market that the

information in comprehensive income can contain significant and relevant information.


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Ball and Brown (1968) found that the content of the company's income number was considerably

crucial for investors. The study justified as well that information about companies’ annual income

has a connection with the stock prices (Ball and Brown, 1968). This might also be interpreted in this

way that Ball and Brown (1968) showed that the income number was value relevant for investors.

Based on the above discussion, an assumption can be made that the inclusion of additional

information in the companies’ income will affect the capital market.

Since 2005, all listed companies within EU have to report with accordance to IFRS standards (FAR,

2011). The main change caused by implementation of IFRS was move towards fair value

accounting for assets and liabilities (Penman, 2007; Sundgren et. al., 2007). There has been a

significant growth in the use of fair value accounting for assets in Sweden since the implementation

of IFRS (Sundgren et. al., 2007). One of advantages of fair value accounting appears to be

providing of more relevant accounting information to the investors (Penman, 2007). However, the

use of fair values without active market prices with the help of valuation models based on expected

future cash flows might be subjective and, hence, volatile financial statements (Penman, 2007;

Sundgren et. al., 2007). Other comprehensive income adjusts unrealized gains and losses arising

from the fair value changes those before the amendment of IAS 1 were booked in a statement of

changes in equity (Lönnqvist, 2011). The study of Ball and Brown (1968) was many years ago, and

it is appealing to check how much accounting is relevant now, especially in the more turbulent

times, when relevance of accounting can be questioned. IASB makes an attempt to enhance the

relevance of accounting with the changes in IAS 1. It is of great importance to investigate the

success of these attempts by asking how the other comprehensive income components are relevant

for investors. This is what the aim of the study is.

To the present time, there has been an extensive research conducted on the value relevance of

comprehensive income compared to net income in Anglo – Saxon countries (Pronobis and Zülch,

2011). The implementation of SFAS 130 in 1997 caused considerable research on the value

relevance of comprehensive income (Pronobis and Zülch, 2011). The study of Kanagaretnam et. al.

(2009, p. 349) who used data from Canadian companies found that comprehensive income had a

stronger explanatory power and association with stock prices and stock returns than net income.

This study has also found that the share price and stock returns associated with some components of

other comprehensive. On the contrary, the study of Dhaliwal, Subramanyam and Trezevant (1999)

established that only one component of other comprehensive income had an association with stock


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returns. However, not much research has been done on value relevance of transactions in equity

(‘dirty surplus’ flows) in EU countries including Sweden (Roberts and Wang, 2009). In contrast to

Anglo – Saxon countries, the issue of addition of other comprehensive income is new in Europe;

hence, there has been no research conducted on value relevance of components of other

comprehensive income after the amendment of IAS 1.

Earnings might be interpreted as one of the most powerful accounting measures that are of interest

to investors. In view of capital market research, investors can be seen as primary users of financial

statements (Ball and Brown, 1968; Kothari, 2001). Professional and non – professional investors

who apply fundamental analysis of business valuation widely use such accounting measure as

earnings (Barker, 2001; Larsson, 2008; Palepu, Healy, Bernard and Peek, 2007). To evaluate

whether inclusion of additional information in the income number affects capital market there might

be a need to study if stock prices react to additional accounting information included in the

components of other comprehensive income. We hope to answer the question whether reporting on

the components of other comprehensive income provides capital market (investors) with useful

information. We investigate if stock prices have an association with the components of other

comprehensive income. According the prior researches, we expect that some components of other

comprehensive income are associated with stock prices.

In line with other studies on value relevance of comprehensive income (Kanagaretnam et. al., 2009;

Pronobis and Zülch, 2011), as well as the IASB's Conceptual Framework (2011), we suggest

investors as primary users of financial statements. From a practical point of view, since we study

association between share price and accounting information, we believe that the study might be

especially useful for non-professional investors those make business evaluation without

professional investment help. Furthermore, we hope that the study might be stimulating for scholars

working in the field of accounting research. The results from the study might be also relevant for

the standard-setter since it provides empirical evidence on the use of accounting standards in

Sweden one of EU countries. In addition, the results from the study of association between the share

price and accounting information might be of interest to the listed companies since capital market is

a source of their financing.


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2. Theory

2.1 Theoretical framework

2.1.1 Income concepts

According to Riahi-Belkaoui (2000, pp. 385-388), the theory and measurement of business income

has always been a prominent area of financial and managerial accounting. In spite of different

measures and measurement methods, the concept of income remains the central subject of various

interpretations. The classical school of thoughts applies historical - cost principle and defines

business income as “accounting income”. Accounting income is the difference between the realized

revenues of the period and the matching historical costs. However, accounting income has been

insensitively criticized for its limitations (Riahi-Belkaoui, 2000, p. 390). One of the arguments

against accounting income is it does not recognize unrealized increases in values of assets because

of the application of historical-cost and realization principle. This allows the recognition of a

various gains from the past and present periods and, as a result, the net income does not match, in

fact, the income of the current period (Riahi-Belkaoui, 2000, p. 390).

Riahi-Belkaoui (2000, pp. 390-391) describes that income concept has also been a point of

considerable interest to economists. Adam Smith described income as “an increase in wealth”.

Following Smith’s ideas, Alfred Marshall connected concept of income to business practices.

Fisher, Lindahl and Hicks developed a concept of economic income. According to Van

Cauwenberge (2007, p. 21), Hicks described firm’s profit as value changes over the level that is

needed to maintain the value of firm’s capital (net assets). Therefore, Van Cauwenberge (2007)

argues that Hicks’ concept of income as capital maintenance supports the concept of comprehensive

income.

The concept of capital maintenance suggests that income is recognized after capital is maintained

and expenses are recovered (Riahi-Belkaoui, 2000, p. 391). Financial capital maintenance means

that the financial (money) amount of company’s net assets at the end of the accounting period goes

over the financial amount of the net assets at the beginning of the period, except transactions with

owners (Schroeder et. al., 2001, p. 64). One can see similarities between definition of


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comprehensive income and content of the concept of financial capital maintenance. Therefore, it

can be understood that the idea of financial capital maintenance supports the concept of

comprehensive income.

