Dissertations / Theses on the topic 'Corporations Australia Finance Econometric models'

Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system.
Doctor of Philosophy

Traditional financial theories see capital structure as a result of mainly financial, tax and growth factors (Modigliani & Miller, 1958). But corporate governance theories (Jensen & Meckling, 1976) and business strategy theories (Barton & Gordon, 1988) suggest that ownership structure and ownership concentration, product diversification and asset specificity may also influence capital structure. Focusing on the examination of the determinants of capital structure in Chinese listed companies, this research goes beyond financial factors and considered business strategy and corporate governance approaches, and their impact on capital structure, in a transitioning Chinese context where institutions, expertise and regulatory processes are different to, but converging on, Western approaches. A panel data set of 1,098 Chinese listed companies for the period of 1991 to 2000 was collected from published sources, and conventional and innovative econometric methodologies were used to model a range of relationships between capital structure and its financial and non-financial determinants. The statistical approaches used in this study included Ordinary Least Squares Model and also Linear Mixed Model, which is a powerful tool to examine panel data where independence of explanatory variables is not assumed. The analysis also involved Hox’s model building procedures to measure model fit. The capital structure of listed companies in both the Shenzhen Stock Exchange and the Shanghai Securities Exchange is positively related to a firm’s tax rate, growth and capital intensity and negatively related to a firm’s profit and size. Other financial factors such as tangibility, risk and duration are non-significant. The capital structure of listed companies, particularly in the Shenzhen Stock Exchange, is positively related to product diversification and negatively related to asset specificity. The capital structure of listed companies in the Shanghai Securities Exchange is positively related to government ownership and ownership concentration of the largest shareholder and negatively related to legal person ownership and ownership concentration of the ten largest shareholders. The data and modelling support financial and non-financial determinants of capital structure. In particular, information asymmetry, business diversity and asset specificity have a significant impact on capital structure. In addition the empirical work in the study supports agency cost explanations of debt and equity. Finally the research demonstrates that the two main financial markets in China, Shenzhen and Shanghai, have operated differently but are converging towards a common norm. The research contributes to the general field of capital structure and provides valuable insights into the nature of the Chinese firm and the evolution of the Chinese financial system.
Doctor of Philosophy

[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.

This study deals with the estimation of the optimal hedge ratios using various econometric models. Most of the recent papers have demonstrated that the conventional ordinary least squares (OLS) method of estimating constant hedge ratios is inappropriate, other more complicated models however seem to produce no more efficient hedge ratios. Using daily AOIs and SPI futures on the Australian market, optimal hedge ratios are calculated from four different models: the OLS regression model, the bivariate vector autoaggressive model (BVAR), the error-correction model (ECM) and the multivariate diagonal Vcc GARCH Model. The performance of each hedge ratio is then compared. The hedging effectiveness is measured in terms of ex-post and ex-ante risk-return traHe-off at various forcasting horizons. It is generally found that the GARCH time varying hedge ratios provide the greatest portfolio risk reduction, particularly for longer hedging horizons, but hey so not generate the highest portfolio return.

This research questions whether technical trading rules can help predict stock price movements for a sample of stocks selected from four equity markets from the Asia-Pacific region: Australia, Malaysia, Hong Kong and Thailand for the period 1989-2008. The research is split into two stages. Stage-1 of the research tests the predictability of technical trading rules against a buyand- hold strategy. The variable moving average (VMA), fixed moving average (FMA) and the trading range break (TRB) trading rules are applied to this research. Economic predictability of these rules is examined by comparing returns conditional on a trading rule buy (sell) signal against an unconditional buy-and-hold return. Any existence of excess returns can thus be established. This follows with a statistical analysis of returns using a traditional t-test methodology. Traditional statistical tests assume normally distributed returns with independent observations and a non-changing distribution across time. In Stage-2 of this research a bootstrap checks whether features such as non-normality, time-varying moments and serial correlation bias test statistics. The bootstrap involves assumptions regarding the underlying returns generating process (RGP) and allows returns conditional on a trading rule buy (sell) signal from the original stock price series to be compared with conditional returns simulated from four common null models: RW, AR (1), GARCH-M and E-GARCH models. Simulated p-values are calculated in conjunction with simulated distributions and are applied in lieu of the theoretical normal distribution. Given this process it is possible to infer as to whether non-linear dependencies in returns can be captured by any of the three trading rules. Given the null model output standard t-test outcomes of predictability of technical trading rules may be diminished and/or eliminated. Conclusions are drawn as to the predictability and profitability of the VMA, FMA and TRB trading rules when applied to the chosen stock samples. Findings of this research indicate returns conditional on technical trading rules exceed unconditional buy-and-hold returns for all stocks. Thai sample output indicates strong support in favour of the predictability of standard test results supporting the use of technical trading rules. Output for Australia, Hong Kong and Malaysia indicates that previous standard t-test outcomes of predictability may be diminished and/or eliminated. This implies that the underlying RGP may be characterised by underlying features of some/all of the stochastic models.

