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No / This paper investigates the dynamics of R&D and capital investment using a large sample of US firms during the period 2002–2016. A partial adjustment approach is employed with a specific focus on the impact of the financial crisis on target adjustment speed. Evidence suggests that firms have a target in both types of investment and adjust to it at varying speeds. Specifically, firms adjusted to the capital investment target faster than to R&D investment. However, firms increased the adjustment speed in R&D investment significantly during the crisis, and it has remained at similar levels during the post-crisis period. The changes in adjustment speeds can be explained by several firm-specific characteristics that are related to the ability of firms to raise internal finance.

This research contains three essays that explore the speed of adjustment, volatility and noise in the Indonesia Stock Exchange. The first essay explores the speed of adjustment in the Indonesia Stock Exchange at daily interval from 2000 to 2004. The model employed is the speed of adjustment with noise. Firstly, I work on the estimation of the speed of adjustment. The estimated speed of adjustment coefficient concludes that the large size leads the smaller size group to adjust to new information. Secondly, I analyse the component in the noise that contributes significantly to the speed of adjustment level. It is confirmed that the factor determining the noise is bid-ask fluctuations. Therefore, it is reasonable to infer the component in the noise from bid-ask component. The decomposition of bid-ask spread into transaction cost and asymmetric information reveals that the latter is found to be a significant component determining the speed of adjustment level. The second essay analyses the fine grain dynamics of the speed of price adjustment to new information from 2000 to 2007. The exact time of adjustment is estimated at intraday frequency instead of at daily frequency. In this work, as an alternative of first moment estimation, second moment model-free estimation using volatility signature plot to estimate of the speed of adjustment is proposed. Both first and second moment estimation of the speed of adjustment provide consistent result of 30 minute adjustment period. Negative relation after 5-minute return interval between speed of adjustment estimate and realized variance is found implying lower noise leads to smaller deviation between observed and equilibrium price. In the third essay, I concentrate the work on the second moment of continuously compounded returns from 2000 to 2007 in the Indonesia Stock Exchange. The main purpose of the last essay is to estimate the noise and efficient variance in the Indonesia Stock Exchange. The realized variance based estimator is employed in the third essay. During the period of the study, noise variance decreases indicating smaller deviation between the observed and equilibrium price, hence improving market quality in the Indonesia Stock Exchange. The optimal frequency to estimate the efficient variance, on average, is nine minutes. The variance ratio of daily efficient variance to daily open-to-close reveals significant private information underlying price process in the Indonesia Stock Exchange.

This thesis examines three aspects of capital structure of manufacturing, mining and retail firms listed on Johannesburg Securities Exchange (JSE). Firstly, it tests for the validity of the pecking order, the static trade-off and the dynamic trade-off theories in the context of South African manufacturing, mining and retail firms. The study used data from 42 manufacturing, 24 mining and 21 retail firms with complete data for four or more consecutive years during 2000-2010 (panel 1) to test the validity of these theories. The research hypotheses were formulated and tested using generalised least squares (GLS) random effects, maximum likelihood (ML) random effects, fixed effects, Prais-Winsten regression, Arellano and Bond, Blundell and Bond and the random effects Tobit models. Secondly, the thesis examines the impact of the firm’s key financial performance variables on firm leverage and speed of target adjustment. A panel of 49 manufacturing, 24 mining and 23 retail firms with complete data for two or more consecutive years during the period 2005-2010 (panel 2) was constructed and used in this test. The research hypotheses were formulated and tested using the same regression models used in panel 1. Lastly, the thesis examines the existence of the discounted value premium in manufacturing, mining and retail firms listed on the JSE. This study was done using panel of 47 manufacturing, 31 mining and 20 retail firms with complete data for four or more consecutive years during the period 2006-2010. A simple t-test was used to evaluate the significance of the sample’s discounted value premium. The study documents that firm growth rate, non-debt tax shields, financial distress, profitability, capital