In addition, the concept of financial capital maintenance considers that holding gains and losses

should be included in income. Holding gains and losses arise from the value of items in the balance

sheet changes (Schroeder et. al., 2001, p. 65). Riahi-Belkaoui (2000, p. 398) mentions that holding

gains and losses occur when assets and liabilities those a firm owes or holds measured in fair

values. Holding gains and losses can be separated in two groups. The realized holding gains and

losses concern the items sold or to the liabilities paid and non-realized gains and losses relate to

items still held and liabilities still owed. With reason that the concept of financial capital

maintenance proposes to include all holding gains and losses in income, one can say that it supports

the model of comprehensive income presented by IASB.

2.1.2 Clean surplus accounting

Concept of comprehensive income or “all-inclusive” income is consistent with the accounting

system that is known as clean surplus relation (Christensen and Feltham, 2003, p. 280). The book

value of equity is the difference between company’s assets and liabilities and can be called the

owners’ “surplus”. Clean surplus relation means the accounting system that recognizes all changes

in the owners’ “surplus” and exchanges of cash between the firm’s owners as well as earnings

(Christensen and Feltham, 2003, p. 280). More exactly, the clean surplus relation suggests that

comprehensive income (earnings) is equal to change in equity during a period increased by issues of

new shares and reduced by dividends to shareholders (Barker, 2001; Ohlson, 1995):

CIt = BVt – BVt-1 – dt

Where:

BVt = book value of the firm’s equity, date t

BVt-1 = book value of the firm’s equity date, t-1

CIt = comprehensive income for period (t-1, t)

dt = dividends, net of capital distributions, date t


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It implies that since clean surplus relation means that there is a connection between equity (balance

sheet) and earnings (the statement of profit and loss), all changes in equity can affect earnings. In

this case, it can be logical to recognize all changes in equity in the statement of profit and loss. With

reason that earnings are equal to change in equity reduced by a factor of dividends (net of capital

distributions) it can be rational to separate changes in equity that comes from transactions with

owners (dividends). This principle of aggregation of changes in equity is obviously applied to the

model of comprehensive income reporting in revised IAS 1.

In addition, Lönnqvist (2011) verifies that since clean surplus relation proposes connection between

balance sheet and a statement of profit and loss, on one hand, there is a connection between assets

and liabilities between incomes and expenses. Lönnqvist (2011) explains net asset as a difference

between a firm’s assets and liabilities that is equity in the balance sheet. When following clean

surplus relation, if there is an increase in net asset that does not arise from new shares issue it

should be recognized as income in a statement of profit and loss. If there is a decrease in the net

asset that does not arise from dividends or when company purchases its own stocks, it should be

recognized as an expense in a statement of profit and loss. It can be assumed that this way of

thinking can be applicable to the revised IAS 1 since it requires recognizing of all changes in equity

not arising from transactions with owners in the statement of comprehensive income.

2.2 Previous research

Relevance and value relevance of the information in the financial statements is often understood

differently. Various user groups of the financial statements can often have different ideas about

what information is relevant (Holthausen and Watts, 2001, pp. 25-26). The IASB's Conceptual

Framework (2011, p. 9) lists various user groups of the financial statements of a listed company and

their different information needs. IASB mean that since investors supply equity capital to the

company, information is of interest to them (IASB's Conceptual Framework, 2011, p. 10). To

enable investors to decide whether to sell, hold or buy shares in the company, the investors need

relevant information. However, opinions about relevant information may vary between different

groups of investors (Holthausen and Watts, 2001, pp. 26-27).


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In view of capital market research, investors are the primary users of financial statements. Capital

market research area supposes that the primary aim of the financial statements is to provide a basis

for valuation of the companies. It is an extensive research area which origin can be traced back to

Ball and Brown (1968) empirical study where they examined the usefulness of income data that

existed in the company's accounting (Ball and Brown, 1968, p. 176; Kothari, 2001, p. 106). The

study of Ball and Brown (1968) is often associated with the term of value relevance that usually

means that stock prices have statistically connection to accounting information. This association

indicates that the tested part of the accounting information relates to the information used by

investors when they make their investment decisions (Francis and Schipper, 1999, p. 326). An

assumption can be made that since the most of research on value relevance of comprehensive

income used different methods of statistical association between income and some market

information (stock prices, stock returns), this research can be understood as capital market research.

As capital market research suggests that financial statements provide investors with information for

companies’ valuation, information about comprehensive income can be of interest to investors.

An extensive research on relevance of comprehensive income comparing to net income has been

done in different countries, especially with Anglo – Saxon accounting tradition. Countries with

Anglo – Saxon accounting tradition apply accounting standards those have been influenced by US

GAAP (Smith, 2006). Chambers, Linsmeier, Shakespeare, and Sougiannis (2007) and Choi, Das,

and Zang (2007) found that other comprehensive income is significant in the valuation of a

company. Choi et. al. (2007) provided evidence that the stock prices react on the inclusion of other

comprehensive income. Kubota, Suda and Takehara (2009) examined the information content of

comprehensive income, other comprehensive income and net income for Japanese firms. They

concluded that other comprehensive income is useful information although they could not rank

between net income and comprehensive income (Kubota et. al., 2009). Kanagaretnam et. al. (2009)

that were using data from Canadian companies, found that such components of other

comprehensive income as available-for-sale and cash flow hedges were considerably associated

with stock prices and stock returns.

By contrast, Dhaliwal et. al. (1999) justified that only such component of comprehensive income as

marketable securities adjustment was associated with stock returns. The researchers found no

evidence that comprehensive income is more strongly associated with stock returns and market

value of equity than net income. Pinto (2005) provides empirical evidence that reporting of such


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element of comprehensive income as foreign currency translation adjustments is significantly value

relevant. The researcher justifies disclosure of foreign currency translation adjustments when she

uses the sample of US multinational companies with considerable investments in foreign countries.

