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HAS THE ADOPTION OF THE AUSTRALIAN INTERNATIONAL FINANCIAL REPORTING STANDARDS BEEN VALUE RELEVANT? Tony Becis Chew Ng* Eduardo Roca Griffith University (Working paper only. Please do not quote without permission from the authors) Key words: International accounting harmonisation, AIFRS, value relevance, post-earnings-announcement drift, and Markov Switching Analysis JEL classification: G14, M41 * Details of Corresponding Author:
Transcript
Page 1: 1. INTRODUCTION

HAS THE ADOPTION OF THE AUSTRALIAN INTERNATIONAL

FINANCIAL REPORTING STANDARDS BEEN VALUE RELEVANT?

Tony BecisChew Ng*

Eduardo RocaGriffith University

(Working paper only. Please do not quote without permission from the authors)

Key words: International accounting harmonisation, AIFRS, value relevance, post-earnings-announcement drift, and Markov Switching Analysis

JEL classification: G14, M41

* Details of Corresponding Author:Department of Accounting, Finance and EconomicsGriffith Business SchoolGriffith UniversityNathan CampusQLD 4111Tel: (07) 3735 6492 Fax: (07) 3735 7760

Page 2: 1. INTRODUCTION

HAS THE ADOPTION OF THE AUSTRALIAN INTERNATIONAL

FINANCIAL REPORTING STANDARDS BEEN VALUE RELEVANT?

Abstract

Australia adopted the international financial reporting standards in 2005 amidst

concerns as to its impact on Australian companies’ profits, balance sheets and share

prices. Only a few studies have attempted to investigate these concerns. One of those

is that of Becis, Ng and Roca (2006), which examined the impact of the Australian

International Financial Reporting Standards (AIFRS) on Australian company profits

and equity. In that study, they found that some companies were negatively affected

while others were positively impacted. Based on the same data that they used, we

extend their work by further investigating the effect of the AIFRS adoption on

company values. We perform the analysis based on a number of methods including

the recently developed and advanced econometric method that takes into account

market cycles – the Markov-regime switching model (Hamilton, 1990 and Krolzig,

1997). Despite the generally cash flow neutral impact of IFRS adoption, our results indicate

that for medium and small firms a positive relationship exists between the impact of AIFRS

on net profit after tax (NPAT) and market value. For large firms, this relationship is negative.

Our results provide evidence that the changes in accounting values arising from the

implementation of the IFRS are value relevant.

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1. INTRODUCTION

In the lead up to the adoption of Australian International Financial Reporting

Standards (AIFRS) in 2005 users of financial reports issued by firms listed on the

Australian Stock Exchange faced a decision regarding which set of accounting

standards they would place their trust in when making investment decisions. With the

inclusion of comparative AIFRS accounting information in financial reports for the

year ending 30 June 2005 investors had the choice of basing their estimation of firm

value upon accounting numbers prepared under alternative accounting regimes – the

pre-existing Australian Generally Accepted Accounting Principles (AGAAP) and the

soon to be implemented AIFRS standards.

Australian reporting entities required to prepare financial reports in

accordance with Part 2M.3 of the Corporations Act 2001 must apply AIFRS for

annual reporting periods commencing on or after 1 January 2005. Prior to this, firms

were required to disclose for the interim and annual reporting periods ending on or

after 30 June 2004, increasingly detailed information regarding their transition to

AIFRS and the impact that adopting the new AIFRS standards was likely to have on

their reported financial performance and financial position. These disclosures were

required by AASB 1047 “Disclosing the Impacts of Adopting Australian Equivalents

to International Financial Reporting Standards”. Accounting Standard AASB 1047

was issued in April 2004.

In complying with the AASB 1047 disclosure requirements in relation to

30 June 2005 annual financial reports, many firms included in their 30 June 2005

preliminary final reports tabular reconciliations of net profit after tax (NPAT) and

shareholders’ equity determined under AGAAP and AIFRS. These quantitative

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AIFRS reconciliations were amongst the first disclosures informing the market of the

likely quantitative impacts that the new accounting standards would have on the

financial reports of publicly listed Australian firms.

So, has the AIFRS been “value relevant”? In other words, has it impacted the

share prices of Australian companies? As noted, at the time of writing there were few

if any published studies investigating the value relevance of quantitative AIFRS

disclosures. The scarcity of research in this area is due to the relative recency of

quantitative AIFRS data. However, there have been a number of studies and surveys

conducted that investigate the impact of AIFRS on financial reports, company

earnings and shareholders’ equity.

One of the first studies in this area was performed by Jubb (2005) who

surveyed corporate AIFRS disclosures contained in annual and half-year reports for

periods ending 30 June 2004. The sample for the study was all ASX listed companies

as at 30 June 2004. Jubb’s study reveals that the main accounting changes introduced

by AIFRS relate to income tax, asset impairment, share-based payments, financial

instruments and intangibles. Jubb’s study did not focussed on quantitative

disclosures. Though in relation to such disclosures, Jubb (2005, p. 11) noted “only a

handful of companies used any quantification in their disclosures, although several

explicitly reported that there would be no material impacts”.

A study by accounting firm Ernst & Young (2005) considered the quantitative

and qualitative AIFRS disclosures contained in 30 June 2005 financial statements.

The population for the Ernst & Young study was the top 100 listed companies taken

from BRW’s 2005 Top 500 Public Companies list. The Ernst & Young study

reported that on average, firms disclosed that the transition to AIFRS was expected to

increase reported profit by 6% in the first AIFRS comparative year. Additionally,

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Ernst & Young reported that firms expected total equity to decrease “by 15% at the

date of transition to AIFRS and by 17% at the end of the first AIFRS comparative

year”. Ernst & Young also observed that the accounting policies most impacted by

AIFRS adjustments were share based payments, goodwill amortisation, income taxes

and defined benefit plans. These ‘most impacted’ accounting policies are consistent

with those identified by Jubb (2005).

In December 2004, accounting firm KPMG (2005) surveyed fifty buy-side and

sell-side financial analysts in Sydney and Melbourne to gain an insight into how

Australian capital markets were likely to react to financial reporting under AIFRS.

The survey was conducted approximately nine months prior to the release of the

initial quantitative AIFRS impact data by 30 June balancers in 30 June 2005

preliminary final reports. KPMG (2005, p. 2) reported that the analysts surveyed

appeared to have an “overall familiarity” with new standards but lacked a “deep

understanding of their complexities and nuances”. Forty-nine percent of analysts

surveyed expected AIFRS to have some impact on market prices, and 62% indicated

that they were likely to mark down a company’s shares if they did not understand why

the company’s results looked different under AIFRS.

Importantly, almost 40% of analysts surveyed believed that market prices at

the time of the survey had not yet factored in the financial report impacts of AIFRS.

Somewhat surprisingly, only 30% of analysts surveyed believed that AIFRS would

improve investment decision making. However, this somewhat unexpected response

is understandable given that none of the analysts surveyed felt “very confident” that

they could “distinguish between variations in a company’s reported results due to a

change in the underlying business performance and those directly resulting from the

move to AIFRS” (KPMG 2005, p. 4). Significantly, the KPMG (2005, p. 6) survey

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concluded “there is likely to be considerable confusion and market dislocation when

the first AIFRS-compliant financial reports begin entering the public domain”.

Utilising the AASB 1047 disclosures contained in the 30 June 2005

preliminary final reports of firms with a 30 June year-end, Becis, Ng and Roca (2006)

examined the impact of the adoption of the IFRS by Australia on the NPAT and

equity of Australian companies. Their analysis of the accounting data reveals that (1)

the majority of ASX 300 companies disclosed increased net profit under AIFRS

compared to AGAAP for the year ended 30 June 2005, and (2) the majority of ASX

300 companies disclosed decreased equity balances under AIFRS compared to

AGAAP as at 30 June 2004 and as at 30 June 2005.

