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)

The literature investigating the relationship between stock market returns and inflation is long and has produced diverse findings. This thesis examines the nature of stock–inflation relations in Sub-Saharan countries whose stock markets were established before 1992. Evidence in this thesis shows that in the short term there is a positive relationship between stocks and inflation. Using the Johansen (1988) evidence, a long-run stock–inflation relationship is confirmed only in Nigeria and South Africa, where it is found to be negative. However, accounting for structural breaks provides evidence for a long-run relationship in Botswana, Ghana and Kenya. The evidence of the effects of regimes in the relationship is further supported by a nonparametric cointegration analysis which finds a long-run relation in countries where the Johansen (1988) method had failed. Unexpected inflation is also found to be related to stock returns in Botswana, Ghana, Kenya, Nigeria and Mauritius, which raises concerns about the use of month-end stock data in analysing this relationship. The thesis confirms the existence of hidden inflation in Kenya, Mauritius, Nigeria and Zimbabwe. Imported inflation, interest rates and the exchange rate are found to have useful information about inflation movements in Sub-Saharan Africa.

本研究主旨有三：(一)整理現有股市財經節目的營運方式、節目內容並瞭解財經節目主持人及其口語傳播技巧。(二)從股市財經節目觀眾收視行為來觀察，以節目收視率及收視觀眾輪廓(audience profile)為基礎，觀察股市財經觀眾其日常生活中收看股市財經節目的相關行為。(三)結合對財經節目與觀眾收視行為的觀察與研究，找出股市財經節目的關鍵要素並提出建議。 本研究以文本分析、深度訪談、二手資料整理等研究方法進行，分析整理後，發現股市財經節目觀眾的收視動機非常明確，為主動閱聽人，收看節目係屬工具性行為，主要目的係希望投資獲利。因此，節目設計應先考量以下兩點：(1)股市財經節目的觀眾特性：男女比例相當、年齡層較高、學歷較高、居住北部地區較多、家庭所得較高、對資訊需求差異大、對節目是否應教育功能意見分歧。(2)股市特性：資訊瞬變、影響股市漲跌因素甚多、需專家解說。 而股市財經節目雖與其他節目有明確區隔，唯同類型的電視投顧節目或股市貼盤節目本身並無差異化，造成電視投顧節目以消耗投顧老師的方式進行經營，四個股市貼盤節目僅有二個尚稱成功，本研究建議節目產製單位應以更深層、更能吸引觀眾的相關投資資訊來提升閱聽眾對節目的忠誠度，而同類型節目之間則應以觀眾對資訊偏好的需求、對節目教育功能的不同的認知來進行差異化。 / This analysis will 1) examine the current format for Stock Market Analysis Television Programs, the program content, the program hosts types, and the host speaking styles. 2) Examine program viewer behavior, based on viewer ratings, audience profile, and the role that these programs play in the daily lives of its viewers. 3) Ascertain the key elements of these programs and provide recommendations based on conclusions reached through cumulative analysis of such television programs and the behavior of their viewers. Based on text analysis, in-depth interviews, and second-hand data, viewers appear to have clear utilitarian motivations for watching these television programs, they are active listeners, and their primary objective is to profit on their stock market investments. Program design should take into consideration the following elements: 1) Viewer Demographics: even proportion of male and female viewers, higher age-bracket, highly educated, living primarily in Northern Taiwan, high household incomes, strong demand for new information, split on whether such programs provide educational value. 2) The Nature of the Domestic Stock Market: information changes quickly, factors affecting the rise and fall of stock prices are many, professional market insight and analysis is needed. Stock Market Analysis Television Programs, which are quite different from other television programs, fall into one of two main types: Investment Consulting Company-produced Analysis Programs, Real-time Market Data and Analysis Programs, with very little variation between competing programs in each category. The former generally relies on a string of new program hosts in an attempt to maintain viewer interest. There are currently only four of the latter type of program currently running with only two of them showing even mild success. This report will recommend that producers of such programs should offer more in-depth content so as to better attract and maintain viewers. Competing programs should also distinguish themselves from one another by offering different types of data and analysis content, and different levels of educational content in their programs.