Moreover, some of behavioral studies investigated whether the way of presentation of

comprehensive income is relevant for investors. The study of Hirst and Hopkins (1998) revealed

that financial analysts could detect earnings management on some items only if this information

was disclosed in a statement of comprehensive income. Maines and McDaniel (2000) found that the

way of presentation of accounting information influenced evaluation of companies performance by

non - professional investors. The researchers showed that non - professional investors used rather

comprehensive income information in a separate statement of comprehensive income than the same

information disclosed as a component of equity. Schroeder et. al. (2001) argue that the results of

these studies have shown that the way of comprehensive income reporting can affect investors’

decision making.

Not much research has been conducted in Sweden. Roberts & Wang (2009) examined how

differences in institutional factors, in different European countries, including Sweden, affect the

value relevance of total hypothetical comprehensive income. The researchers added components

from statement of equity to net income and then linked the total income with stock returns. Roberts

& Wang (2009) justified that comprehensive income was significant in explaining stock returns.

Roberts & Wang (2009) found that total comprehensive income was incrementally relevant in

Sweden where equity market plays a crucial role in financing of the companies. However, Roberts

& Wang (2009) conducted their study on total comprehensive income. However, the study did not

test value relevance of components of other comprehensive income. The reason of lack of research

on the relevance of components of other comprehensive income on data from the Swedish

companies can be explained by newly revision of IAS 1.

Practitioners, standard-setters and academics appear to consider other comprehensive income

economically significant (Roberts & Wang, 2009). Reporting of other comprehensive income

components corresponds to require from users of financial statements for more visible and useful

presentation (Van Cauwenberge, 2007). New accounting information has been included in the

corporate income number, although, there is no study on the usefulness of this information for the

users in Sweden. Study on the value relevance of other comprehensive income based on data from


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Swedish companies might be needed. Value relevance of accounting information can be tested by

the method when stock price relate to book value of equity, earnings and other relevant information

(Ohlson, 1995). To evaluate whether inclusion of other comprehensive income was useful for the

users in Sweden, study of association between stock prices and book value of equity, as well as

earnings, might be useful.


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3. Method

3.1 Data collection and sample

In this section, we describe what companies we have selected to investigate and what information

we have collected for these companies. We begin with the selection of companies to investigate.

Since 2005, all companies that are listed on the stock market within the European Union are obliged

to prepare their consolidated financial statements in accordance with IASB's standards1 (FAR,

2011, pp. 3 and 29-32). In Sweden, there are three securities exchanges and four multilateral trading

facilities that are authorized by the Swedish Financial Supervisory Authority (Finansinspektionen,

2012). In these stock exchanges, there are a total of 516 listed companies2, of which 245 companies

are listed on NASDAQ OMX Stockholm (also known as Stockholm Stock Exchange or

Stockholmsbörsen). We have chosen to limit selection to the companies that are listed on the

Stockholm Stock Exchange. The reason for this limitation is that the companies listed on the other

stock exchanges are usually smaller companies with low trading volumes.

The companies on the Stockholm Stock Exchange are divided into three size segments. The size

segments are Small Cap, Mid Cap and Large Cap. Large Cap contains companies which have a

market value of over 1 billion Euros. The Mid Cap segment includes companies, which have a

market value between 150 million and 1 billion Euros. Companies with a market value of less than

150 million Euros are contained in the Small Cap segment. Of the 245 companies listed on the

Stockholm Stock Exchange, 111 companies belong to the Small Cap segment, 76 companies to the

Mid Cap segment, and 58 companies belong to the Large Cap segment (NASDAQ OMX

Stockholm, 2012:1). The sample includes companies that belong to Large and Mid Cap since it is

more likely that these companies have a wide range of other comprehensive income components.

The initial sample includes 134 companies. We look at the market information about the companies

three months after the fiscal year end (in the end of March). Therefore, we have excluded

companies which fiscal year is dissimilar to the calendar year because they publish their annual

reports in different periods. Following Kanagaretnam et. al. (2009) who showed results only for

1 Such as The commission of the European Communities has adopted these standards (FAR, 2011, pp. 3 and 29-32). 2 The three securities exchanges are NASDAQ OMX Stockholm (245 listed companies, see http://www.nasdaqomxnordic.com/), Nordic Growth Market (16 listed companies, see http://www.ngm.se/) and Burgundy (0 listed companies, see http://www.burgundy.se/) and the four multilateral

trading facilities are NASDAQ OMX Stockholm First North (112 listed companies, see http://www.nasdaqomxnordic.com/firstnorth/), Nordic

Growth Market (18 listed companies, see http://www.ngm.se/), AktieTorget (125 listed companies, see http://www.aktietorget.se/) and Burgundy (0 listed companies, see http://www. burgundy.se/). The information from the market places was retrieved March 10, 2012.


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non-financial firms we excluded financial and real estate companies. We excluded also firm-year

observations when all components of other comprehensive income were zero.

According to the rules of Stockholm Stock Exchange, the companies' financial reports shall be

available at the company's website for at least five years after publication (NASDAQ OMX

Stockholm, 2012:2, p. 3.1.6). We collected data accounting information from the companies’ annual

reports that covers period 2009-2011. We started from the year 2009 because the companies

reported in accordance with IFRS have to present comprehensive income since January, 1st 2009.

To collect accounting data for the fiscal year 2011, we used both annual and year-end reports

because some companies had not published their annual reports yet. The year-end reports are not

audited but to ensure the reliability of the data we have compared information included in annual

and year-end reports for previous years. We confirmed that information was identical. Finally, we

have ended in 246 firm-year observations.

We manually collected information about net income, components of other comprehensive income

and book value of equity from the annual and year-end reports. Most of the information was in

Swedish Crowns, but some information was in US dollars or Euros. When firms disclosed financial

information in foreign currency we converted it to Swedish Crowns using the average exchange

rate. To ensure that the market had the information from the annual reports or year-end reports, we

used the share price and number of shares outstanding 3 months after the fiscal year end. From the

corporate press releases we got to know that the most of the companies publish their annual reports

and all companies publish their year-end reports to the end of March. We used the database

Datastream to collect information about the market value and number of shares outstanding. The

information was brought together in a spreadsheet in Excel.