expenditure, asset tangibility, price earnings, ordinary share prices and changes in working capital were significant predictors of firm leverage. Dividend paid, capital expenditure, firm growth rate, profitability, cash flow from operations and economic value added were positively correlated to leverage. Asset tangibility, firm profitability, non-debt tax shields, financial distress, liquidity, price earnings, share price and retention rate were negatively correlated to leverage. Asset tangibility, financial distress, firm growth, non-debt tax shields, and long-term debt repaid were negatively correlated to changes in debt issued, whilst profitability, actual dividend paid, capital expenditure and changes in working capital were positively correlated. These results confirm the complementary nature of the trade-off and pecking order theories. Furthermore, the firms had positive and significant speeds of adjustment. In panel 1, the true speed of adjustment for the sample was 57.64% (0.81 years) for book-to-debt ratio (BDR) and 42.44% (1.25 years) for market-to-debt (MDR). The speed for manufacturing firms was 45.08% (1.16 years) for BDR and 44.59% (1.17 years) for MDR; for mining firms, 72.07% (0.54 years) for BDR and 56.45% (0.83 years) for MDR; and for retail firms, 28.42% (2.07 years) for BDR and 42.48% (1.25 years) for MDR. In panel 2, the true speed of adjustment for the sample was 64.20% for book-to-debt ratio (BDR) and 28.11% for market-to-debt ratio (MDR). The true speed for manufacturing firms was 34.42% for BDR and 30.56% for MDR; for mining firms, 69.59% for BDR and 45.77% for MDR; and for retail firms, 9.34% for BDR. These results confirm the validity of the dynamic trade-off theory. Finally, manufacturing, mining and retail firms had a positive discounted value premium. This ranged from 5.16% to 9.48% (on perpetual growth), with mining firms having the largest (9.48%), followed by manufacturing (8.54%) and retail firms (5.16%). Of the observations for the full sample, 92.23% showed a positive discounted value premium. This evidence on the speed of adjustment and discounted value premium suggests the existence of a target capital structure different from the theoretical optimal capital structure hypothesised by the static trade-off theory. / Thesis (PhD)--University of Pretoria, 2013. / Financial Management / unrestricted

This thesis examines the link between mergers and acquisitions (M&As) and corporate financial leverage. The thesis proposes and tests various hypotheses regarding: (1) the relationship between the probability of firms undertaking M&As and corporate financial leverage; and (2) the changes in financial leverage prior to firms' decision to initiate M&As. The empirical evidence on the proposed hypotheses is based on a large sample of firms in the UK during the period 1996 and 2006. The empirical analysis presented in this study contributes to the large and growing body of literature on the interdependence of corporate financing and investment decisions. Specifically, this study contributes to the literature in two ways. First, the thesis investigates the link between firms leverage deviations (i.e. the deviations of firms observed leverage ratios from target leverage ratios) and the probability of undertaking M&As in the future. Building upon the earlier literature, it is argued that extreme leverage deviations lower the probability of undertaking M&As by impairing firms ability to raise capital to finance these deals. The study s empirical analyses suggest that extremely overleveraged firms have lower probability of undertaking M&As. Moreover, the link between extreme overleverage and the probability of undertaking M&As is weaker for diversification-increasing acquisitions (i.e. deals in which the acquirer and the target firm operate in different industries); for domestic acquisitions (i.e. deals in which the acquirer and the target firm are domiciled in the same country); and for focused (i.e. single-segment) firms undertaking acquisitions. Thus, the leverage deviation effect is not symmetric for all types of acquisitions and for all firms. Second, the thesis examines how the pre-acquisition changes in corporate financial leverage may be influenced by: (1) the extent to which firms deviate from their target leverage ratios; and (2) firms intentions to initiate M&As. Key empirical findings in this section suggest that firms that have higher leverage deviations adjust their leverage at a higher rate than those with lower deviations. More importantly, the empirical evidence suggests that firms that undertake M&As adjust their pre-acquisition leverage at a higher rate than those that do not. These findings suggest that, when making adjustments to corporate capital structure, managers tend to consider their firms leverage deviations and their future acquisition plans. Furthermore, the study s findings partly explain the differences in the speeds of financial leverage adjustments reported in the existing literature.