This thesis explores the impact of two behavioural finance concepts, social psychology and psychology, on household financial decisions. Under social psychology, I investigate whether the variety and intensity of social engagement enhances stock market participation. With regard to psychology, I examine two behavioural biases. First, I investigate whether mental accounting influences portfolio choice in three asset classes and whether financial advice and housing tenure increase (decrease) the effects of mental accounts on portfolio choice. Second, I examine whether households’ self-reported housing wealth are anchored on published house price indices and whether anchoring bias is mediated by market information, mortgage refinancing decisions and social factors. The main contributions and findings in the three studies are as follows. First, although there is an elaborate body of research concerning the relationship between social engagement mechanisms and portfolio choice, most studies investigate specific mechanisms in isolation. Using three waves in the British Household Panel Survey (BHPS), I bring together five social engagement measures in one model and show that socially engaged individuals are more likely to participate in the stock market. Consistent with Granovetter’s (1973) theory of social networks I find that a weak tie (measured by social group involvement) has a positive effect on stock market participation whereas a strong tie (measured by talking to neighbours) has no effect. More trusting individuals are more likely to participate in the stock market, as are those who identify with a political party. In contrast, the degree to which religion is important appears to have little impact. These results are robust using different specifications. Overall, the results of this study demonstrate that the likelihood of stock market participation increases with the variety and intensity of social engagement. Second, despite the established theoretical underpinnings of mental accounting in behavioural portfolio theory (BPT) and recent extensions, not much is known about their implications in real life situations. I use a recent UK household survey, the Wealth and Assets Survey (WAS), which has comprehensive information about financial assets to investigate whether there are differences in the ownership and portfolio share of three asset classes among individuals who exhibit no mental account, a single mental account and multiple mental accounts, and the conditional influences of financial advice, housing, cognitive ability, time preference and risk tolerance. Overall I find that mental accounting together with financial advice and housing tenure explain variations in both the probability of ownership and portfolio share in the three asset classes. Households that exhibit a single mental account have low share of investments in, and are less likely to own, a risky asset when compared to those that exhibit no mental account or exhibit multiple mental accounts. I also find that, when compared to having no mental account, exhibiting a single mental account or multiple mental accounts increases both the probability and investment share in a fairly safe asset but decreases portfolio share in safe assets. In addition, among those that exhibit a single mental or multiple mental accounts, financial advice decreases portfolio share in risky assets and fairly safe assets and increases portfolio share in safe assets. Housing tenure increases both the probability and portfolio share in risky assets, decreases portfolio share in fairly safe assets and increases portfolio share in safe assets. These results are consistent using multi-equation regressions, sub-samples, reparametrised variables and poisson regressions. Finally, as little is known about how households derive the self-reported house prices estimates that are commonly used to determine housing wealth, the third study examines whether households are anchored on published house price indices. The key conjecture is that, while assessing the values of their homes, homeowners place more weight on house price news at the expense of property characteristics and other market information. I find support for this hypothesis using sixteen waves of the BHPS, multiple methods, and both regional and national house price indices. I conclude that changes in self-reported housing wealth are anchored on changes in published house price indices. Specifically, ownership through a mortgage and greater financial expectations increase anchoring effects while mortgage refinancing decreases the effects. Moreover, use of money raised from refinancing for home investment, as opposed to other consumption purposes, has a positive association with change in self-reported house value and both uses reduce anchoring bias. In addition, I find that computer use increases anchoring bias and, among social engagement mechanisms, religiosity reduces anchoring while other measures have no effect. These results are robust to internal instrumental variables, national aggregate house prices, alternative indices and sub-samples.

Dans cette thèse, nous proposons quatre contributions originales à l'étude de l'intégration monétaire et financière des pays asiatiques.Dans le premier chapitre nous déterminons la sensibilité relative des devises asiatiques (ASEAN-5, Corée du Sud) face aux chocs simulés sur le dollar, l'euro et l'ACU. Nous mettons en évidence la volonté de ces pays de se détourner d'une politique de change exclusivement centrée sur le dollar vers une politique plus flexible, où le poids de l'ACU semble avoir gagné en importance.Le deuxième chapitre met l'accent sur la synchronisation entre les cycles des affaires de l'ASEAN-5. Nous montrons que la corrélation entre les cycles est plus forte durant les phases de contraction mais que la dynamique d'ajustement est propre à chaque pays. Par ailleurs, certains cycles des affaires de l'ASEAN-5 contiennent des informations pertinentes pour prédire les changements de régime des autres pays.Le troisième chapitre examine le co-mouvement entre les taux de change réels de l'ASEAN-5 du point de vue de la parité de pouvoir d'achat généralisé (Enders and Hurns, 1994, 1997). Nous montrons que les taux de change réels sont liés par un processus à mémoire longue, ce qui soutient l'idée d'une intégration monétaire plus poussée entre différents sous-groupes de pays. Enfin dans le dernier chapitre, nous examinons le degré d'intégration des marchés boursiers en Asie (ASEAN-5, Hong Kong, Japon). Nos résultats montrent que la volatilité des marchés boursiers internationaux partagent une tendance stochastique commune. En revanche, les marchés boursiers des pays émergents apparaissent encore segmentés tant au niveau global que régional. / This thesis proposes four contributions to the study of Asian monetary and financial integration.The first chapter examines to what extent the East Asian exchange rates (ASEAN-5, South Korea) are sensitive to shocks simulated on the US dollar, the euro and the ACU. We show that these countries have moved from a US dollar-based pegging system to a more flexible exchange rate policy, where the weight of the ACU has increased over the last years. The second chapter attempts to analyze the correlation among the ASEAN-5 business cycles. Estimates reveal that correlations are higher during downturns but the process of adjustment to shocks displays idiosyncratic features. We also provide evidence that the signals contained in some leading ASEAN-5 business cycles help predict regime switching in other countries. The third chapter examines the co-movement among the ASEAN-5 real exchange rates through the generalized purchasing power parity (Enders and Hurns, 1994, 1997). We find that real exchange rates are tied through a long memory process, supporting further monetary integration among different sub-groups of the ASEAN-5.In the last chapter, we investigate to what extent the stock markets in Asia (Hong Kong, Japan, ASEAN-5) are integrated. Our results reveal that the stock market volatilities in developed countries share a common stochastic trend. Conversely, emerging markets appear to be segmented from both each other and global markets.