Before we ran the multiple regression analysis, we removed observations that were regarded as

outliers. However, before the exclusion of the outliers we investigated whether these extreme values

those were detected as outliers were wrongly recorded under the data collection process. Pallant

(2010, p. 43) describes outliers as scores that are much below or well above other scores. If outliers

are left in the sample, they can significantly bias the results of a regression analysis (Moore, 2001).

Pallant (2010, p. 159) explains that outliers can be detected using different methods. We followed

recommendations provided by Pallant (2010, p. 159) and excluded outliers that had Mahalanobis

distances above the critical value. For the regression model 1, we have excluded outliers that had


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Mahalanobis distances above 18,47 since this regression model contains 4 independent variables.

Before the regression analysis according model 2, we excluded outliers those had Mahalanobis

distances above 20,52 because this model includes 5 independent variables. Furthermore, we

excluded outliers that had standardized residuals that were higher than 3,3 or less than –3,3. Totally,

before regression analysis according model 1 we excluded 28 outliers 1 and 30 outliers before the

regression according model 2. In general, these outliers could be interpreted as observations with

extremely high and extremely low values of net income, book value, etc. These outliers included,

for example, such companies as AstraZeneca, Stora Enso and Lundin Mining Corporation SDB, etc.

In other words, for the companies those were identified as outliers there were large variations

between net income, other comprehensive income components and other values.

3.2 Research design

Value relevance of accounting information can be proved by statistical study of relationship

between book value of equity and earnings as well as other relevant information to the stock prices

(Ohlson, 1995). To test value relevance of comprehensive income, researchers commonly use

statistical studies applying regression analysis (Kanagaretnam et. al., 2009; Pronobis and Zülch,

2011; Roberts and Wang, 2009). Multiple regression analysis allows to explore the relationship

between one continuous dependent measure and a number of independent variables (Pallant, 2010).

Research on value relevance of comprehensive income often follows the well-known theoretical

model developed by Ohlson (1995) that explains investor’s value of a firm as a function of a firm’s

book value and residual earnings (Kanagaretnam et. al., 2009).

Since we aim to clarify if stock prices reflect the information recognized in components of other

comprehensive income, research design follows the statistical study conducted by Kanagaretnam et.

al. (2009). Kanagaretnam et. al. (2009) among other things investigated components of other

comprehensive income as explanatory variables for stock prices. The models that are used in this

part of the paper were developed by Kanagaretnam et. al. (2009, pp. 355-356). The regression

models that the researchers developed are based on the valuation function of Ohlson (1995).

Model 1:

PRICE = b0 + b1 BVE_S + b2 NI_S + b3 HEDGE_S + b4 SEC_S + b5 FOREX_S+ έ


Jörgen Ekström

17

Where:

PRICE = price per share 3 months after the end of fiscal year;

BVE_S = book value of common equity at the end of the year deflated by the number of

outstanding shares;

NI_S = annual net income after extraordinary items and discontinued operations deflated by the

number of outstanding shares;

HEDGE_S = the change of the fair value of cash flow hedges for a year deflated by the number of

outstanding shares;

SEC_S = the change in fair value of available-for-sale financial instruments for a year deflated by

the number of outstanding shares;

FOREX_S = the change of accumulated foreign currency translation adjustment for a year deflated

by the number of outstanding shares;

έ = error term

Use of such variable as book value of common equity is ambiguous, and; therefore, we exchange it

for book value of equity similar to Ohlson (1995) and Graham, Lefanowicz, and Petrony (2003).

Furthermore, we replace net income after extraordinary items and discontinued operations reported

according to Canadian GAAP by net income before tax. It should be also noted that we have tried to

do multiple regression using extended model 1 of Kanagaretnam et. al. (2009) and add the variable

of actuarial gains and losses. However, this regression analysis indicated high multicollinearity;

therefore, we have decided to modify this equation to ensure the reliability of regression results.

Under the annual report study, we have found only 42 observations of such variable as the change

in fair value of available-for-sale financial instruments. The number of observations is much less

compared, for example, with such components of other comprehensive income as the change of the

fair value of cash flow hedges and the change of accumulated foreign currency translation

adjustment. Therefore, we conduct a bivariate regression between share price and changes in fair

value of available-for-sale financial instruments to identify whether it can be used as explanatory

variable for the share price.

Regression equation is:


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18

PRICE = b0 + b1 SEC_S + έ

Table 3.1 presents the results of regression between share price and the change in fair value of

available-for-sale financial instruments.

Variables Unstandardized Standardized t Sig.

Coefficients Coefficients

B Std. Error

Constant 125,366 16,563 7,569 0,000

SEC_S -9,928 44,808 -0,035 -0,222 0,826

Table 3.1 Regression between share price and the change of fair value of available-for-sale financial instruments.

Pallant (2010, p. 161) says that standardized coefficients play an important role when comparing the

variables. However, analysis of unstandardized coefficients is used when one tries to build a

regression equation. Since we aim to compare variables not to build a regression equation, we use

analysis of standardized regression coefficients in the study. According regression a standardized

coefficient on the change of available-for-sale financial instruments was negative (-0,035) and not

statistically significant. Significance means p-value that is also called as the significance level

(Moore, 2001, p. 442). In the statistical sense “significant” does not suggest “important”. It actually

means that something does not likely to happen by chance (Moore, 2001, p. 443).

Freedman (2009, p. 70) recommends that if p is less than 0,1 (10%) one can say that the coefficient

is statistically significant at 10% level, or barely significant. If p is less than 0,5 (5%) coefficient is

statistically significant at 5% level, or statistically significant. If p is less than 0,01 (1%), then

coefficient is statistically significant at 1% level, or highly significant (Freedman, 2009, p. 70).