As conclusões das pesquisas sobre velocidade de ajustamento da estrutura de capital em direção ao alvo (SOA - Speed Of Adjustment) são muito divergentes quanto à velocidade medida. A maioria dos estudos mensura o SOA sem levar em conta certas especificidades das empresas ou de suas estratégias. Dividindo-se a amostra em empresas não adquirentes, adquirentes eventuais e adquirentes em série, o presente estudo tem por objetivo investigar o padrão de comportamento do SOA no período entre 1990 e 2010 para empresas norte-americanas. Considerando diversas variáveis de controle (restrições financeiras, oportunidades de crescimento, grau de alavancagem financeira e emissão/redução de dívidas e ações), tem-se uma investigação mais aprofundada de como as empresas não adquirentes, adquirentes eventuais e adquirentes em série ajustam sua estrutura de capital em direção ao alvo. São utilizadas como variáveis dependentes o endividamento a valor de mercado e endividamento líquido a valor de mercado. Verificou-se que os endividamentos médios para as três amostras são diferentes entre si, de forma estatisticamente significante. As empresas adquirentes em série possuem o menor endividamento, ao passo que as empresas não adquirentes são as mais endividadas, estando as empresas adquirentes eventuais em posição intermediária quanto ao endividamento. Este resultado sugere que as empresas possuem padrões de endividamentos distintos em função de sua política de investimentos relacionada à aquisições. É utilizado o modelo de ajustamento parcial para mensurar o SOA, empregando painel de dados dinâmico com a técnica do Método dos Momentos Generalizados (GMM) Sistêmico para se medir a velocidade de ajustamento da estrutura de capital de um período a outro. Esta técnica tem-se mostrado a menos enviesada e, assim, tem sido uma das mais utilizadas em trabalhos empíricos. Os resultados encontrados evidenciam que o padrão de comportamento do SOA pode depender da sua estratégia de investimentos em aquisições. O SOA das empresas adquirentes em série é constantemente menor em comparação ao SOA das empresas adquirentes, mesmo considerando as diversas variáveis de controle. O SOA das empresas não adquirentes permanece em posição intermediária. Esses resultados em conjunto sugerem que a folga financeira (baixo nível de endividamento e elevado saldo de caixa) seja um fator relevante para as adquirentes em série. Desse modo, tais empresas ajustam seu endividamento de forma mais lenta, em resposta a uma estrutura de capital mais adequada à sua política de investimentos. Por outro lado, as empresas adquirentes eventuais ajustam mais rapidamente sua estrutura de capital em função de sua política de aquisições esporádicas. / The conclusions of surveys on speed of adjustment (SOA) towards the target capital structure are widely divergent as regards the measured speed. Most studies measure the SOA without taking into account certain specificities of the companies or of their strategies. Dividing the sample in non-acquiring companies, sporadic acquiring companies and serial acquirers, this study seeks to investigate the pattern of behavior of the SOA, in the period between 1990 and 2010 for North American companies. Considering several control variables (financial restrictions, growth opportunities, degree of financial leverage and issuance/reduction of debts and shares), we have a more in-depth investigation into how non-acquiring companies, sporadic acquiring companies and serial acquirers adjust their capital structure towards the target. Market leverage value and net market leverage are used as dependent variables. It was verified that the average debt levels for the three samples are different from one another, in a statistically significant manner. The serial acquirers have the lowest leverage, while non-acquiring companies have the highest leverage, with acquirers companies in an intermediate position on the leverage. This result suggests that companies have different debts patterns, due to its investment policy related to acquisitions. The partial adjustment model is employed to measure the SOA, using dynamic panel data with the Generalized Method of Moments (GMM) Systemic to measure the speed of adjustment of the capital structure from one period to another. This technique has shown itself to be less biased and has thus been one of the most commonly used techniques in empirical studies. The results show evidence that the SOA may depend of its investment strategy. The SOA of serial acquirers companies is constantly lower than the SOA of acquiring companies, even considering all the control variables. The SOA of non-acquiring companies remains in an intermediate position. Taken together, these results suggest that the financial slack (low debt and high cash balance) is a relevant factor to serial acquirers. Thus such companies adjust their debt more slowly in response to a more adequate capital structure to their investment policy. On the other hand, sporadic acquiring companies adjust faster its capital structure, due to its sporadic acquisition policy.

No description available.

