1. INTRODUCTION

449 views
358 views

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
449
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
3
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

1. INTRODUCTION

  1. 1. 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 Please do not quote without permission from the authors) Key words: International accounting harmonisation, AIFRS, value relevance, post- earnings-announcement drift, and Markov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: Department of Accounting, Finance and Economics Griffith Business School Griffith University Nathan Campus QLD 4111 Tel: (07) 3735 6492 Fax: (07) 3735 7760
  2. 2. 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. 2
  3. 3. 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 3
  4. 4. 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, 4
  5. 5. 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 5
  6. 6. 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 6
  7. 7. 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: 7
  8. 8. 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). 8
  9. 9. 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. 9
  10. 10. 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 10
  11. 11. 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. 11
  12. 12. 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. 12
  13. 13. 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. 13
  14. 14. 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 14
  15. 15. 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). 15
  16. 16. 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. 16
  17. 17. [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”. 17
  18. 18. 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] 18
  19. 19. 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. 19
  20. 20. 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. 20
  21. 21. [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. 21
  22. 22. 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] 22
  23. 23. [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
  24. 24. 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). 24
  25. 25. 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 25
  26. 26. 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
  27. 27. 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
  28. 28. 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 28
  29. 29. 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
  30. 30. 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 30
  31. 31. 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
  32. 32. 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
  33. 33. 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. 33
  34. 34. 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. 34
  35. 35. 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. 35
  36. 36. 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. 36
  37. 37. 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 102 Total sample firms 173 TABLE 2 Sample Firms: Actual AIFRS Reconcilers: Extracted from 30 June 2005 Preliminary Final Reports NPAT Equity Equity 30 June 2005 1 July 2004 30 June 2005 Total sample firms 173 173 173 — No Reconciliation 60 102 71 Total Aggregate 113 71 102 Reconciliations Reconciliation Change — AIFRS Increase 72 9 30 — AIFRS Decrease 39 56 66 — No Change 2 6 6 Total Aggregate 113 71 102 Reconciliations 37