Since the variable does not have statistical significance it can be interpreted as if the variable is not

making a statistically significant contribution to the equation (Pallant, 2010, p. 161). The variable of

the change in fair value of available-for-sale financial instruments (SEC_S) is not statistically

significant and, hence, we excluded it from the regression model 1.

We wanted to extend the regression model developed by Kanagaretnam et. al. (2009); therefore, we

collected data about the companies’ actuarial gains and losses. However, we have only 48

observations. Therefore, we make a regression between share price and actuarial gains and losses to

find out whether this variable can contribute to the regression model.


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19

Regression equation is:

PRICE = b0 + b1 AGL_S + έ

Where:

AGL_S = actuarial gains and losses for a year deflated by the number of outstanding shares

Table 3.2 presents the results of regression between share price and actuarial gains and losses.



B Std. Error

Constant 115,807 16,505 7,017 0,000

AGL_S -13,379 9,596 -0,201 -1,394 0,170

Table 3.2 Regression between share price and actuarial gains and losses.

The coefficient on actuarial gains and losses is negative (-0,201) and is not statistically significant.

Since this variable is not making a unique statistical contribution to the equation, it was not

included in the model. We found extremely few observations (less than 10) for both changes in

revaluation amount of property, plant and equipment (IAS 16) and changes in fair value of

intangible assets (IAS 38), consequently these components of other comprehensive income could

not be used as variables. This can be also interpreted as such components of other comprehensive

income as change of the fair value of cash flow hedges, and the change of accumulated foreign

currency translation adjustment are the most common for the largest and medium-sized Swedish

companies.

Consequently, the regression model 1 becomes:

PRICE = b0 + b1 BVE_S+ b2 NI_S + b3 HEDGE_S + b4 FOREX_S + έ

Where:


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20

PRICE = price per share 3 months after the end of fiscal year;

BVE_S = book value of equity at the end of the year deflated by the number of outstanding shares;

NI_S = net income before tax for the fiscal year deflated by the number of outstanding shares;

HEDGE_S = the change of fair value of cash flow hedges for a fiscal year deflated by the number

of outstanding shares;

FOREX_S = the change of accumulated foreign currency translation adjustment for a year deflated

by the number of outstanding shares;

έ = error term

Then Kanagaretnam et. al. (2009) added an indicator variable GAIN to their basic regression model

to investigate how the market reacts to positive cash flow hedge numbers. GAIN is equal 1 if a

company has profit in cash flow hedging and is equal 0 if a company has a loss in cash flow

hedging. Then they introduced an interaction variable HEDGE_GAIN_S that is equal to

GAIN*HEDGE_S (Kanagaretnam et. al., 2009, p. 356). Kanagaretnam et. al. (2009, p. 356)

developed regression model 2 that is:

PRICE = b0 + b1 BVE_S + b2 NI_S + b3 HEDGE_S + b4 SEC_S + b5 FOREX_S + b6 GAIN + b7

HEDGE_GAIN_S + έ

The basic regression model 2:

PRICE = b0 + b1 BVE_S + b2 NI_S + b3 HEDGE_S + b4 FOREX_S + b5 GAIN + b6

HEDGE_GAIN_S + έ

We have tried to do regression analysis using this model; however, Pearson’s correlation between

HEDGE_S and HEDGE_GAIN_S was 0,966. According to Pallant (2010, p. 151), a correlation

that is equal to 0,9 or above can be a sign of multicollinearity. We also had a VIF value of

HEDGE_S that was equal to 27,063 and a VIF value of HEDGE_GAIN_S that was equal to

24,349. Pallant (2010) mentions that a VIF value above 10 also is a sign of multicollinearity.

Phenomenon of multicollinearity can occur when explanatory variables move too closely together

that can make evaluation of their individual effects on dependent variable difficult or even

impossible (Murray, 2006, p. 321). Furthermore, when one independent variable is a combination of


Jörgen Ekström

21

other independent variables, singularity can occur (Pallant, 2010, p. 151). In this model, the variable

HEDGE_GAIN_S is a combination of other two independent variables such as HEDGE_S and

GAIN. Pallant (2010, p. 151) says that before the regression analysis one should check for both

multicollinearity and singularity because these phenomena unquestionably do not contribute to an

appropriate regression model. Consequently, we have excluded variable HEDGE_S from the model

2 to avoid the possibility of multicollinearity or singularity.

Finally, the regression model 2 becomes:

PRICE = b0 + b1 BVE_S + b2 NI_S + b3 FOREX_S + b4 GAIN + b5 HEDGE_GAIN_S + έ


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22

4. Empirical analysis

4.1 Regression model 1

Table 4.1 below presents descriptive statistics for the variables that we used in the study of

association between share price and components of other comprehensive income.

Variables Mean Std. N

Deviation

PRICE 108,6242 77,21914 218

NI_S 8,9943 11,36289 218

BVE_S 44,0012 45,26798 218

FOREX_S - 0,6432 3,82860 206

HEDGE_S 0,2506 1,01754 131

Table 4.1 Descriptive statistics for the variables. Variables: PRICE = price per share 3 months after the end of fiscal

year; NI_S = annual net income before tax deflated by the number of outstanding shares; BVE_S = book value of

equity at the end of the year deflated by the number of outstanding shares; FOREX_S = the change of accumulated

foreign currency translation adjustment for a year deflated by the number of outstanding shares; HEDGE_S = the

change of the fair value of cash flow hedges for a year deflated by the number of outstanding shares.

All variables are deflated by the number of shares outstanding. According to table 4.1 the mean of

net income is equal 8,9943, which signals that the majority of non-financial companies in Large and

Mid Cap were profitable over the period 2009-2011. Most of the companies have negative value of

such component of other comprehensive income as change of accumulated foreign currency

translation adjustment. This component of other comprehensive income mainly includes changes in

fair values of assets and liabilities in foreign subsidiaries (Lönnqvist, 2011). This detail that most of

the companies have negative value of change of accumulated foreign currency translation

adjustment under 2009-2010 can be probably understood in the light of this fact that Swedish

Crown was weak under 2009 and became stronger under 2010-2011. However, the majority of the

firms have positive change of such component as change of the fair value of cash flow hedges. This

can be eventually understood in this way that the largest and the medium-sized Swedish companies

listed on NASDAQ OMX Stockholm successfully used such risk management procedures as

financial hedging under 2009-2011.


