Investigatino The Relationship Beween Maret Values And Accounting Numbers For 30 Selected Australia Listed Companies

Investigating the Relationship between Market Values and Accounting Numbers for 30 Selected Australian Listed Companies Victoria Jane Clout B Business (Hons.) (Queensland University of Technology) A dissertation submitted for the degree of Doctor of Philosophy within the School of Accountancy, Faculty of Business, Queensland University of Technology April 2007 Investigating the Relationship between Market Values and Accounting Numbers for 30 Australian Listed Companies ABSTRACT In capital market research (CMR) studies of the value relevance of accounting numbers are founded upon the concept that, in equilibrium, the book values are equal to or have some long-term relationship with the market value and that market returns are related to book returns This thesis seeks to resolve a gap in the CMR by examining 30 selected individual firms listed on the Australian stock market during the period 1950 to 2004, using equilibrium correction modelling techniques Even these limited prior works used cross-sectional techniques rather than the long-run, time-series, analysis used in this study Moreover, dynamic analysis in the CMR has tended to focus on indexes or portfolio data rather than using firmspecific case study data of the type modelled here No prior research has taken this approach using Australian data The results of this thesis indicated that an equilibrium correction relationship between market values and book values for firms listed on the Australian Stock Exchange (ASX) could be determined by using accounting and macroeconomic regressors The findings of the thesis were consistent with the literature in terms of the variables suggested and important in the firm’s valuation from the three main approaches, the analysts (industry) approach, the finance and accounting theory (textbook) approach and the CMR literature approach The earnings, dividends and book value variables are significant in their relationships with the firm’s market values The models constructed were typically more informative and had an increased forecasting performance compared with the a priori models tested, based on theory and the literature Keywords Capital market research; Value Relevance; Dynamic Modelling Equilibrium correction; Error correction models; Forecasting; Sufficiency ii iii Contents Chapter Introduction 1.1 Purpose of the study 1.2 Relationship to prior research 1.3 Motivation 1.4 Research question 1.5 Significance of the study 1.6 Outline of thesis Chapter Literature review 2.1 Introduction 11 2.2 Financial analyst’s approach 11 2.3 Finance and accounting theory (textbook) approaches 13 2.4 Capital market approaches 21 2.4.1 22 2.5 Cross-sectional studies – fundamental analysis 2.4.2 Earnings 24 2.4.3 Book value 26 2.4.4 Combined role of book value and earnings 27 2.4.5 Time series studies 28 2.4.6 Gaps in current CMR literature 29 Summary 33 Chapter Theoretical framework 3.1 Introduction 35 3.2 Issues emanating from current CMR 36 3.3 Variable identification 37 3.4 Functional form 38 3.5 Dynamic specification 38 3.6 Replication for benchmarking 40 iv 3.7 Benchmarking in final ‘best’ model selection 40 3.8 Economic theory at the foundational level of CMR 42 3.9 Examination of results in firm specific context 43 3.10 The sufficiency of accounting numbers for market value 44 3.11 Framework 44 3.12 Summary 45 Chapter Research methods 4.1 Introduction 46 4.2 Selected sample of 30 firms 47 4.2.1 Criteria for the selection of firms 47 Variable definitions 53 4.3.1 The dependent variables 53 4.3.2 Independent variables 58 4.4 Currency 65 4.5 Testing down procedure for the statistical models 67 4.5.1 General-to-specific approach 67 4.3 4.5.2 Testing for co-integration using an equilibrium correction model (ECM) 68 4.6 Benchmarking of models and procedure for the selection of the ‘best’ model for each firm 70 4.6.1 Benchmarking of models 70 4.6.2 Procedure for the selection of the ‘best’ model for each firm 73 4.7 Diagnostic tests 74 4.8 Summary 76 v Chapter Results 5.1 Introduction 77 5.2 Descriptive statistics 78 5.3 Levels of integration of the variables 85 5.3.1 ACF graphical analysis 85 5.3.2 ADF statistical evidence 91 Results at the untransformed (raw) level 97 5.4 5.4.1 Statistical equilibrium correction models for all 30 firms 5.4.2 Rationale for discontinuing untransformed (raw) level to the next phase 5.5 97 Results at the logged level for each of the 30 firms 105 107 