The findings presented by the overseas literature regarding the value relevance

of alternative accounting standard disclosures are somewhat inconsistent. It has been

suggested that this inconsistency is due to the peculiarities of the various accounting

standards considered. Nonetheless, this literature provides a valuable context for the

issues considered and the tests performed in this study. Most of the overseas

literature considers the value relevance of earnings reconciliations between various

non-US domestic GAAP, IAS and US GAAP. Australian data is used in some of the

overseas literature (for example Rees 1995; Barth & Clinch 1996). However, none of

these studies focus exclusively on Australian alternative accounting standard

reconciliations.

In this paper, we extend the work of Becis, Ng and Roca (2006). Based on the

same sample data, we combine their results with share market data to determine

whether firm share market returns reacted at the time that AASB 1047 and subsequent

AIFRS disclosures were released to the market. Answering this question provides

insights regarding the value relevance of the AIFRS and AGAAP accounting

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standards. In addressing this question, this study performs five value relevance tests.

The first two tests are relatively short window event tests that compare the cumulative

average abnormal returns (CAAR) of firms that disclosed large increases to NPAT

under AIFRS (AIFRS winners) with the CAAR of firms that disclosed small increases

or decreases to NPAT under AIFRS (AIFRS losers). The third test examines the

correlation between changes to NPAT under AIFRS and cumulative abnormal returns

(CAR). The fourth test compares the long-term cumulative average returns (CAVR)

of AIFRS winners and losers during three distinct AIFRS disclosure periods within a

forty-four month window. The final test, also utilising a long window, employs

Markov Switching Analysis to objectively identify and compare the share-market

return characteristics of AIFRS winners and losers during three similar disclosure

periods.

The results of the short window event study show that despite the transition to

AIFRS broadly having no cash flow impact, in the 22 days following the AIFRS

reconciliation announcement for the year ending 30 June 2005, firms that reported

higher NPAT under AIFRS produced cumulative abnormal returns that were up to

two percent higher than returns for firms that disclosed lower NPAT under AIFRS.

The results of the long window event study suggest that the NPAT advantage enjoyed

by firms that generally report higher earnings under AGAAP than AIFRS gradually

eroded as those firms disclosed to the market their expected position under AIFRS.

2. IMPORTANCE AND CONTRIBUTIONS OF THE STUDY

There has been substantial discussion in the financial press regarding the

suspected market impacts arising from the adoption of AIFRS (for examples see:

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Page 8: 1. INTRODUCTION

Hogan 2005; Alderton 2006; Buffini 2006; CPA Australia 2006). Furthermore, in the

lead up to the adoption of AIFRS, the Financial Reporting Council (FRC) expecting

some kind of market reaction in response to the release of quantitative AIFRS

disclosures warned “for some companies, the impact on company reporting

requirements and potentially share prices as a result of the adoption of IASB

standards will be significant. There is a need to keep investors and users fully

informed” (FRC 2005, section i).1 Whilst there has been considerable speculation

regarding the market impacts of AIFRS adoption, there is currently little, if any,

empirical analysis available to support such arguments. This study aims to address

this deficiency and inform the debate by examining whether the market did in fact

react to AIFRS disclosures, and if so, to what degree.

Furthermore, from a capital markets perspective, the adoption of AIFRS may

be somewhat less warranted if it observed that the market did not react to financial

information presented in accordance with the new standards. That is, if the market

did not react to AIFRS disclosures, then it would be difficult to argue that the new

accounting standards provided the market with new or value relevant information

(Amir et al. 1993; Rees 1995). In this respect, this study considers whether

quantitative AIFRS disclosures are meaningful numbers to investors (Kothari 2001, p.

121).

The value relevance of accounting changes has been subject to debate in the

literature ever since the term “value relevance” was coined by Amir, et al (1993).

Venkatachalam (1999, p. 317) notes that studies investigating the value relevance of

amounts reported under different accounting standards are a “starting point for further

enquiries on the usefulness of such reconciling amounts”. This study provides a

1 The FRC is a body established under the Australian Securities and Investments Commission Act 2001 that is responsible in Australia for the broad oversight of the accounting standard setting process for private, public and not-for-profit sectors (FRC 2002).

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starting point for further Australian research into the value relevance of AIFRS

reconciliations in the same way that studies investigating the value relevance of Form

20-F reconciliations in the US provided a starting point for more direct tests of value

relevance involving the accuracy of analysts’ forecasts or the predictive ability of

earnings under alternative accounting standards.

The second contribution to the literature made by this study relates to the

determination of firm value in an Australian context. Capital market theory suggests

that firm value is equal to the present value of future cash flows. Applying this

premise suggests that the adoption of AIFRS, which is generally a cash flow neutral

change, should have little or no impact on investors’ pricing decisions. If AIFRS

disclosures are in fact associated with changes in firm value this study will provide

insights regarding the information considered by investors when pricing firms.

The third contribution that this study makes to the literature relates to market

efficiency. The efficient market hypothesis suggests that all value relevant

information is immediately incorporated into market prices. However, post

announcement drift is a characteristic exhibited by share prices when they are slow to

react to unexpected earnings or other value relevant information. Accepting that there

may be reasons for investors to reassess firm value in reaction to AIFRS disclosures

despite their cash flow neutrality, in an efficient market one would expect prices to

immediately incorporate the information contained AIFRS disclosures. In the event

that it is observed that market prices react to AIFRS disclosures, the results of this

dissertation will contribute to the literature by identifying the period of time over

which quantitative AIFRS disclosures are impounded into share market prices.

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Finally, this paper contributes to the literature by performing a Markov

Switching Analysis (Hamilton, 1989 and Krolzig, 1997) test utilising AIFRS

reconciliations and market data. This advanced methodology is a relatively recent

development in the time series econometrics literature that allows the analysis of the

relationships of the variables to vary according to regimes (or states) of the variables.

One of the major advantages of this approach is that it does not require prior

specifications or dating of returns’ regimes. Instead, regimes and their corresponding

probabilities of occurrence are endogenously determined rather than pre-determined.

Thus, the use of the Markov switching model allows us to perform a more robust and

informative analysis of the impact of the IFRS on share prices. This paper is likely

one of the first to utilise this methodology in relation to the analysis of AIFRS

reconciliation data.

The reconciliations from AGAAP to AIFRS, which form the basis of this

study, are an important source of information for investors. It is important to

understand whether these reconciliations are value relevant, and if they are value

relevant, it is important to understand how and why these reconciliations impact

market values despite their largely cash flow neutral nature.

3. METHODOLOGY

Five tests are conducted to determine the share return performance of AIFRS

winners and losers over the short-term, medium-term and long-term. Three event

studies are conducted (for examples, see Beaver 1968, Wilson 1986and Amir et al.

1993) – one for the short-term, another one for the medium term and another one for

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the long-term. In addition, a correlation test was also performed for the short-term,

and a Markov regime switching analysis for the long-term.

3.1 Short and Intermediate Window Tests

The short window test identifies the cumulative average abnormal returns

(CAAR) of AIFRS winners and losers using daily data for the twenty-two trading

days immediately following the release of 30 June 2005 preliminary final reports.

The intermediate window test observes the CAAR of AIFRS winners and losers for

the twenty-one weeks following the release of the 30 June 2005 preliminary final

reports. It is performed to supplement the findings of the short window test and to

gain an insight into the medium-term CAAR characteristics of AIFRS winners and

losers.