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23

Then to determine the strength of relationship between the variables we define coefficients on

Pearson correlation for pairs of variables that are presented in table 4.2.

Variables PRICE NI_S BVE_S FOREX_S HEDGE_S

PRICE 1,000 0,773 0,529 -0,077 -0,132

NI_S 0,773 1,000 0,815 -0,121 -0,258

BVE_S 0,529 0,815 1,000 -0,018 -0,164

FOREX_S -0,077 -0,121 -0,018 1,000 -0,351

HEDGE_S -0,132 -0,258 -0,164 -0,351 1,000

PRICE . 0,000 0,000 0,136 0,066

NI_S 0,000 . 0,000 0,042 0,001

BVE_S 0,000 0,000 . 0,397 0,031

FOREX_S 0,136 0,042 0,397 . 0,000

HEDGE_S 0,066 0,001 0,031 0,000 .

Pea

rso

n

Co

rrel

atio

nS

ig. (

1-t

aile

d)

Table 4.2 The strength of relationship between the variables.

Pallant (2010, p. 134) describes that tree levels of strength when speaking about a correlation

between variables. Correlation is small if the correlation coefficient is between 0,10 and 0,29.

Correlation is medium if the correlation coefficient is between 0,30 and 0,49. Correlation is large if

the correlation coefficient is between 0,50 and 1,0. Net income is highly correlated to the share

price (0,773). Furthermore, this correlation coefficient is statistically significant at 1% level.

Change of accumulated foreign currency translation adjustment (FOREX_S) has small negative

correlation to the share price. However, the correlation coefficient is not statistically significant.

Change of the fair value of cash flow hedges (HEDGE_S) has small negative correlation to the

share price (-0,132) thus it is higher than the correlation between share price and change of

accumulated foreign currency translation adjustment. It is essential to emphasize that the correlation

coefficient between share price and change of the fair value of cash flow hedges is statistically

significant at 10% level. Totally, any of variables have a correlation coefficient that is equal or

higher than 0,9 that could be a sign of multicollinearity.

To verify that results of regression are not biased by multicollinearity that probably not evident

from the correlation table, we do collinearity test (Pallant, 2010, p. 158). This test allows identifying

such values as tolerance and variance inflation factor (VIF) those can also indicate multicollinearity.

Tolerance is a factor that shows the extent of variability of the particular independent variable that

is not explained by the other independent variables. VIF is calculated as 1 divided by tolerance.

Multicollinearity occurs when tolerance is less than 0,10 and VIF above 10. According to the test of


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24

collinearity, values of tolerance are between 0,29 and 0,80 that is higher than 0,10. The values of

VIF are between 1,25 and 3,41 that is lower than 10. Both tolerance and VIF values were not

interpreted as problematic. The maximum of Mahalanobis distance is 13,537, which does not

suggest any problems for a regression model with 4 independent variables (Pallant, 2010, p. 159).

The maximum of Cook’s distance is 0,119, which is less than one and are thus not considered to be

a problem (Pallant, 2010, p. 160). The results of the regression, according to the first regression

model, are presented in table 4.3.



B Std. Error

Constant 66,090 6,180 10,690 0,000

NI_S 7,440 0,690 1,100 10,780 0,000

BVE_S -0,580 0,170 -0,340 -3,520 0,000

FOREX_S 1,890 1,240 0,090 1,520 0,130

HEDGE_S 9,680 4,770 0,130 2,030 0,050

Table 4.3 The result of regression, according to the first regression model.

Net income (NI_S) has a positive coefficient that is equal to 1,10 and also significant at 1% level.

The change of the fair value of cash flow hedges (HEDGE_S) has also a positive coefficient (0,13)

which is statistically significant at 5% level. Change of accumulated foreign currency translation

adjustment (FOREX_S) has also a positive coefficient, but not statistically significant. Table 4.4

presents a summary of the first regression model.

Model R R Square Adjusted Std. Error of

R Square the Estimate

1 0,801 0,642 0,630 46,97706

Table 4.4 Summary of model 1.

R Square indicates how much of the variance in the dependent variable is explained by the

regression model (Pallant, 2010). R Square is 0,642 which means that the regression model 1

explains 64,2 % of the variance of dependent variable (share price). Pallant (2010, p. 160) mentions

that R Square that is equal 46,8 % can be understood as a quite respectable result. Therefore, R

Square that is equal 64,2% can be interpreted as quite high. Another factor that is used to value

regression model is Adjusted R Square (Pallant, 2010). According to the results, Adjusted R Square


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25

for the regression model 1 is 63 % that is comparable to the results of Kanagaretnam et. al. (2009)

who provide Adjusted R Square equal 68 %. Furthermore, the regression model 1 reaches statistical

significance that could be seen in the table 4.5.

Model Sum of

Squares

df Mean

Square

F Sig.

1 Regression 467053,5 4 116763,4 52,91 ,000b

Residual 260407,6 118 2206,844

Total 727461,1 122

Table 4.5 ANOVAa

All these indicators as high R Square and Adjusted R Square, as well as, statistically significance of

the regression model 1 could be interpreted as regression model 1 has a good explanatory ability for

the share price and statistically valid.

4.2 Regression model 2

The results of Pearson correlation of the pairs of variables that are included in the second regression

model are presented in table 4.6.