  38. 38. TABLE 3 AIFRS Reconciliations by Sector: Extracted from 30 June 2005 Preliminary Final Reports Sector Firms Sum of Aggregate Percentage of NPAT and Equity Firms Providing Reconciliations One or More Reconciliation Consumer Discretionary 26 49 0.77 Consumer Staples 7 13 0.71 Energy 10 16 0.80 Financials 53 86 0.72 Health Care 13 18 0.69 Industrials 29 40 0.59 Information Technology 5 10 0.80 Materials 21 36 0.67 Telecommunication 3 7 1.00 Utilities 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 Market Firms Observations Percentage of Firms Capitalisation (Aggregate NPAT and Providing Band Equity Reconciliations) Reconciliations ASX 1–50 (Lge) 22 45 0.86 ASX 51–100 (Med) 28 48 0.79 ASX 101–300 (Sml) 123 193 0.67 Total 173 Total 284 Ave 0.71 38
  39. 39. TABLE 5 Summary Statistics for Aggregate AIFRS Reconciliations of All Sample Firms: Extracted from 30 June 2005 Preliminary Final Reports Median Mean Standard First Third Number of (Ave) Deviation Quartile Quartile 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 is the change in NPAT under AIFRS (compared to NPAT under AGAAP) for ∆N the year ended 30 June 2005 (‘millions). is the change in NPAT under AIFRS for the year ended 30 June 2005 ∆N/N expressed as a percentage of AGAAP NPAT for the year ended 30 June 2005. is the change in NPAT under AIFRS for the year ended 30 June 2005 ∆N/E5 expressed as a percentage of AGAAP equity at 30 June 2005. ∆E04 is the change in equity under AIFRS at 30 June 2004 (‘millions). is the change in equity under AIFRS at 30 June 2004 expressed as a ∆E04/E04 percentage of AGAAP equity at 30 June 2004. ∆E05 is the change in equity under AIFRS at 30 June 2005 (‘millions). is the change in equity under AIFRS at 30 June 2005 expressed as a ∆E05/E05 percentage of AGAAP equity at 30 June 2005. 39
  40. 40. 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 All AIFRS AIFRS W +/- L 1st 2nd 3rd 4th Day Sample Losers Winners Quartile Quartile Quartile Quartile Firms 1 0.008 0.007 0.008 0.001 0.005 0.012 0.004 0.011 2 0.010 0.003 0.013 0.010 (0.001) 0.017 0.003 0.019 3 0.013 0.007 0.015 0.008 0.002 0.022 0.004 0.022 4 0.012 0.005 0.016 0.011 0.004 0.017 0.008 0.020 5 0.015 0.002 0.021 0.019 0.002 0.019 0.017 0.021 6 0.018 0.004 0.025 0.020 0.004 0.022 0.019 0.028 7 0.018 0.008 0.023 0.015 0.012 0.020 0.015 0.027 8 0.016 0.005 0.022 0.016 0.007 0.021 0.010 0.027 9 0.016 0.005 0.022 0.017 0.006 0.019 0.013 0.024 10 0.014 0.003 0.020 0.017 0.006 0.013 0.012 0.024 11 0.016 0.005 0.023 0.017 0.007 0.013 0.014 0.030 12 0.014 0.002 0.021 0.019 0.006 0.010 0.013 0.027 13 0.015 0.007 0.020 0.014 0.012 0.008 0.010 0.030 14 0.016 0.005 0.022 0.017 0.012 0.008 0.010 0.032 15 0.019 0.011 0.023 0.012 0.020 0.012 0.011 0.034 16 0.020 0.013 0.024 0.011 0.022 0.011 0.011 0.037 17 0.019 0.011 0.024 0.014 0.018 0.013 0.008 0.037 18 0.017 0.011 0.022 0.011 0.018 0.010 0.007 0.033 19 0.016 0.008 0.020 0.012 0.015 0.008 0.006 0.034 20 0.016 0.012 0.020 0.008 0.018 0.007 0.003 0.035 21 0.015 0.014 0.017 0.002 0.023 0.005 0.002 0.030 22 0.018 0.020 0.019 -0.001 0.027 0.008 0.007 0.029 40
  41. 41. TABLE 7 Cumulative Average Abnormal Returns for the Twenty One Weeks following the release of 30 June 2005 Preliminary Final Reports (Intermediate Window) Trading All AIFRS AIFRS W +/- L 1st 2nd 3rd 4th Week Sample Losers Winners Quartile Quartile Quartile Quartile Firms 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 41
  42. 42. TABLE 8 Correlation by Industry of Aggregate AIFRS NPAT Reconciliations and Cumulative Average Abnormal Returns Sector n ∆N/N R r Consumer 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. is the average change in NPAT under AIFRS for the year ended 30 June ∆N/N 2005 expressed as a percentage of AGAAP NPAT for the year ended 30 June 2005. the market–adjusted return from day -1 to day 5, where day 0 is the R preliminary final report release date. is the correlation coefficient. Correlation only shown for industries with r three or more observations. * one outlier removed from this industry. 42