Another simple method for assessing whether quantitative AIFRS disclosures

are value relevant is to perform a correlation test. This study performs several

correlation tests to determine whether there is a relationship between changes to

NPAT under AIFRS and cumulative abnormal returns (CAR).2 The return window

for these tests span from the close of trading on the day before the event to the end of

the fifth trading day after the event.

Correlations are performed for the entire sample, and also for firms grouped

by sector and market capitalisation. These correlations are performed by using the

change in NPAT under AIFRS as a percentage of NPAT under AGAAP for the year

ending 30 June 2005.

2 Since the correlation tests involve individual firm observations, it is noted that cumulative average returns are used instead of cumulative average abnormal returns.

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For the year ending 30 June 2005, a scatter diagram was produced plotting

sample firm AIFRS NPAT reconciliations as a percentage of AGAAP NPAT against

sample firm CAR measured from day -1 to day 5, where day 0 is the preliminary final

report release date. A six day event window was selected for this test based on the

results in Table 6 which show that the difference in CAAR of AIFRS winners and

losers reaches a relatively stable plateau approximately six days after the 30 June

2005 preliminary final reports are released to the market. A six day window also

gives the market time to react to the ostensibly ‘new’ quantitative AIFRS information

contained in 30 June 2005 preliminary reports. Rees (1995) uses a four day event

window for a similar study of reconciliations to US GAAP.

3.2 Long Window Association Test – Association between AIFRS Winners and

Losers and Long Term Returns

A long-term event study is also conducted that compares the long-term

cumulative returns of AIFRS winners and losers.3 The window for this test spans

forty-four months. It begins on 1 July 2002 and ends on 28 February 2006. During

the window, AASB 1047 required firms to release increasingly detailed disclosures

regarding their adoption of AIFRS. The AIFRS disclosure requirements during this

window can be classified into three distinct periods: pre-disclosure; qualitative

disclosure; and quantitative disclosure.

3 This test does not adjust firm returns for market returns as the period of observation for all firms begins on the same date, being 1 July 2002.

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3.2.1 Pre-Disclosure

In the twenty-four months following the announcement of the move to AIFRS,

firms were not required by AGAAP to disclose information related to the expected or

actual impacts of the move. During this ‘pre-disclosure’ period investors were

unlikely to know with any meaningful degree of certainty whether a particular firm

would eventually be an AIFRS winner or an AIFRS loser. It is expected that changes

in firm returns during this period are not closely associated with whether firms

eventually become AIFRS winners or losers. The pre-disclosure period commenced

with the announcement to adopt AIFRS in July 2002 and ended during July 2004

when qualitative AIFRS disclosures were required by AASB 1047 to be included in

AGAAP financial reports.

3.2.2 Qualitative Disclosure

In financial reports for the year ended 30 June 2004 and the half-year ended

31 December 2004, AASB 1047 required firms to provide (1) an explanation of how

the transition to AIFRS was being managed and (2) a narrative explanation of the key

differences in accounting policies that were expected to arise from the adoption of

AIFRS (AASB 1047, 4.1). During this ‘qualitative disclosure’ period investors were

provided with qualitative information and an indication of the components of the

financial report that would be subject to quantitative changes. Based on these

qualitative disclosures, it is likely that analysts and sophisticated investors were able

to identify industries and firms that would eventually be AIFRS winners and AIFRS

losers. This period commenced during July 2004 and ended during July 2005.

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3.2.3 Quantitative Disclosure

In financial reports for the year ended 30 June 2005, AASB 1047 required

firms to disclose data regarding the expected qualitative and quantitative impacts of

the adoption of AIFRS. During this ‘quantitative disclosure’ period firms were

required to identify specific components of the financial report that were expected to

be impacted by the adoption of AIFRS and also the size of any impact. This is the

first disclosure period in which ordinary investors could distinguish AIFRS winners

from AIFRS losers. This period commenced during July 2005 and ended with the

release of the first half-year financial reports prepared under AIFRS during January

2006.

3.3 Markov Switching Analysis

The final test assesses the value relevance of qualitative and quantitative

AIFRS disclosures by comparing the systematic risk or return characteristics vis-à-vis

the market of firms across three discrete disclosure periods. This test uses Markov

Regime Switching Analysis (Hamilton, 1990, and Krolzig, 1997) to perform this

assessment. The Markov Switching Analysis objectively determines the probability

of each firm’s return behaviour being in one of three “states” (or in Markov Switching

Analysis terminology, “regimes”) in each of three disclosure periods. The duration of

each regime is also determined. It then calculates the systematic risk of each firm in

each regime or cycle (for a detailed discussion of the Markov Regime Switching

methodology, see Roca and Wong, forthcoming). The Markov Regime Switching

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approach therefore allows us to take into account market cycles. The periods used for

this test differ slightly from those used for the long window association test.

The window for this test spans 1 January 2000 to 28 February 2006. The three

periods used for this test are as follows. The first period called ‘pre-announcement’

precedes the announcement of the adoption of AIFRS. This period begins on 1

January 2000 and ends on 2 July 2002. The second period called ‘qualitative

disclosure’ spans the time from the announcement to adopt AIFRS until just before

the release of the first AIFRS quantitative impact data. This period begins 3 July

2002 and ends 31 July 2005. The third period called ‘quantitative disclosure’ spans

the time from the release of the first AIFRS quantitative impact data until the

commencement of research for this study. This final period begins on 1 August 2005

and ends on 28 February 2006.

3.4 Sample Description

The population for this study is the ASX 300 as at 28 September 2005 which

represented approximately 95% of the total market capitalisation of the ASX at that

date. The market capitalisation of firms in the ASX 300 ranged from $246 million to

$73.4 billion.4

The AIFRS reconciliation data used for this study was primarily collected

from AASB 1047 disclosures contained in 30 June 2005 preliminary final reports.

Generally, firms released their 30 June 2005 preliminary final reports within a two

month window – 1 August 2005 to 30 September 2005. Some firms did not include

AASB 1047 disclosures in their preliminary final report. Where a firm’s AASB 1047

4 The inclusion of medium and smaller sized firms improves the relevance of this study to firms of all sizes (Rees 1995, p. 307).

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disclosures was made available via other means, such as on the firm’s website or in

the entity’s annual report, that AASB 1047 source was utilised. All monetary data in

this study, including financial results and share price data, is stated in Australian

dollars (AUD). Where an entity’s financial report or AIFRS reconciliations were not

issued in AUD, for example BHP, the relevant amounts were translated to AUD using

the 30 June 2005 exchange rate available from the Australian Taxation Office

website.

Of the 300 firms considered for inclusion in the final sample, fifteen firms did

not report under AGAAP and were excluded from the sample. Also excluded were

ten firms that were either publicly listed for the first time within the twelve months

preceding 30 June 2005 or that underwent other structural changes such as a mergers

or de-mergers during that time. One hundred and two firms with a year-end other

than 30 June 2005 were also excluded from the final sample. This resulted in 173

firms that could potentially provide AIFRS reconciliation data that would be suitable

for the study. Table 1 presents a summary of the firms excluded from the ASX 300 to

arrive at the final sample.

[INSERT TABLE 1 ABOUT HERE]

Table 2 presents a summary of the AIFRS NPAT and equity reconciliations

provided by sample firms. Of the 173 firms included in the final sample, 113 firms

(65%) provided a reconciliation of NPAT at 30 June 2005, 71 firms (41%) provided a

reconciliation of equity at 30 June 2004 and 101 firms (59%) provided a

reconciliation of equity at 30 June 2005.

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[INSERT TABLE 2 ABOUT HERE]

To provide an understanding of the number of aggregate reconciliations issued

by each firm, of the 173 sample firms, 50 firms provided no aggregate reconciliations,

16 firms provided only one aggregate reconciliation, 51 firms provided two aggregate

reconciliations, and 56 firms provided all three aggregate reconciliations. Therefore,

where a firm issued reconciliation data it was likely to issue two or three of the

reconciliations of interest.