Variables PRICE NI_S BVE_S FOREX_S GAIN HEDGE_

GAIN_S

PRICE 1,000 0,777 0,535 -0,084 -0,177 -0,096

NI_S 0,777 1,000 0,817 -0,120 -0,212 -0,189

BVE_S 0,535 0,817 1,000 -0,015 -0,232 -0,022

FOREX_S -0,084 -0,120 -0,015 1,000 -0,288 -0,311

GAIN -0,177 -0,212 -0,232 -0,288 1,000 0,563

HEDGE_GAIN_S -0,096 -0,189 -0,022 -0,311 0,563 1,000

PRICE . 0,000 0,000 0,117 0,022 0,139

NI_S 0,000 . 0,000 0,043 0,008 0,016

BVE_S 0,000 0,000 . 0,416 0,004 0,404

FOREX_S 0,117 0,043 0,416 . 0,001 0,000

GAIN 0,022 0,008 0,004 0,001 . 0,000

HEDGE_GAIN_S 0,139 0,016 0,404 0,000 0,000 .

Sig

. (1

-tai

led

)P

ears

on

Co

rrel

atio

n

Table 4.6 The strength of relationship between the variables.


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26

As expected, any correlation coefficients are higher than 0,9 suggesting no problems with

multicollinearity. Added variables have small negative correlation to the share price. GAIN has a

negative correlation coefficient (-0,177) that is statistically significant at 5% level.

HEDGE_GAIN_S has also negative correlation coefficient (-0,096) that is not statistically

significant.

The collinearity test confirms that there is no concern about multicollinearity because VIF values

are between 1,240 and 3,712. The VIF values are below 10 that is considered as unproblematic. The

values of tolerance are between 0,269 and 0,806 which are above 0,1 suggesting no problems with

multicollinearity. The maximum of Mahalanobis distance is 18,776, and the maximum of Cook’s

distance is 0,085 suggesting no serious problems. The results of the regression, according to the

second regression model, are presented in table 4.7.



B Std. Error

Constant 72,479 8,386 8,642 0,000

NI_S 7,769 0,712 1,145 10,908 0,000

BVE_S -0,726 0,177 -0,425 -4,096 0,000

FOREX_S 1,551 1,244 0,076 1,247 0,215

GAIN -19,832 10,890 -0,127 -1,821 0,071

HEDGE_GAIN_S 28,923 10,274 0,207 2,815 0,006

Table 4.7 The result of regression, according to the second regression model.

Net income (NI_S) has a positive coefficient (1,145) that is statistically significant at 1% level.

Change of accumulated foreign currency translation adjustment (FOREX_S) has also a positive

coefficient (0,076) that is not statistically significant. The indicator variable (GAIN) has a negative

coefficient (-0,127) that is statistically significant at 10% level. The interaction variable

(HEDGE_GAIN_S) has a positive coefficient (0,207) that is statistically significant at 1% level.

Table 4.8 presents a summary of the second regression model.

Model R R Square Adjusted Std. Error of

R Square the Estimate

2 0,811 0,658 0,644 46,50260

Table 4.8 Summary of model 2.


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27

Similar to the regression model 1 regression model 2 reaches statistically significance that could be

seen in table 4.9.

Model Sum of

Squares

df Mean

Square

F Sig.

2

Regression 479441,977 5 95888,395 44,342 ,000b

Residual 248686,780 115 2162,494

Total 728128,757 120

Table 4.9 ANOVAa

The regression model 2 explains 65,8% of the variance of the dependent variable (share price) since

R Square is equal 0,658. R Square of the model 2 is higher than R Square of the model 1 that is

equal to 64,2%. R Square for the both models can be interpreted as high which means that the

regression models 1 and 2 have high explanatory power for the share price and statistically valid.

According to our results, Adjusted R Square for model 1 is 63 %, but lower than Kanagaretnam et.

al. (2009) who got adjusted R Square for model 1 equal to 68 %. It is the same for model 2, when

the adjusted R Square is 64,4 % and Kanagaretnam et. al. (2009) provide 69,02 %. It implies that

our results regarding adjusted R Square are comparable to the results of Kanagaretnam et. al.

(2009), but lower. We assume that Kanagaretnam et. al. (2009) used other statistical methods to

handle multicollinearity, however, the researchers do not mention anything about multicollinearity

in the article. In summary, the results indicate that the second regression model has higher

explanatory ability of stock price than the first regression model. Therefore, the inclusion of such

independent variable in the model as an indicator variable GAIN is statistically valid.

The coefficient on the net income (NI_S) is positive and significant for both models at 1% level

which is similar to the study of Kanagaretnam et. al. (2009). The results show that the change of

accumulated foreign currency translation adjustment (FOREX_S) has positive coefficients those are

not statistically significant for the both models. The results are similar to the results of the study of

Kanagaretnam et. al. (2009) since the change of accumulated foreign currency translation

adjustment (FOREX_S) was not statistically significant for the share price according to their results

either.


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28

According to the results, for the model 1 the change of the fair value of cash flow hedges

(HEDGE_S) has a positive coefficient which is statistically significant at 5% level. For the model 2,

indicator variable (GAIN) has a negative coefficient that is statistically significant at 10% level. The

interaction variable (HEDGE_GAIN_S) has a positive coefficient that is statistically significant at

1% level. The study of Kanagaretnam et. al. (2009) found that the coefficient on the change of the

fair value of cash flow hedges (HEDGE_S) was negative and statistically significant at 1% level for

both model 1 and model 2. We have excluded HEDGE_S from the model 2. Thus, the coefficients

on both change of the fair value of cash flow hedges (HEDGE_S) and the interaction variable

(HEDGE_GAIN_S) are positive that can be interpreted a providential sign (Kanagaretnam et. al.,

2009). Kanagaretnam et. al. (2009) had a positive coefficient on the interaction variable

(HEDGE_GAIN_S), but it was statistically significant at 10% level that they did not consider as

strong statistical evidence. In summary, the coefficients on such variables as the change of the fair

value of cash flow hedges (HEDGE_S) and the interaction variable (HEDGE_GAIN_S) are lower

than the study of Kanagaretnam et. al. (2009) found, but statistically significant.