This thesis provides more precise characterisation of patterns, causes and consequences of takeover activity in Australia over three decades spanning from 1972 to 2004. The first contribution of the thesis is to characterise the time series behaviour of takeover activity. It is found that linear models do not adequately capture the structure of merger activity; a non-linear two-state Markov switching model works better. A key contribution of the thesis is, therefore, to propose an approach of combining a State-Space model with the Markov switching regime model in describing takeover activity. Experimental results based on our approach show an improvement over other existing approaches. We find four waves, one in the 1980s, two in the 1990s, and one in the 2000s, with an expected duration of each wave state of approximately two years. The second contribution is an investigation of the extent to which financial and macro-economic factors predict takeover activity after controlling for the probability of takeover waves. A main finding is that while stock market boom periods are empirically associated with takeover waves, the underlying driver is interest rate level. A low interest rate environment is associated with higher aggregate takeover activity. This relationship is consistent with Shleifer and Vishny (1992)'s liquidity argument that takeover waves are symptoms of lower cost of capital. Replicating the analysis to the biggest takeover market in the world, the US, reveals a remarkable consistency of results. In short, the Australian findings are not idiosyncratic. Finally, the implications for target and bidder firm shareholders are explored via investigation of takeover bid premiums and long-term abnormal returns separately between the wave and non-wave periods. This represents the third contribution to the literature of takeover waves. Findings reveal that target shareholders earn abnormally positive returns in takeover bids and bid premiums are slightly lower in the wave periods. Analysis of the returns to bidding firm shareholders suggests that the lower premiums earned by target shareholders in the wave periods may simply reflect lower total economic gains, at the margin, to takeovers made in the wave periods. It is found that bidding firms earn normal post-takeover returns (relative to a portfolio of firms matched in size and survival) if their bids are made in the non-wave periods. However, bidders who announce their takeover bids during the wave periods exhibit significant under-performance. For mergers that took place within waves, there is no difference in bid premiums and nor is there a difference in the long-run returns of bidders involved in the first half and second half of the waves. We find that none of theories of merger waves (managerial, mis-valuation and neoclassical) can fully account for the Australian takeover waves and their effects. Instead, our results suggest that a combination of these theories may provide better explanation. Given that normal returns are observed for acquiring firms, taken as a whole, we are more likely to uphold the neoclassical argument for merger activity. However, the evidence is not entirely consistent with neo-classical rational models, the under-performance effect during the wave states is consistent with the herding behaviour by firms.

Choi Tsz Wang.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.
Includes bibliographical references (leaves 43-45).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Review of Structural Models --- p.5
Chapter 2.1 --- The Merton model --- p.5
Chapter 2.2 --- The default barrier model of Black and Cox --- p.7
Chapter 3 --- Estimating the Merton model --- p.10
Chapter 3.1 --- The Variance Restriction (VR) method --- p.10
Chapter 3.2 --- The Maximum Likelihood estimation (ML) method --- p.12
Chapter 3.3 --- Comparison between VR and ML methods --- p.13
Chapter 4 --- Implications of Using the Proxy in Default Barrier Estimation --- p.15
Chapter 4.1 --- Rejection of SC framework --- p.16
Chapter 4.2 --- Positive barrier implication --- p.17
Chapter 4.3 --- Barier over debt implication --- p.17
Chapter 4.4 --- Numerical illustration --- p.19
Chapter 5 --- The Proposed Framework --- p.22
Chapter 5.1 --- Maximum likelihood estimation --- p.23
Chapter 5.2 --- Barrier-to-debt ratio specification --- p.25
Chapter 5.3 --- Simulation checks --- p.26
Chapter 5.4 --- Comments on the performance of α --- p.29
Chapter 6 --- Estimation with Empirical Data --- p.33
Chapter 6.1 --- Description of data --- p.33
Chapter 6.2 --- Empirical results --- p.35
Chapter 7 --- Conclusion --- p.41
References --- p.43