Share market return data for the ASX 300 entities was obtained from the

Datastream database. The precision of the Datastream return data was checked by

manually calculating the return for one entity based on its price and dividend history.

The preliminary final report dates used in this study were initially sourced

from the announcement date page on the Aspect Huntley web site. However, it was

found that these dates were often not the actual dates that preliminary final reports

were made public via ASIC. Therefore, additional confirmation of the actual ASIC

announcement date and time was necessary.5 The ASIC announcement date and time

information was ultimately sourced from the Aspect Huntley website using the

advanced search feature.

A check was performed regarding whether preliminary final reports were

released after market close (i.e., after 4pm Sydney time). This was necessary to

determine whether the day that a firm’s preliminary final report was released was the

first day that the market had an opportunity to react to the AIFRS disclosures

contained in the report. For firms that released their preliminary final reports after

market close their event day was considered to be the next ASX trading day. Of the

5 Rees (1995, p. 303) notes that “identifying the specific date that a particular item becomes public knowledge is critical when conducting event studies”.

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sample firms that provided AIFRS reconciliations, thirteen (7.5%) released their

preliminary final report after 4pm.

Some firms did not issue financial results by the preliminary final report due

date. Where these entities released AIFRS reconciliations on a later date, that date

was used as the event date.

Table 3 presents a summary of the sample firms grouped by GICS sector; the

number of aggregate reconciliations observed for each sector; and the percentage of

firms in each sector that provided at least one of the three aggregate reconciliations of

interest. The sample firms operate within 10 sectors. The three sectors most

represented in the sample are Financial, Industrials and Consumer Discretionary.

Firms within these sectors represent 62% of all sample firms and contribute 61% of

all aggregate AIFRS reconciliations. The three sectors with the lowest incidence of

firms providing aggregate reconciliations data are Telecommunication, Information

Technology and Utilities. Firms in these sectors represent 8% of all sample firms and

contribute 10% of all aggregate AIFRS reconciliations.

[INSERT TABLE 3 ABOUT HERE]

Table 4 presents the sample firms categorised by market capitalisation bands.

Eighty- six percent of large firms (i.e., ASX 1-50), 79% of medium firms (i.e., ASX

51-100), and 67% of small firms (i.e., ASX 101-300) provided at least one aggregate

AIFRS reconciliation.

[INSERT TABLE 4 ABOUT HERE]

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On average, larger firms disclosed more aggregate AIFRS reconciliation data

than smaller firms did. This difference is likely due to the extra resources available to

larger firms and more intense analyst scrutiny.

4. Analysis of Results

4.1 Aggregate Reconciliation Descriptive Statistics

Table 5 presents descriptive statistics of aggregate AIFRS reconciliation data

extracted from sample firm 30 June 2005 preliminary final reports. The population

for this data is the ASX 300. This data is used to provide evidence of whether AIFRS

disclosures are value relevant.

[INSERT TABLE 5 ABOUT HERE]

Overall, for the year ended 30 June 2005, sixty-five percent of sample firms

reported that NPAT would be higher under AIFRS than under AGAAP. Table 5

shows that for the year ended 30 June 2005, on average, firms reported that median

NPAT was $1.577 million higher under AIFRS than under AGAAP and mean NPAT

was $10.932 million higher under AIFRS than under AGAAP. As a percentage of

AGAAP NPAT, median and mean NPAT were approximately 4.2% and 7.1% higher

under AIFRS than under AGAAP, respectively. The frequency distribution is right-

skewed indicating that most sample firms reported higher NPAT under AIFRS than

under AGAAP.

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On the other hand, 79% of sample firms reported that equity as at 30 June

2004 would be lower under AIFRS than under AGAAP. Table 5 shows that as at 30

June 2004, on average, sample firms disclosed that median equity was $12.928

million lower under AIFRS than under AGAAP and that mean equity was $139.86

million lower under AIFRS than under AGAAP. As a percentage of AGAAP equity

as at 30 June 2004, median and mean equity were approximately 3.6% and 7.1%

lower under AIFRS than under AGAAP, respectively.

Finally, 65% of sample firms reported that equity as at 30 June 2005 was

lower under AIFRS than under AGAAP Table 5 shows that as at 30 June 2005, on

average, firms reported that median equity was $4.541 million lower under AIFRS

than under AGAAP and that mean equity was $169.954 million lower under AIFRS

than under AGAAP. As a percentage of AGAAP equity as at 30 June 2005, median

and mean equity were approximately 1.1% and 5.3% lower under AIFRS than under

AGAAP, respectively.

4.2 Short Return Window Event Test Results

Table 6 presents statistics of the cumulative abnormal returns of AIFRS

winners and losers in the twenty-two trading days (approximately one calendar

month) following the release of 30 June 2005 preliminary final reports. The results of

this test are presented graphically in Figure 1. Figures 2, 3 and 4 show the CAAR of

winners and losers during this period grouped by large, medium and small market

capitalisation.

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[INSERT TABLE 6 ABOUT HERE]

[INSERT FIGURE 1 ABOUT HERE]

[INSERT FIGURE 2 ABOUT HERE]

[INSERT FIGURE 3 ABOUT HERE]

[INSERT FIGURE 4 ABOUT HERE]

With respect to all firms within the ASX 300 that provided reconciliation data,

Table 6 shows that the CAAR of AIFRS winners exceeds the CAAR of AIFRS losers

in twenty-one out of the twenty-two days immediately following the release of 30

June 2005 final preliminary reports. The largest difference between the CAAR of

AIFRS winners and losers was 2.0% on day six. The largest difference between the

CAAR of the biggest AIFRS winners (firms with AIFRS NPAT increases in the

fourth quartile) and the biggest AIFRS losers (firms with AIFRS increases/decreases

in the first quartile) was 2.5% also on day six. On days sixteen and seventeen the

biggest AIFRS winners had CAAR that were 3.7% higher than the market return.

The short window test results show that the relationship between changes to

NPAT under AIFRS and market returns is positive for the ASX 300 as a whole,

however when considered by firm size, the relationship is negative for large firms and

positive for medium and small firms.6

Furthermore, the difference between the CAAR of AIFRS winners and losers

suggests that AIFRS NPAT reconciliations are value relevant. That is, firm CAAR

seem to vary in proportion to the impact of AIFRS on NPAT. Therefore, it is

suggested that generally cash flow neutral AIFRS NPAT disclosures are value

relevant.

6 Amir (1993, p. 262) notes the inclusion of observations of financial institutions may confound results produced by this type of test.

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As mentioned the largest difference between the CAAR of AIFRS winners

and losers was 2.0% on day six. This suggests that it took the market approximately

six days (the drift period) to incorporate into prices the value relevant information

contained in 30 June 2005 preliminary final reports. Notably, the difference between

the CAAR of AIFRS winners and losers was relatively stable for the sixteen trading

days immediately following the drift period (Days 7 to 22). Therefore, it is concluded

that the cumulative average abnormal returns of AIFRS winners and losers exhibit

post-announcement drift.

4.3 Intermediate Return Window Event Test Results

This test observes the CAAR of AIFRS winners and losers for the twenty-one

weeks following the release of the 30 June 2005 preliminary final reports. It is

performed to supplement the findings of the short window test and to gain an insight

into the medium-term CAAR characteristics of AIFRS winners and losers. The

results of this test are presented in Table 7. A graphical representation of the results is

provided in Figure 5. The weekly return statistics were derived by averaging the daily

average abnormal returns in each week. Table 7 shows that the CAAR of AIFRS

winners exceeded the CAAR of AIFRS losers in seventeen out of the twenty-one

weeks immediately following the release of 30 June 2005 preliminary reports. The

largest difference between the cumulative average abnormal returns of AIFRS

winners and losers was 3.1% in week fourteen.