  43. 43. TABLE 9 Long Window Relative Cumulative Returns Surrounding the Release of Quantitative AIFRS Disclosures: July 2002 to January 2006 43
  44. 44. Below Mean Cumulative Returns Above Mean Cumulative Returns Month Losers Winners Lowest Losers Winners Highest Pre-Disclosure period: Jul 02 0.59 0.39 L 0.41 0.61 W Aug 02 0.63 0.54 L 0.38 0.46 W Sep 02 0.75 0.44 L 0.25 0.56 W Oct 02 0.59 0.38 L 0.41 0.62 W Nov 02 0.63 0.41 L 0.38 0.59 W Dec 02 0.63 0.43 L 0.38 0.57 W Jan 03 0.69 0.46 L 0.31 0.54 W Feb 03 0.63 0.48 L 0.38 0.52 W Mar 03 0.66 0.49 L 0.34 0.51 W Apr 03 0.69 0.57 L 0.31 0.43 W May 03 0.63 0.59 L 0.38 0.41 W Jun 03 0.63 0.66 W 0.38 0.34 L Jul 03 0.69 0.70 W 0.31 0.30 L Aug 03 0.72 0.72 W 0.28 0.28 L Sep 03 0.69 0.79 W 0.31 0.21 L Oct 03 0.69 0.75 W 0.31 0.25 L Nov 03 0.69 0.79 W 0.31 0.21 L Dec 03 0.63 0.79 W 0.38 0.21 L Jan 04 0.69 0.80 W 0.31 0.20 L Feb 04 0.69 0.75 W 0.31 0.25 L Mar 04 0.63 0.75 W 0.38 0.25 L Apr 04 0.66 0.70 W 0.34 0.30 L May 04 0.66 0.74 W 0.34 0.26 L Jun 04 0.66 0.70 W 0.34 0.30 L Jul 04 0.59 0.72 W 0.41 0.28 L Average 0.44 0.56 0.56 0.44 Qualitative Disclosure Period: Aug 04 0.66 0.74 W 0.34 0.26 L Sep 04 0.72 0.74 W 0.28 0.26 L Oct 04 0.72 0.74 W 0.28 0.26 L Nov 04 0.84 0.82 L 0.16 0.18 W Dec 04 0.78 0.77 L 0.22 0.23 W Jan 05 0.88 0.84 L 0.13 0.16 W Feb 05 0.88 0.84 L 0.13 0.16 W Mar 05 0.81 0.84 W 0.19 0.16 L Apr 05 0.84 0.82 L 0.16 0.18 W May 05 0.84 0.80 L 0.16 0.20 W Jun 05 0.84 0.84 L 0.16 0.16 W Average 0.67 0.33 0.33 0.67 Quantitative Disclosure Period: Jul 05 0.84 0.84 L 0.16 0.16 W Aug 05 0.84 0.85 W 0.16 0.15 L Sep 05 0.91 0.87 L 0.09 0.13 W Oct 05 0.91 0.87 L 0.09 0.13 W Nov 05 0.91 0.89 L 0.09 0.11 W Dec 05 0.91 0.89 L 0.09 0.11 W Jan 06 0.91 0.90 L 0.09 0.10 W Average 0.83 0.17 0.17 0.83 Average All 0.56 0.44 0.44 0.56 44
  45. 45. TABLE 10 Markov Switching Analysis Regime Probabilities and Durations: 1 January 2000 to 28 February 2006 AIFRS Disclosure Regime Number of Average Average Winners / Period Observations Probability Duration Losers 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 45
  46. 46. FIGURE 1 Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 300 0.030 0.020 0.010 Average CAAR Losers Winners 0.000 0 1 2 3 4 5 6 7 8 9 10 11 12 16 -9 -8 -7 -6 -4 -3 -2 -1 - 13 14 15 17 18 19 20 -5 -1 -0.010 -0.020 Trading Day Since Event FIGURE 2 Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 1-50 (Large Firms) 0.01 0 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 -0.01 Average CAAR -0.02 Losers Winners -0.03 -0.04 -0.05 Trading Days Since Event 46
  47. 47. FIGURE 3 Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 51-100 (Medium Firms) 0.06 0.05 0.04 0.03 0.02 Average CAAR Losers Winners 0.01 0 -10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 -0.01 -0.02 -0.03 Trading Days Since Event FIGURE 4 Short Window Cumulative Average Abnormal Returns for the 30 Trading Days Surrounding the Event – ASX 101-300 (Small Firms) 0.030 0.020 0.010 Average CAAR 0.000 Losers Winners 0 1 2 3 4 6 7 8 9 11 16 -9 -8 -7 -6 -5 -4 -3 -1 5 10 12 13 14 15 17 18 19 20 -2 - -1 -0.010 -0.020 -0.030 Trading Days Since Event 47
  48. 48. FIGURE 5 Intermediate Window Cumulative Average Abnormal Returns for the Twenty-One Weeks (105 Trading Days) following the Event 0.03 0.02 0.01 0.00 59 19 29 39 49 69 79 89 99 -1 CAAR 9 Average Losers Winners -0.01 -0.02 -0.03 -0.04 Trading Days Since Event FIGURE 6 Scatter Diagram: AIFRS NPAT 30 June 2005 Reconciliations and Market-Adjusted Returns 0.15 0.1 Six Day Market-Adjusted Return 0.05 0 -1.25 -1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1 1.25 -0.05 -0.1 -0.15 Aggregate AIFRS NPAT Reconciliation as a Percentage of AGAAP NPAT 48

×