Cette thèse a pour objectif de prendre part à la réflexion sur le risque systémique et ses conséquences négatives sur l’économie réelle, et au débat sur la mise en place d’une règlementation macro-prudentielle (effets systémiques) efficace pour l’industrie bancaire en visant la stabilité financière. Pour cela, ce travail contribue à la littérature existante à travers plusieurs aspects. Dans le premier chapitre de cette thèse, sur un échantillon de banques de l’OCDE, nous étudions la manière dont la valeur de la franchise affecte le risque bancaire avant, pendant et après la crise financière mondiale de 2007–2008, en utilisant des mesures de risque individuelles et systémiques. Nous réétudions l’hypothèse de la valeur de la franchise bancaire et son rôle disciplinant au regard de la prise de risque et de l’expansion au risque systémique avant, pendant et après la crise financière. Nous montrons qu’avant la crise, la valeur de la franchise bancaire impacte positivement la prise de risque et le risque systémique non seulement des très grandes banques dites “too-big-too-fail” mais aussi des grandes banques européennes et américaines. Cependant, nos résultats montrent que pendant et après la crise, cet effet s’inverse. En considérant la période d’avant crise, nous allons plus loin dans nos investigations sur la relation entre la valeur de la franchise d’une part et la prise de risque et l’exposition au risque systémique d’autre part, en prenant en compte les effets des différences entre les cultures de prise de risque, la taille des banques et les stratégies bancaires. Le deuxième chapitre analyse la dynamique de la structure du capital des banques en fonction de leur niveau de capital interne ciblé et/ou externe imposé. Plus précisément, il examine plusieurs caractéristiques. (i) si les frictions du marché et les coûts d’ajustement du capital sont plus considérables lorsqu’il s’agit d’ajuster les ratios de fonds propres réglementaires par rapport à un ratio de levier simple. (ii) les mécanismes d’ajustement utilisés par les banques pour ajuster leur ratio de capital. (iii) comment la vitesse d’ajustement et les mécanismes d’ajustement diffèrent entre les grandes banques systémiques et complexes d’une part, et les banques moins systémiques d’autre part. Les résultats suggèrent que les banques sont plus flexibles et plus rapides dans l’ajustement de leur ratio de levier que dans l’ajustement de leurs ratios de capital réglementaire. Tandis que les banques d’importance systémique (SIFI) sont moins réactives que les autres banques dans l’ajustement de leur ratio de levier cible, elles sont néanmoins plus rapides à atteindre leurs ratios réglementaires cibles. D’autres investigations montrent que les SIFIs pourraient être plus réticentes à modifier leur base de capital en émettant ou en rachetant des actions et préfèrent une réduction plus importante ou une expansion plus rapide de leur taille. Dans le dernier chapitre, nous analysons comment la structure organisationnelle internationale et l’expansion géographique de 105 banques européennes cotées qui ont des filiales à travers le monde, pourrait affecter leur importance systémique au cours de la période 2005–2013. Nous examinons également comment le pic de la crise financière mondiale de 2008–2009 et l’ampleur de la crise de la dette souveraine européenne de 2010–2011 pourraient avoir affecté ces relations. Nous montrons que l’internationalisation et la complexité organisationnelle sont des facteurs importants du risque systémique bancaire, en particulier pendant les années de stress financier 2008–2013. / The aim of this thesis is to contribute on the current debate on the systemic risk and its policy implications for the implementation of new (systemic risk-based) capital requirements in the banking industry. We extend the existing literature in many aspects. In the first chapter, we investigate how bank charter value affects risk for a sample of OECD banks by using standalone and systemic risk measures before, during, and after the global financial crisis of 2007–2008. We revisit the self‐discipline role of charter value on bank’s risk-taking and systemic risk prior, during and after the crisis. We show that bank charter value is positively associated with risk-taking and systemic risk for very large “too-big-too-fail” banks and large U.S. and European banks prior to the crisis, but such a relationship is inverted during and after the crisis. Then, we deepen investigation on this relation between charter value and risk-taking and systemic risk prior to the crisis, regarding differences in risk taking cultures, bank size and bank strategies. The second chapter analyzes the dynamics of banks’ capital structure towards their desired and/or imposed capital level. It analyzes several interesting features. (i) whether or not market frictions and capital adjustment costs are larger for regulatory capital ratios vis-à-vis a plain leverage ratio. (ii) which adjustment channels banks use to adjust their capital ratio. (iii) how the speed of adjustment and adjustment channels differ between large, systemic and complex banks versus small banks. Findings suggest that banks are more flexible and faster in adjusting to their leverage capital ratio than to regulatory capital ratios. Whereas, systemically important banks are slower than other banks in adjusting to their target leverage ratio but quicker in reaching their target regulatory ratios. Further explores show that SIFIs might be more reluctant to change their capital base by either issuing or repurchasing equity and prefer sharper downsizing or faster expansion. In the third chapter, we analyze how the international organization structure and the geographic expansion, of 105 European listed banks that have foreign affiliates around the world, could affect bank level measures of systemic risk during the 2005–2013 period. We also investigate how the peak of the global financial crisis of 2008–2009 and the height of the European sovereign debt crisis of 2010–2011 might have affected such relationships. We find that internationalization and foreign complexity are important drivers of bank systemic risk, particularly during the 2008–2013 financial stress years.