[INSERT TABLE 7 ABOUT HERE]

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[INSERT FIGURE 5 ABOUT HERE]

The largest positive difference between the CAAR of the biggest AIFRS

winners (fourth quartile) and the biggest AIFRS losers (first quartile) was 2.6% in

week eight. Notably, in some weeks the group of firms that were the second biggest

losers (second quartile) had CAAR that was lower than the group of firms that were

the biggest AIFRS losers (first quartile). During week four the biggest AIFRS

winners (fourth quartile) have cumulative average returns that were 3.2% higher than

the market return.

Overall, the results of the intermediate window test are consistent with the

results of the short window test. The following points are noted. First, the post

announcement divergence between the CAAR of AIFRS winners and losers is clearly

observable suggesting that AIFRS NPAT disclosures are value relevant. Second, the

CAAR of AIFRS winners are higher than those of AIFRS losers, suggesting that

AIFRS NPAT changes and CAAR are positively related. Third, the intermediate

window results show that the post announcement divergence between the CAAR of

AIFRS winners and losers persists for approximately 95 days (see Figure 5).

4.4 Correlation Test Results

4.4.1 Correlation between Cumulative Abnormal Returns and NPAT

Reconciliations as a Percentage of AGAAP NPAT

For the year ending 30 June 2005, a scatter diagram was produced plotting

sample firm AIFRS NPAT reconciliations as a percentage of AGAAP NPAT against

23

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sample firm CAR measured from day -1 to day 5, where day 0 is the preliminary final

report release date. A six day event window was selected for this test based on the

results in Table 6 which show that the difference in CAAR of AIFRS winners and

losers reaches a relatively stable plateau approximately six days after the 30 June

2005 preliminary final reports are released to the market. A six day window also

gives the market time to react to the ostensibly ‘new’ quantitative AIFRS information

contained in 30 June 2005 preliminary reports. Rees (1995) uses a four day event

window for a similar study of reconciliations to US GAAP.

An examination of the initial scatter diagram revealed a number of outliers.

Outliers with values that were more than ± three standard deviations from their

respective mean were removed from the data before performing the Pearson’s

product-moment correlation analysis and producing a second scatter diagram.

[INSERT FIGURE 6 ABOUT HERE]

A review of the resulting scatter diagram reveals that most observations fall

within the upper-right quadrant indicating that sample firms with positive aggregate

AIFRS NPAT reconciliations generally produced positive CAR over the return

window period. For this outlier adjusted sample, over the observation period there

was a slight correlation between AIFRS NPAT reconciliations (expressed as a

percentage of NPAT under AGAAP) and CAR (r = 0.0916).

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4.4.2 Correlation by Firm Size

A similar correlation test was also performed for sample firms grouped by

market capitalisation. This analysis showed that the correlation between CAR and

AIFRS NPAT changes as a percentage of AGAAP NPAT was negative for large

firms (r = -0.0771). However, the correlation was positive for medium firms (r =

0.1384) and small firms (r = 0.0630). These results support the graphical data

presented in Figures 2, 3 and 4. It can be seen that large firm returns reacted

differently to generally cash flow neutral AIFRS adoption disclosures than medium

and small firms. This may be due to the larger analyst following enjoyed by large

firms.

4.43 Correlation by Sector

A further correlation test was performed for sample firms grouped by sector.

The results are presented in Table 8. This analysis shows that the correlation between

CAR and aggregate AIFRS NPAT changes as a percentage of AGAAP NPAT is

positive for five out of nine sectors.

[INSERT TABLE 8 ABOUT HERE]

4.5 Long Window Association Test Results

Table 9 presents the cumulative return performance of AIFRS winners and

losers relative to the mean cumulative return performance of all sample firms. The

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window for this test spans the forty-four months commencing with the announcement

on 3 July 2002 of the decision to adopt AIFRS and ending with the issue of the first

AIFRS half-year financial reports in February 2006. The return results during this

window are grouped into three disclosure periods: pre-disclosure, qualitative

disclosure and quantitative disclosure. Table 9 shows that the cumulative returns of

AIFRS losers were lower than the cumulative returns AIFRS winners in twenty-four

months out of the forty-four month observation window (56%).

The data in the Table 9 is derived as follows. The cumulative return of each

firm is determined for the period starting 3 July 2002 and ending at the end of the

month being tested. The mean of the cumulative returns of all sample firms is also

determined for this period. These results are compared. For example, in the test for

Jul 02, it was found that 59% (39%) of AIFRS losers (winners) had a cumulative

return that was below the mean of the cumulative returns of all sample firms. By

necessity, for the same period, 41% (61%) of AIFRS losers (winners) had a

cumulative return that was above the mean of the cumulative returns of all sample

firms. In this manner, the cumulative return performance of AIFRS winners and

losers relative to the cumulative returns of all sample firms was identified for each

month in the observation period.

[INSERT TABLE 9 ABOUT HERE]

Considered on a “disclosure period” basis, during the pre-disclosure period

AIFRS losers had lower cumulative returns than AIFRS winners in eleven out of

twenty-five months (44%), during the qualitative disclosure period AIFRS losers had

26

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lower cumulative returns in eight out of twelve months (67%), and during the

quantitative disclosure period AIFRS losers had lower cumulative returns than AIFRS

winners in five out of six months (83%).

Overall, these ‘disclosure period’ based results suggest that the cumulative

returns of AIFRS losers progressively deteriorated in the lead up to the adoption of

AIFRS relative to the mean of the cumulative returns of all sample firms. It is

suggested that this relative deterioration occurs in response to the increasingly

detailed information released by AIFRS losers to the market disclosing the negative

impact that AIFRS would have on their reported financial performance.

In summary, Table 9 shows that the relative return performance of AIFRS

winners and losers across the disclosure periods is not the same. The cumulative

returns of AIFRS losers are relatively better in the pre-disclosure period when little

AIFRS information was available, whilst the cumulative returns of AIFRS winners

are relatively better in the quantitative disclosure period when the market is more

aware of the expected quantitative impacts of AIFRS. Therefore, it is concluded that

there is no association between AIFRS NPAT reconciliations and long term

cumulative returns. For the same reasons, it is also concluded that the Cumulative

returns during the three disclosure periods are not associated with AIFRS NPAT

changes.

4.6 Markov Switching Analysis Results

Table 10 presents Markov Switching Analysis regime probabilities for sample firms.

The window for this test commences 1 January 2000 and ends on 28 February 2006.

The test results show the regime probabilities for AIFRS winners and losers during

27

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the three disclosure periods. Similar to the long window association test, the

observation window is grouped into three disclosure periods: pre-announcement (as

opposed to pre-disclosure in long window association test), qualitative disclosure and

quantitative disclosure.

[INSERT TABLE 10 ABOUT HERE]

The regime probabilities in Table 10 show that in the pre-announcement period

AIFRS winners were classified by the Markov Switching Analysis as being in the

high growth regime for a lesser amount of time (6.0%) than AIFRS losers (7.9%).

Similarly, in the qualitative disclosure period AIFRS winners were classified as being

in the high growth regime for a lesser amount of time (17.3%) than AIFRS losers

(18.5%). However, in the quantitative disclosure period AIFRS winners were

classified as being in the high growth regime for a greater amount of time (18.2%)

than AIFRS losers (15.6%). These statistics show that in the period following the

disclosure of quantitative AIFRS information the returns of AIFRS winners exhibited

high growth characteristics for a greater amount of time than the returns of AIFRS

losers which is a reversal of the situation that existed in both the pre-announcement

and qualitative disclosure periods.