Australia may present a special case in the analysis of strikes because, for most of the Twentieth Century, the Australian Industrial Relations Commission has acted as an industrial "umpire" charged with keeping the industrial peace. We begin with a review of major contributions to the theory of strikes, and reestimations and evaluations of the time-series models of previous Australian researchers. We then develop theoretical models of strikes and non-strike industrial action, stemming from Marshall's (1920) contribution to the theory of wages. If higher real wages lead to lower levels of employment, union demands are likely to be greater, and industrial action more frequent, when the duration of unemployment of retrenched workers is shorter. Important determinants of the opportunity costs of wage demands to employees, are wage losses of retrenched employees during unemployment and in subsequent re-employment. Critical in the union's decision to threaten a strike or a non-strike action, is a permanent loss of market share directly associated with strikes. The model of strikes is tested, along with variables suggested by other theories, using time-series data from the period 3:1959 to 4:1992. We show that the model is robust and out-performs modified versions of other Australian models. We find that the Prices and Incomes Accord is associated with a reduction in strike activity, but that other researchers have over-estimated its impact. Australian Workplace Industrial Relations Survey data is used to produce cross-sectional models of strikes and non-strike actions in unionised workplaces. We test the importance of the opportunity costs of wage demands and strikes, using variables describing the firm's competitive environment and local labour market conditions. Because the objectives of workplaces differ, we estimate separate models for privately owned workplaces, government non-commercial establishments and government business enterprises. All empirical models are broadly consistent with the predictions of our theoretical model.

The Australian Trade Deficit (TD) has been increasing in the past 50 years, and this deficit has become more significant in the last few decades. This rising TD level in Australia has brought the national debt level to a new height, making this country one of the world‟s highest debt-ridden countries. The most alarming fact associated with these trends is that Australia‟s ability to service the increasing debt levels in the future has been diminishing since the increasing debt levels in Australia have been predominantly used for Consumption (C) rather than for gross capital formation. The diminishing ability to service the increasing debt levels in Australia is due to the fact that the TD level is increasing as a proportion of the Australian Gross Domestic Product (GDP), while the Australian gross capital formation as a proportion of the Australian debt is one of the lowest amongst the major debtor countries in the world.

Using 1980 - 2012 annual data, the study empirically investigates the dynamic relationship between financial development and economic growth in three developing countries (South Africa, Brazil and Kenya) and three developed countries (United States of America, United Kingdom and Australia). The study was motivated by the current debate regarding the role of financial development in the economic growth process, and their causal relationship. The debate centres on whether financial development impacts positively or negatively on economic growth and whether it Granger-causes economic growth or vice versa. To this end, two models have been used. In Model 1 the impact of bank- and market-based financial development on economic growth is examined, while in Model 2 it is the causality between the two that is explored. Using the autoregressive distributed lag (ARDL) bounds testing approach to cointegration and error-correction based causality test, the results were found to differ from country to country and over time. These results were also found to be sensitive to the financial development proxy used. Based on Model 1, the study found that the impact of bank-based financial development on economic growth is positive in South Africa and the USA, but negative in the U.K – and neither positive nor negative in Kenya. Elsewhere the results were inconclusive. Market-based financial development was found to impact positively in Kenya, USA and the UK but not in the remaining countries. Based on Model 2, the study found that bank-based financial development Granger-causes economic growth in the UK, while in Brazil they Granger-cause each other. However, in South Africa, Kenya and USA no causal relationship was found. In Australia the results were inconclusive. The study also found that in the short run, market-based financial development Granger-causes economic growth in the USA but that in South Africa and Brazil, the reverse applies. On the other hand bidirectional causality was found to prevail in Kenya in the same period.
Economics
DCOM (Economics)