Kanagaretnam et. al. (2009) found that change in fair value of available-for-sale financial

instruments was positive and significant at 1% level for the both models. The researchers concluded

that available-for-sale components of other comprehensive income were significantly associated

with the share price. However, we have modified their model by excluding the variable of change in

fair value of available-for-sale financial instruments. We excluded this variable from the both

models since the variable did not have explanatory power on the dependent variable (share price)

according to the simple regression. Consequently, we got results on the Swedish data those are

comparable to the results of the study of Kanagaretnam et. al. (2009) that used Canadian data, but

different in some points.


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29

5. Discussion and conclusions

5.1 Discussion

One of the reasons why IASB imposed reporting on comprehensive income is to enhance the

usefulness and relevance of financial statements. In this study, we investigate the value relevance of

the components of other comprehensive income. We have found some evidence that the change of

the fair value of cash flow hedges is statistically associated with the share price. Particularly, we

found some evidence that winning cash flow hedging position is significantly associated with the

share price. However, both total change of the fair value of cash flow hedges and its winning

position have small association with the share price.

The results can be also interpreted in this way that the change of the fair value of cash flow hedges

has some value relevance. In particular, positive change of the fair value of cash flow hedges is

more value relevant. According to the results, reporting of such component of other comprehensive

income as the change of the fair value of cash flow hedges can be understood as useful for investors

and capital market. However, we did not find that available-for-sale component of other

comprehensive income or other components of other comprehensive income were associated with

the share price.

According to the results, reporting of such component of other comprehensive income as the change

of the fair value of cash flow hedges can be understood as useful for investors and capital market.

The study of DeMarzo and Duffie (1995) found that financial hedging or corporate risk

management improves information effect of the corporate earnings. In addition, financial hedging

signals to the shareholders about the ability of management to provide financial risk management.

The study has revealed that, when accounting information about financial hedging is available for

the investors, it eliminates noise among the outside investors. Hence, it can be understood as the

results of the study confirms that reporting on accounting information about financial hedging in the

income statement can be of interest to outside investors both professional and non – professional. In

other words, it can be useful for investors to look at the company’s income statement and such

component of comprehensive income as change of the fair value of cash flow hedges. It is

especially crucial to pay attention whether the change of the fair value of cash flow hedges is a


Jörgen Ekström

30

positive number. This can signal to the investors about successful corporate risk management that

can be interpreted as positive information about the company. Moreover, the results possibly could

be valuable for scholars working in the same field of research.

In addition, when collecting data for the study we found extremely few observations of fair value

changes of intangible assets (IAS 38), fair value changes of property, plant and equipment items

(IAS 16). This may be understood in this way that companies listed at Large and Mid Cap of

NASDAQ OMX Stockholm do not normally use revaluation model to measure intangible assets

and assets related to property, plant and equipment. These companies probably prefer cost model of

measurement for those assets. The results may be interpreted to be in line with the prior researches.

Sundgren et. al. (2007) report that empirical evidence on the use of revaluation model of

measurement according to IAS 16 in Sweden is limited. However, there is some international

evidence justifying that companies prefer cost method of recognition for the assets of property,

plant and equipment (Sundgren et. al., 2007). Sundgren et. al (2007) verify that the absence of an

active market because of uniqueness of intangible assets might be a reason of limited use of

revaluation model for measurement of intangible assets in Sweden. Hence, the results on the lack of

use of revaluation models under IAS 16 and IAS 38 might be relevant for the standard-setter.

Value relevance tests are tests of both relevance and reliability. Reporting of unrealized gains and

losses in other comprehensive income can probably enhance the relevance of the financial

information at the possible expense of reliability (Kanagaretnam et. al., 2009, p. 364). However,

investors should bear in mind that information included in components of other comprehensive

income arises from some transitory changes of fair value of assets and liabilities. It is worth noting

that there are some studies which found that fair value accounting increases the volatility of

financial statements (Kabir and Lasward, 2011, p. 273). When looking at numbers in other

comprehensive income investors should be aware that these components may include changes in

fair values that come from not only market values of the assets and liabilities, but also from fair

value estimations when different financial accounting models were used. This information may

contain some subjective bias depending on honesty of the corporate management (Penman, 2007).


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31

5.2 Conclusions, limitations and further research

According to the results of the study, it can be argued that efforts of IASB appear not to be highly

effective since only one component of other comprehensive income has an association with the

share price and not much significance was found. However, the results may be because of the

limitations of the study. First, amendment of IAS 1 is new as it is in effect since January, 2009;

hence we used the data for the short period. Second, financial crisis might have caused the fact that

share prices were moving in the chaotic way. Therefore, similar study can be suggested to be

performed in the future using longer data streams.

In addition, the study has shown that companies generally do not use revaluation models those are

allowed by IAS 16 and IAS 38. Hence, further qualitative research may investigate how companies

choose a method of measurement according IAS 16 and IAS 38. This study focuses on the

companies those belong to Large and Mid Cap at Stockholm’s Stock Exchange. Hence, the sample

includes the largest and medium size companies that can potentially cause some size bias in the

results. Moreover, the results of this study are based on data from only Swedish companies and,

therefore, may not be applicable to the other countries. For this reason, future research possibly

could include a wider sample of companies those are listed in other countries those comply with

IFRS regulation. Furthermore, it would be interesting to investigate the relevance of components of

other comprehensive income using a qualitative method, for instance, conducting interviews with

both professional and non-professional investors, as well as producers of financial statements. Such

research is needed to add further explanations of the practical usefulness of other comprehensive

income.

Finally, this paper provides some insight into understanding the practical applicability of several

IFRS standards in Sweden. This paper also proposes some relevant implications for researchers and

practitioners in the field of accounting under IFRS. This paper throws new light on the effects of

implication of revised IAS 1 and reporting of other comprehensive income. This paper might help

investors in better understanding of practical use of the components of other comprehensive

income. Additionally, this paper may perhaps encourage the researchers working in the field of

accounting research to further investigation of usefulness of comprehensive income, especially

other comprehensive income. The evidence from this study can probably inspire the standard-setter

to further improvement of IFRS standards.


Jörgen Ekström

32

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