In relation to time spent in the recession regime, in the pre-announcement

period AIFRS winners were classified as being in the recession regime for a greater

amount of time (30.3%) than AIFRS losers (26.7%). Similarly, in the qualitative

disclosure period AIFRS winners were classified as being in the recession regime for

a greater amount of time (18.2%) than AIFRS losers (17.3%). However, in the

quantitative disclosure period AIFRS winners were classified as being in the recession

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Page 29: 1. INTRODUCTION

regime for a lesser amount of time (23.8%) than AIFRS losers (27.2%). These

statistics show that in the period following the release of quantitative AIFRS

information the returns of AIFRS winners exhibited recessionary characteristics for a

lesser amount of time than the returns of AIFRS losers. Again, this is a reversal of the

situation that existed in both the pre-announcement and qualitative disclosure periods.

In summary, the Markov Switching Analysis provides objective evidence that

following the release of 30 June 2005 AASB 1047 disclosures the share market

returns of AIFRS winners were more ‘bull-like’ (i.e., high-growth) and less ‘bear-

like’ (i.e., recessionary) than the market returns of AIFRS losers. This is a reversal of

the return characterisations for these groups that existed prior to the release of

quantitative AIFRS disclosures. If the return characteristics of AIFRS winners and

losers were unrelated to the expected impact of AIFRS on those firms, the relative

regime probabilities of AIFRS winners and losers should be similar in any given

disclosure period. This is not the case. Therefore, it is concluded that changes to

return characteristics (i.e., regime probabilities) of AIFRS winners and losers across

disclosure periods will be uniform and unrelated to the expected impact of AIFRS on

NPAT.

5. Summary and Conclusions

This paper investigated the impact of the adoption of AIFRS on market values.

Five empirical tests investigating the value relevance of qualitative and quantitative

AIFRS disclosures were conducted. The tests also examined the relative market

performance of AIFRS winners and losers over short, intermediate and long windows.

29

Page 30: 1. INTRODUCTION

The tests in this paper are motivated by the Australian share market’s buoyant

behaviour surrounding the initial release of quantitative AIFRS information.

Particularly of interest was whether share market returns were being driven by

disclosures of increased NPAT under AIFRS. However, assuming that the share

market is efficient, intuition suggests that disclosures of increased earnings under

AIFRS alone should not drive market returns higher without related increases to

underlying cash flows. Despite the lack of underlying changes to cash flow, the test

results show that the share market performance of AIFRS winners consistently

exceeded that of AIFRS losers over the following periods: (1) the twenty-two trading

days immediately following the release of quantitative AIFRS data; (2) the twenty-

one trading weeks immediately following the release of quantitative AIFRS data, and

(3) the period beginning prior to the announcement to adopt AIFRS and ending six

months after the release of quantitative AIFRS data. These results are supported by

an objective Markov Switching Analysis test.

Overall, the results suggest that AIFRS NPAT disclosures are value relevant.

This finding is consistent with those of Amir, Harris and Venuti (1993) and Rees

(1995) who, in studies involving reconciliations to US GAAP from non-US GAAP,

found a positive relationship between aggregate alternative accounting standard

reconciliations and market-adjusted returns.

The test results in this study suggest that the positive impact of AIFRS on

NPAT has flowed through to the security values of medium and small firms.

Uncertainty exists regarding why investors in these firms have apparently reacted to

reports of increased earnings under AIFRS that are broadly unaccompanied by similar

increases to underlying cash flows. Market values of large firms are seemingly

unaffected by reports of higher NPAT under AIFRS. The results of this study leave

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Page 31: 1. INTRODUCTION

open the question of whether the market’s overall positive reaction following the

release of quantitative AIFRS disclosures is due to: (1) earnings being misstated under

AGAAP and therefore being more accurate under AIFRS; (2) the market being

inefficient and unduly reacting to cash flow neutral AIFRS earnings information; or

(3) some other reason. Given these possibilities, it is suggested that quantitative

AIFRS NPAT disclosures of medium and small firms are positively related to changes

in market value as these firms have smaller analyst followings and are therefore more

open to the influence of AIFRS disclosures. This paper provides a basis for further

investigations regarding this issue.

The inclusion of AIFRS comparatives in 30 June 2005 preliminary final

reports presents researchers with a unique data set that can be used to study the

market’s reaction to alternative accounting information in an Australian context. In

summary, the test results presented in this dissertation show that AIFRS winners

generated higher market returns than AIFRS losers following the release of

quantitative AIFRS data. This finding is important for several reasons. First, it

suggests that a naive trading strategy based on cash flow neutral AIFRS earnings

results would have generated cumulative abnormal returns of up to two and a half

percent. Second, it suggests that quantitative AASB 1047 disclosures are value

relevant which in turn implies that the market believes that AIFRS produces higher

quality accounting information than AGAAP.

Possibilities for further research arising from the discussions in this

dissertation include the following. First, due to the novelty of AIFRS disclosures,

further research could investigate whether the market takes longer to react to earnings

surprises stemming from AIFRS disclosures than from AGAAP disclosures. For

example, an analysis of the post-announcement drift durations following AGAAP and

31

Page 32: 1. INTRODUCTION

AIFRS earnings surprises could be undertaken. Second, research could investigate

whether the accuracy of analyst’s forecasts improves following the adoption of

AIFRS. This would provide additional evidence regarding the quality of the new

standards relative to AGAAP.

32

Page 33: 1. INTRODUCTION

References

AASB 1047 Disclosing the impacts of adopting Australian equivalents to

International Financial Reporting Standards.

Alderton, R. 2006, NAB profits alter substantially under changes to IFRS, CCH

Australia Limited, 9 May 2006.

Amir, E., T. S. Harris, and E. K. Venuti, 1993, A comparison of the value relevance

of US versus non-U.S. GAAP accounting measures using Form 20-F

Reconciliations, Journal of Accounting Research, 31(Supplement), 230–264.

Barth, M. E. and G. Clinch, 1996, International accounting differences and their

relation to share prices: evidence from U.K., Australian, and Canadian Firms,

Contemporary Accounting Research, 13, 135–170.

Beaver, W. 1968, The information content of annual earnings announcements,

Journal of Accounting Research, Supplement 6, 67–92.

Becis, T.; C. Ng, and E. Roca, 2006, The mpact of the adoption of the Australian

International Financial Reporting Standards on profits and equity of Australian

companies, unpublished paper, Griffith University.

Buffini, F. 2006, Whole new standard of confusion, Financial Review, 24 March

2006, 1.

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CPA Australia. 2006, Business ready for AIFRS but ‘wait and see’ on benefits,

28 February 2006,

[http://www.cpaaustralia.com.au/cps/rde/xchg/cpa/hs.xsl/1017_17590_ENA_HT

ML.htm].

Deloitte and Touche. 2003, Use of IFRS for reporting by domestic listed companies

by country, IAS plus website [http://www.iasplus.com].

Ernst & Young, 2005, The impacts of AIFRS on Australian companies: a study of the

financial statement disclosures by Australia’s top 100 listed companies.

Financial Reporting Council. 2002, Bulletin 2002/4 Adoption of international

accounting standards by 2005, 3 July 2002.

Financial Reporting Council. 2005, 2005 Timeline planning framework, Information

Paper first issued, December 2003, [http://www.frc.gov.au/reports/other/info-

paper.asp].

Hamilton, J. D. 1989, A new approach to the economic analysis of non-stationary

time series and the business cycle, Econometrica, 57(2), 357-384.

Hogan, R. 2005, Harder than it looks, CFO, John Fairfax Holdings Limited,

1 October 2005, 20.

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Jubb, C., 2005, Transition to IFRS: listed companies’ expected accounting policy

impacts as revealed by AASB 1047 Disclosures, Media Release, Institute of

Chartered Accountants in Australia, 16 March 2005.