As conclusões das pesquisas sobre velocidade de ajustamento da estrutura de capital em direção ao alvo (SOA - Speed Of Adjustment) são muito divergentes quanto à velocidade medida. A maioria dos estudos mensura o SOA sem levar em conta certas especificidades das empresas ou de suas estratégias. Dividindo-se a amostra em empresas não adquirentes, adquirentes eventuais e adquirentes em série, o presente estudo tem por objetivo investigar o padrão de comportamento do SOA no período entre 1990 e 2010 para empresas norte-americanas. Considerando diversas variáveis de controle (restrições financeiras, oportunidades de crescimento, grau de alavancagem financeira e emissão/redução de dívidas e ações), tem-se uma investigação mais aprofundada de como as empresas não adquirentes, adquirentes eventuais e adquirentes em série ajustam sua estrutura de capital em direção ao alvo. São utilizadas como variáveis dependentes o endividamento a valor de mercado e endividamento líquido a valor de mercado. Verificou-se que os endividamentos médios para as três amostras são diferentes entre si, de forma estatisticamente significante. As empresas adquirentes em série possuem o menor endividamento, ao passo que as empresas não adquirentes são as mais endividadas, estando as empresas adquirentes eventuais em posição intermediária quanto ao endividamento. Este resultado sugere que as empresas possuem padrões de endividamentos distintos em função de sua política de investimentos relacionada à aquisições. É utilizado o modelo de ajustamento parcial para mensurar o SOA, empregando painel de dados dinâmico com a técnica do Método dos Momentos Generalizados (GMM) Sistêmico para se medir a velocidade de ajustamento da estrutura de capital de um período a outro. Esta técnica tem-se mostrado a menos enviesada e, assim, tem sido uma das mais utilizadas em trabalhos empíricos. Os resultados encontrados evidenciam que o padrão de comportamento do SOA pode depender da sua estratégia de investimentos em aquisições. O SOA das empresas adquirentes em série é constantemente menor em comparação ao SOA das empresas adquirentes, mesmo considerando as diversas variáveis de controle. O SOA das empresas não adquirentes permanece em posição intermediária. Esses resultados em conjunto sugerem que a folga financeira (baixo nível de endividamento e elevado saldo de caixa) seja um fator relevante para as adquirentes em série. Desse modo, tais empresas ajustam seu endividamento de forma mais lenta, em resposta a uma estrutura de capital mais adequada à sua política de investimentos. Por outro lado, as empresas adquirentes eventuais ajustam mais rapidamente sua estrutura de capital em função de sua política de aquisições esporádicas. / The conclusions of surveys on speed of adjustment (SOA) towards the target capital structure are widely divergent as regards the measured speed. Most studies measure the SOA without taking into account certain specificities of the companies or of their strategies. Dividing the sample in non-acquiring companies, sporadic acquiring companies and serial acquirers, this study seeks to investigate the pattern of behavior of the SOA, in the period between 1990 and 2010 for North American companies. Considering several control variables (financial restrictions, growth opportunities, degree of financial leverage and issuance/reduction of debts and shares), we have a more in-depth investigation into how non-acquiring companies, sporadic acquiring companies and serial acquirers adjust their capital structure towards the target. Market leverage value and net market leverage are used as dependent variables. It was verified that the average debt levels for the three samples are different from one another, in a statistically significant manner. The serial acquirers have the lowest leverage, while non-acquiring companies have the highest leverage, with acquirers companies in an intermediate position on the leverage. This result suggests that companies have different debts patterns, due to its investment policy related to acquisitions. The partial adjustment model is employed to measure the SOA, using dynamic panel data with the Generalized Method of Moments (GMM) Systemic to measure the speed of adjustment of the capital structure from one period to another. This technique has shown itself to be less biased and has thus been one of the most commonly used techniques in empirical studies. The results show evidence that the SOA may depend of its investment strategy. The SOA of serial acquirers companies is constantly lower than the SOA of acquiring companies, even considering all the control variables. The SOA of non-acquiring companies remains in an intermediate position. Taken together, these results suggest that the financial slack (low debt and high cash balance) is a relevant factor to serial acquirers. Thus such companies adjust their debt more slowly in response to a more adequate capital structure to their investment policy. On the other hand, sporadic acquiring companies adjust faster its capital structure, due to its sporadic acquisition policy.