5.5.1 Statistical equilibrium correction models for all 30 firms 5.5.2 Benchmark results 107 114 5.3.3 Summary of the ‘best’ models phase for the 30 firms selected in the benchmarking 116 5.5.4 Graphical analysis of model performance and model recursives for the ’best’ models 5.6 5.7 5.8 123 Comparison of the untransformed and log-transformed results 126 Events during the study period identified 127 5.7.1 Market value events 127 5.7.2 Book value events 130 5.7.3 Earnings events 132 5.7.4 Dividend events 134 5.7.5 Macro-economic events 136 Summary 138 vi Chapter Discussion and analysis 6.1 Introduction 139 6.2 Overall results for the entire sample of 30 firms 139 6.3 Analysis of the five selected firms ‘best’ models 140 6.3.1 Statistical model example - Burns, Philp & Co Ltd 140 6.3.2 Real statistical model example - Southcorp Ltd 144 6.3.3 Random walk with trend model example Permanent Trustee Co Ltd 6.3.4 6.3.5 Earnings capitalisation model example Australian Gas Light Co Ltd 149 Ohlson-type model example - Coles Myer Ltd 151 6.3.6 Summary of discussion 6.4 147 154 Comparative analysis of firms with non-statistical ‘best’ models 156 6.4.1 The Australian Gas Light Company 156 6.4.2 Angus & Coote (Holdings) Ltd 157 6.4.3 Argo Investments Ltd 158 6.4.4 Coles Myer Ltd 159 6.4.5 Campbell Brothers Ltd 160 6.4.6 Harris Scarfe Holdings Ltd 161 6.4.7 DJL Ltd 162 6.4.8 MIM Holdings Ltd 162 6.4.9 The National Australia Bank 163 6.4.10 Permanent Trustee Co Ltd 164 6.4.11 Smith (Howard) Ltd 165 6.4.12 Southcorp Ltd 166 6.4.13 WMC Limited 166 6.4.14 Woodside Petroleum Ltd 167 6.4.15 Summary 168 vii 6.5 Analysis of the consistency, value relevance and sufficiency of the 30 companies 168 6.5.1 Consistency 168 6.5.2 Value relevance 172 6.5.3 Sufficiency 173 6.5.4 Ranking 176 6.6 Discussion of overall findings 180 6.7 Comparison of results with literature 182 6.7.1 Analyst approaches to valuation 182 6.7.2 Finance textbook approaches to valuation 185 6.7.3 Accounting textbook approaches to valuation 187 6.8 6.7.4 Capital market approaches 192 Summary 196 Chapter Conclusions 7.1 Introduction 199 7.2 Summary of thesis 200 7.3 Main findings 201 7.4 Limitations and future research 206 References 208 Appendix A – Standard procedure 228 Appendix B – Accounting & market value and data levels of integration 232 Appendix C – Benchmarking results for all 30 selected firms 293 viii Appendix D – Results used untransformed (raw) data – change in market value as the dependent variable (estimated for 4-year holdout forecasting period) 323 Appendix E – The ‘best’ model performance and recursive graphics for all 30 firms – based a 10 year hold out forecasting period 354 Appendix F - companies with alterative models to the statistical model selected as ‘best’ comparative figures 385 ix List of Tables Table 4.1 Number of companies on the Sydney Stock Exchange Official List as at December 31, 1945-1962 48 Table 4.2 Selected sample of 30 firms 50 Table 4.3 Market sector representation for the sample of 30 firms 51 Table 4.4 Exact periods raw share price obtained from the CRIF AGSM Annual Report Record (ARR) database (from the master dataset held at the CRIF AGSM) 55 Table 4.5 Australian Foundation Investment Company Ltd raw share price collection source information 56 Table 4.6 Exact sources of raw share price for the 30 firms 57 Table 4.7 Exact periods accounting numbers obtained from the CRIF AGSM Annual Report Record (ARR) database (from the master dataset held at the CRIF AGSM) 61 Table 4.8 Australian Foundation Investment Company Ltd accounting number sources 65 Table 4.9 Example of currency conversion for Australian Foundation Investment Co Ltd 66 Table 4.10 Models constructed 74 Table 4.11 Diagnostic tests and RMSE 79 Table 5.1-1 Descriptive statistics of financial data for the 30 firms – firms AFI to FHF 80 Table 5.1-2 Descriptive statistics of financial data for the 30 firms – firms GOW to STO 81 Table 5.1-3 Descriptive statistics of financial data for the 30 firms – firms TTH to WPL 82 Table 5.2 Descriptive statistics for macro-economic variables (1950 to 2004) 83 Table 5.3 Summary of interpretations of correlograms for the thirty firms 88 Table 5.3-1 Augmented Dickey Fuller (ADF) tests on individual firms – AFI to CSR (tested with a trend and a constant and at the first lag level) 94 x PANEL C: Real Statistical Model (Model 3) Real Return Fitted 0.0 -0.5 -1.0 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 0.4 1-step Forecasts Real Return 0.2 0.0 -0.2 1994 1995 1996 1997 1998 1999 2000 2001 