Kothari, S. P., 2001, Capital markets research in accounting, Journal of Accounting

and Economics, 31, 105-231.

KPMG, 2005, Perceptions and realities: Market perception and the realities of

financial reporting under the Australian equivalents of International Financial

Reporting Standards, [http://www.kpmg.com.au/Portals/0/aifrs-perceptions-

paper.pdf].

Krolzig, H.-M., 1997, Markov-Switching vector auto-regressions, Modelling,

statistical inference and application to business cycle analysis, Lecture Notes in

Economics and Mathematical Systems, 454, Berlin: Springer.

Rees, L. L., 1995, The information contained in reconciliations to earnings based on

US accounting principles by non-US companies, Accounting and Business

Research, 25 (100), 301–310.

Roca, E. and Wong, V. forthcoming, An analysis of the sensitivity of Australian

superannuation funds to market movements: a Markov Regime Switching

approach, Applied Financial Economics.

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Venkatachalam, M., 1999, Are 20-F reconciliations between IAS and US-GAAP

value relevant: A discussion, Journal of Accounting and Economics, 26, 313–318.

Wilson, G. P., 1986, The relative information content of accruals and cash flows:

combined evidence at the earnings announcement and annual report release date,

Journal of Accounting Research, Supplement, 24, 165-200.

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TABLE 1

Sample Firms: Potential AIFRS Reconcilers:

Extracted from 30 June 2005 Preliminary Final Reports

Population – ASX 300 at 28 September 2005 300— Firms that do not disclose under AGAAP 15— Firms not listed for twelve months or that were restructured 10— Firms that do not have a 30 June 2005 year end 102Total sample firms 173

TABLE 2

Sample Firms: Actual AIFRS Reconcilers:

Extracted from 30 June 2005 Preliminary Final Reports

NPAT30 June 2005

Equity1 July 2004

Equity30 June 2005

Total sample firms 173 173 173— No Reconciliation 60 102 71Total Aggregate Reconciliations

113 71 102

Reconciliation Change— AIFRS Increase 72 9 30— AIFRS Decrease 39 56 66— No Change 2 6 6Total Aggregate Reconciliations

113 71 102

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TABLE 3

AIFRS Reconciliations by Sector:

Extracted from 30 June 2005 Preliminary Final Reports

Sector Firms Sum of Aggregate NPAT and Equity Reconciliations

Percentage of Firms Providing

One or More Reconciliation

Consumer Discretionary

26 49 0.77

Consumer Staples 7 13 0.71Energy 10 16 0.80Financials 53 86 0.72Health Care 13 18 0.69Industrials 29 40 0.59Information Technology

5 10 0.80

Materials 21 36 0.67Telecommunication 3 7 1.00Utilities 6 11 0.83

Total 173 Total 286 Ave 0.71

TABLE 4

AIFRS Reconciliations by Market Capitalisation:

Extracted from 30 June 2005 Preliminary Final Reports

MarketCapitalisationBand

Firms Observations(Aggregate NPAT and

Equity Reconciliations)

Percentage of Firms Providing

Reconciliations

ASX 1–50 (Lge) 22 45 0.86ASX 51–100 (Med) 28 48 0.79ASX 101–300 (Sml)

123 193 0.67

Total 173 Total 284 Ave 0.71

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TABLE 5

Summary Statistics for Aggregate AIFRS Reconciliations of All Sample Firms:

Extracted from 30 June 2005 Preliminary Final Reports

Median Mean(Ave)

Standard Deviation

First Quartile

Third Quartile

Number of Observations

∆N 1.577  10.932  93.338  –0.875  14.099  113        ∆N/N 4.2%  7.1%  68.2%  –2.5%  20.6%  113        ∆N/E05 0.6%  0.8%  3.8%  –0.6%  2.4%  113        ∆E04 –12.928  –139.860  419.610  –81.493  –0.500  71        ∆E04/E04 –3.6%  –7.1%  17.9%  –9.7%  –0.2%  71        ∆E05 –4.541  –169.954  781.220  –49.827  0.904  102        ∆E05/E05 –1.1%  –5.3%  19.9%  –7.5%  0.5%  102        

∆Nis the change in NPAT under AIFRS (compared to NPAT under AGAAP) for the year ended 30 June 2005 (‘millions).

∆N/Nis the change in NPAT under AIFRS for the year ended 30 June 2005 expressed as a percentage of AGAAP NPAT for the year ended 30 June 2005.

∆N/E5is the change in NPAT under AIFRS for the year ended 30 June 2005 expressed as a percentage of AGAAP equity at 30 June 2005.

∆E04 is the change in equity under AIFRS at 30 June 2004 (‘millions).

∆E04/E04is the change in equity under AIFRS at 30 June 2004 expressed as a percentage of AGAAP equity at 30 June 2004.

∆E05 is the change in equity under AIFRS at 30 June 2005 (‘millions).

∆E05/E05is the change in equity under AIFRS at 30 June 2005 expressed as a percentage of AGAAP equity at 30 June 2005.

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TABLE 6

Cumulative Average Abnormal Returns for the Twenty Two Trading Days following

the Release of 30 June 2005 Preliminary Final Reports (Short Window)

Trading Day

All SampleFirms

AIFRS Losers

AIFRS Winners

W +/- L 1st

Quartile2nd

Quartile3rd

Quartile4th

Quartile

1 0.008 0.007 0.008 0.001 0.005 0.012 0.004 0.0112 0.010 0.003 0.013 0.010 (0.001) 0.017 0.003 0.0193 0.013 0.007 0.015 0.008 0.002 0.022 0.004 0.0224 0.012 0.005 0.016 0.011 0.004 0.017 0.008 0.0205 0.015 0.002 0.021 0.019 0.002 0.019 0.017 0.0216 0.018 0.004 0.025 0.020 0.004 0.022 0.019 0.0287 0.018 0.008 0.023 0.015 0.012 0.020 0.015 0.0278 0.016 0.005 0.022 0.016 0.007 0.021 0.010 0.0279 0.016 0.005 0.022 0.017 0.006 0.019 0.013 0.02410 0.014 0.003 0.020 0.017 0.006 0.013 0.012 0.02411 0.016 0.005 0.023 0.017 0.007 0.013 0.014 0.03012 0.014 0.002 0.021 0.019 0.006 0.010 0.013 0.02713 0.015 0.007 0.020 0.014 0.012 0.008 0.010 0.03014 0.016 0.005 0.022 0.017 0.012 0.008 0.010 0.03215 0.019 0.011 0.023 0.012 0.020 0.012 0.011 0.03416 0.020 0.013 0.024 0.011 0.022 0.011 0.011 0.03717 0.019 0.011 0.024 0.014 0.018 0.013 0.008 0.03718 0.017 0.011 0.022 0.011 0.018 0.010 0.007 0.03319 0.016 0.008 0.020 0.012 0.015 0.008 0.006 0.03420 0.016 0.012 0.020 0.008 0.018 0.007 0.003 0.03521 0.015 0.014 0.017 0.002 0.023 0.005 0.002 0.03022 0.018 0.020 0.019 -0.001 0.027 0.008 0.007 0.029

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TABLE 7

Cumulative Average Abnormal Returns for the Twenty One Weeks following the

release of 30 June 2005 Preliminary Final Reports (Intermediate Window)

Trading Week

All SampleFirms

AIFRS Losers

AIFRS Winners

W +/- L 1st

Quartile2nd

Quartile3rd

Quartile4th

Quartile

1 0.011  0.005  0.014  0.010  0.009  0.001  0.019  0.017 2 0.017  0.005  0.022  0.017  0.011  0.003  0.032  0.020 3 0.016  0.006  0.022  0.016  0.015  -0.006  0.029  0.025 4 0.018  0.011  0.022  0.011  0.018  -0.002  0.021  0.032 5 0.017  0.019  0.017  -0.001  0.025  -0.002  0.019  0.025 6 0.013  0.019  0.011  -0.008  0.017  0.004  0.010  0.021 7 0.009  0.003  0.014  0.010  0.003  0.001  0.010  0.023 8 0.007  -0.003  0.015  0.017  0.000  -0.010  0.012  0.026 9 0.005  -0.005  0.013  0.018  0.005  -0.023  0.013  0.024 10 0.008  -0.002  0.016  0.018  0.012  -0.026  0.020  0.024 11 0.003  -0.005  0.010  0.015  0.010  -0.025  0.014  0.012 12 -0.005  -0.017  0.004  0.021  0.007  -0.042  0.010  0.003 13 -0.011  -0.026  0.001  0.027  -0.003  -0.049  0.009  -0.001 14 -0.015  -0.033  -0.002  0.031  -0.010  -0.044  0.005  -0.010 15 -0.017  -0.034  -0.004  0.030  -0.013  -0.044  0.004  -0.015 16 -0.016  -0.031  -0.005  0.025  -0.004  -0.046  0.000  -0.016 17 -0.013  -0.020  -0.006  0.013  0.010  -0.041  -0.002  -0.020 18 -0.015  -0.016  -0.011  0.005  0.015  -0.037  -0.014  -0.024 19 -0.015  -0.015  -0.012  0.003  0.013  -0.037  -0.013  -0.023 20 -0.014  -0.007  -0.014  -0.007  0.023  -0.039  -0.013  -0.026 21 -0.017  -0.006  -0.019  -0.013  0.025  -0.045  -0.012  -0.035 

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TABLE 8

Correlation by Industry of Aggregate AIFRS NPAT Reconciliations and Cumulative Average

Abnormal Returns

Sector n ∆N/N R rConsumer Discretionary 18        0.0689     0.0313      0.1113   Consumer Staples 5        0.3876    –0.0092     0.3398   Energy* 7       –0.2282     0.0192    –0.1549   Financials* 35        0.1500     0.0080     0.1114   Health Care 8        0.1478     0.0351     0.7654   Industrials* 15        0.0555     0.0315    –0.3156   Information Technology 4        0.1703    –0.0025     0.1787   Materials* 10       –0.3028     0.0218    –0.2068   Telecommunication 2        0.7731     0.0694    -    Utilities 5        0.0620    –0.0085    –0.1858   

n is the number of NPAT reconciliation observations for the industry.

∆N/Nis the average change in NPAT under AIFRS for the year ended 30 June 2005 expressed as a percentage of AGAAP NPAT for the year ended 30 June 2005.

Rthe market–adjusted return from day -1 to day 5, where day 0 is the preliminary final report release date.

ris the correlation coefficient. Correlation only shown for industries with three or more observations.

* one outlier removed from this industry.

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TABLE 9

Long Window Relative Cumulative Returns Surrounding the Release of Quantitative AIFRS Disclosures: July 2002 to January 2006

Below Mean Cumulative Returns Above Mean Cumulative ReturnsMonth Losers Winners Lowest Losers Winners HighestPre-Disclosure period:Jul 02 0.59 0.39 L 0.41 0.61 WAug 02 0.63 0.54 L 0.38 0.46 WSep 02 0.75 0.44 L 0.25 0.56 WOct 02 0.59 0.38 L 0.41 0.62 WNov 02 0.63 0.41 L 0.38 0.59 WDec 02 0.63 0.43 L 0.38 0.57 WJan 03 0.69 0.46 L 0.31 0.54 WFeb 03 0.63 0.48 L 0.38 0.52 WMar 03 0.66 0.49 L 0.34 0.51 WApr 03 0.69 0.57 L 0.31 0.43 WMay 03 0.63 0.59 L 0.38 0.41 WJun 03 0.63 0.66 W 0.38 0.34 LJul 03 0.69 0.70 W 0.31 0.30 LAug 03 0.72 0.72 W 0.28 0.28 LSep 03 0.69 0.79 W 0.31 0.21 LOct 03 0.69 0.75 W 0.31 0.25 LNov 03 0.69 0.79 W 0.31 0.21 LDec 03 0.63 0.79 W 0.38 0.21 LJan 04 0.69 0.80 W 0.31 0.20 LFeb 04 0.69 0.75 W 0.31 0.25 LMar 04 0.63 0.75 W 0.38 0.25 LApr 04 0.66 0.70 W 0.34 0.30 LMay 04 0.66 0.74 W 0.34 0.26 LJun 04 0.66 0.70 W 0.34 0.30 LJul 04 0.59 0.72 W 0.41 0.28 LAverage 0.44 0.56 0.56 0.44Qualitative Disclosure Period:Aug 04 0.66 0.74 W 0.34 0.26 LSep 04 0.72 0.74 W 0.28 0.26 LOct 04 0.72 0.74 W 0.28 0.26 LNov 04 0.84 0.82 L 0.16 0.18 WDec 04 0.78 0.77 L 0.22 0.23 WJan 05 0.88 0.84 L 0.13 0.16 WFeb 05 0.88 0.84 L 0.13 0.16 WMar 05 0.81 0.84 W 0.19 0.16 LApr 05 0.84 0.82 L 0.16 0.18 WMay 05 0.84 0.80 L 0.16 0.20 WJun 05 0.84 0.84 L 0.16 0.16 WAverage 0.67 0.33 0.33 0.67Quantitative Disclosure Period:Jul 05 0.84 0.84 L 0.16 0.16 WAug 05 0.84 0.85 W 0.16 0.15 LSep 05 0.91 0.87 L 0.09 0.13 WOct 05 0.91 0.87 L 0.09 0.13 WNov 05 0.91 0.89 L 0.09 0.11 WDec 05 0.91 0.89 L 0.09 0.11 WJan 06 0.91 0.90 L 0.09 0.10 WAverage 0.83 0.17 0.17 0.83

Average All 0.56 0.44 0.44 0.56

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TABLE 10

Markov Switching Analysis Regime Probabilities and Durations:

1 January 2000 to 28 February 2006

AIFRSWinners / Losers

Disclosure Period

Regime Number of Observations

Average Probability

Average Duration

Winners Pre-announce High 49 0.060 3.3      Normal 49 0.616 14.5      Recession 49 0.303 4.3      

Qualitative High 56 0.173 14.1      Normal 56 0.645 67.7      Recession 56 0.182 9.8      

Quantitative High 55 0.182 1.5      Normal 55 0.580 6.1      Recession 55 0.238 1.7      

Losers Pre-announce High 21 0.079 5.2      Normal 21 0.654 16.6      Recession 21 0.267 4.0      

Qualitative High 25 0.185 12.3      Normal 25 0.642 60.9      Recession 25 0.173 6.2      

Quantitative High 25 0.156 1.6      Normal 25 0.573 4.7      Recession 25 0.272 1.9      

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Page 45: 1. INTRODUCTION

FIGURE 1

Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 300

FIGURE 2

Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 1-50 (Large Firms)

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Page 46: 1. INTRODUCTION

FIGURE 3

Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 51-100 (Medium Firms)

FIGURE 4

Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 101-300 (Small Firms)

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Page 47: 1. INTRODUCTION

FIGURE 5

Intermediate Window Cumulative Average Abnormal Returns for the Twenty-One Weeks (105 Trading Days) following the Event

FIGURE 6

Scatter Diagram: AIFRS NPAT 30 June 2005 Reconciliations and Market-Adjusted Returns

47


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