399 M.I.M HOLDINGS LTD (MIM) PANEL A: Statistical Model (Model 1) 0.5 Raw Return Fitted 0.0 -0.5 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Raw Return 0.5 0.0 -0.5 1997 1998 1999 2000 2001 2002 2003 2004 PANEL B: Forecasting Model (Model 2) 0.5 Raw Return Fitted 0.0 -0.5 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Raw Return 0.5 0.0 -0.5 1997 1998 1999 2000 2001 2002 2003 2004 400 PANEL C: Real Statistical Model (Model 3) 0.5 Real return Fitted 0.0 -0.5 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Real return 0.5 0.0 -0.5 1997 1998 1999 2000 2001 2002 2003 2004 401 NATIONAL AUSTRALIA BANK (NAB) PANEL A: Statistical Model (Model 1) Raw Return Fitted 1.0 0.5 0.0 -0.5 1950 0.75 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 2005 Raw Return 0.50 0.25 0.00 -0.25 1999 2000 2001 2002 2003 2004 2005 2006 PANEL B: Forecasting Model (Model 2) Raw Return Fitted 1.0 0.5 0.0 -0.5 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 2005 Raw Return 0.5 0.0 1999 2000 2001 2002 2003 2004 2005 2006 402 PANEL C: Ohlson-type Model (Model 9) Raw Return Fitted 1.0 0.5 0.0 -0.5 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 2005 Raw Return 0.5 0.0 -0.5 1999 2000 2001 2002 2003 2004 2005 2006 403 PERMANENT TRUSTEE CO LTD (PMT) PANEL A: Statistical Model (Model 1) Raw return Fitted 0.50 0.25 0.00 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Raw return 0.2 0.0 -0.2 1997 1998 1999 2000 2001 2002 2003 2004 PANEL B: Forecasting Model (Model 2) Raw return Fitted 0.50 0.25 0.00 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Raw return 0.25 0.00 -0.25 1997 1998 1999 2000 2001 2002 2003 2004 404 PANEL C: Random Walk with Trend (Model 5) Raw return Fitted 0.50 0.25 0.00 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Raw return 0.2 0.0 -0.2 1997 1998 1999 2000 2001 2002 2003 2004 405 SMITH (HOWARD) LTD (SMI) PANEL A: Statistical Model (Model 1) 0.75 Raw Return Fitted 0.50 0.25 0.00 -0.25 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 1.0 1-step Forecasts Raw Return 0.5 0.0 1996 1997 1998 1999 2000 2001 2002 2003 PANEL B: Forecasting Model (Model 2) 0.75 Raw Return Fitted 0.50 0.25 0.00 -0.25 1950 0.75 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Raw Return 0.50 0.25 0.00 -0.25 1996 1997 1998 1999 2000 2001 2002 2003 406 PANEL C: Real Statistical Model (Model 3) 0.50 Real return Fitted 0.25 0.00 -0.25 -0.50 1950 0.75 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 Real return 0.50 0.25 0.00 -0.25 1996 1997 1998 1999 2000 2001 2002 2003 407 SOUTHCORP LTD (SRP) PANEL A: Statistical Model (Model 1) 0.50 Raw Return Fitted 0.25 0.00 -0.25 1950 0.50 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 2005 Raw Return 0.25 0.00 -0.25 1999 2000 2001 2002 2003 2004 2005 2006 PANEL B: Forecasting Model (Model 2) 0.50 Raw Return Fitted 0.25 0.00 -0.25 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 0.50 1-step Forecasts Raw Return 0.25 0.00 -0.25 1999 2000 2001 2002 2003 2004 2005 2006 408 PANEL C: Real Statistical Model (Model 3) Real return Fitted 0.25 0.00 -0.25 -0.50 1950 1955 1960 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 2005 Real return 0.25 0.00 -0.25 -0.50 1999 2000 2001 2002 2003 2004 2005 2006 409 W.M.C LIMITED (now Alumina Limited AWC) (WMC) PANEL A: Statistical Model (Model 1) Raw return Fitted -1 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 1-step Forecasts Raw return -1 -2 1999 2000 2001 2002 2003 2004 2005 2006 PANEL B: Forecasting Model (Model 2) 1.5 Raw return Fitted 1.0 0.5 0.0 -0.5 1950 1955 1960 1.0 1-step Forecasts 1965 1970 1975 1980 1985 1990 1995 2000 2005 Raw return 0.5 0.0 -0.5 -1.0 1999 2000 2001 2002 2003 2004 2005 2006 410 PANEL C: Real Statistical Model (Model 3) Real Return Fitted -1 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 1-step Forecasts Real Return -1 -2 1999 2000 2001 2002 2003 2004 2005 2006 411 WOODSIDE PETROLEUM LTD (WPL) PANEL A: Statistical Model (Model 1) 1.0 Raw return Fitted 0.5 0.0 -0.5 1955 1.5 1960 1965 1-step Forecasts 1970 1975 1980 1985 1990 1995 2000 2005 Raw return 1.0 0.5 0.0 1999 2000 2001 2002 2003 2004 2005 2006 PANEL B: Forecasting Model (Model 2) 1.0 Raw return Fitted 0.5 0.0 -0.5 1955 1960 1965 1.5 1-step Forecasts 1970 1975 1980 1985 1990 1995 2000 2005 Raw return 1.0 0.5 0.0 1999 2000 2001 2002 2003 2004 2005 2006 412 PANEL C: Random Walk with Trend (Model 5) 1.0 Raw return Fitted 0.5 0.0 -0.5 1955 1960 1965 1-step Forecasts 1970 1975 1980 1985 1990 1995 2000 2005 Raw return 0.5 0.0 -0.5 1999 2000 2001 2002 2003 2004 2005 2006 413