A importância de se considerar os volumes na análise dos movimentos de preços de ações pode ser considerada uma prática bastante aceita na área financeira. No entanto, quando se olha para a produção científica realizada neste campo, ainda não é possível encontrar um modelo unificado que inclua os volumes e as variações de preços para fins de análise de preços de ações. Neste trabalho é apresentado um modelo computacional que pode preencher esta lacuna, propondo um novo índice para analisar o preço das ações com base em seus históricos de preços e volumes negociados. O objetivo do modelo é o de estimar as atuais proporções do volume total de papéis negociados no mercado de uma ação (free float) distribuídos de acordo com os seus respectivos preços passados de compra. Para atingir esse objetivo, foi feito uso da modelagem dinâmica financeira aplicada a dados reais da bolsa de valores de São Paulo (Bovespa) e também a dados simulados por meio de um modelo de livro de ordens (order book). O valor do índice varia de acordo com a diferença entre a atual porcentagem do total de papéis existentes no mercado que foram comprados no passado a um preço maior do que o preço atual da ação e a sua respectiva contrapartida, que seria a atual porcentagem de papéis existentes no mercado que foram comprados no passado a um preço menor do que o preço atual da ação. Apesar de o modelo poder ser considerado matematicamente bastante simples, o mesmo foi capaz de melhorar significativamente a performance financeira de agentes operando com dados do mercado real e com dados simulados, o que contribui para demonstrar a sua racionalidade e a sua aplicabilidade. Baseados nos resultados obtidos, e também na lógica bastante intuitiva que está por trás deste modelo, acredita-se que o índice aqui proposto pode ser bastante útil na tarefa de ajudar os investidores a definir intervalos ideais para compra e venda de ações no mercado financeiro. / The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.

The study examines the dynamic relationship between financial development and investment in three Southern African countries (Botswana, South Africa and Mauritius) during the period 1976 – 2014 using annual data. The motivation for selecting these countries is mainly based on their different characteristics in their economic and financial structure. Employing the Autoregressive Distributed Lag (ARDL) bounds test approach, the study examines the role of financial development in boosting investment; and the causal relationship between financial development and investment. The study makes use of composite financial development indices and divides financial development into bank-based and market-based financial development. In addition, both the impact of bank- and market-based financial development on investment, on the one hand; and the causality between bank- and market-based financial development and investment, on the other, were examined within the flexible accelerator model/framework. For both models, both bank-based and market-based financial development are assumed as having an accelerator-enhancing effect on investment. Empirical results show that, for Botswana, the impact of bank-based financial development on investment is positive in both the short run and the long run while no impact of market-based financial development is found for both periods. For South Africa, the effect of bank-based financial development on investment is found to be negative in the short run and has no impact in the long run. However, market-based financial development has only a positive effect on investment in the long run. For Mauritius, market-based financial development is the only type of financial development found to have a significant positive effect on investment, and only, in the short run. The results of the causality test show that: for Mauritius, both bank-based and market-based financial development tend to drive investment, both in the short run and in the long run; while- in South Africa, investment drives both bank-based and market-based financial development only in the short run. In Botswana, bank-based and market-based financial development and investment drive each other in the short run while investment tends to only drive bank-based financial development in the long run. Therefore, all three countries show differing results and tend to confirm that there are inter-country differences that determine the relationship between investment and financial development. The inter-country differences maybe as a result of the different stages of financial and economic development for each country. / Economics / D. Phil. (Economics)

A importância de se considerar os volumes na análise dos movimentos de preços de ações pode ser considerada uma prática bastante aceita na área financeira. No entanto, quando se olha para a produção científica realizada neste campo, ainda não é possível encontrar um modelo unificado que inclua os volumes e as variações de preços para fins de análise de preços de ações. Neste trabalho é apresentado um modelo computacional que pode preencher esta lacuna, propondo um novo índice para analisar o preço das ações com base em seus históricos de preços e volumes negociados. O objetivo do modelo é o de estimar as atuais proporções do volume total de papéis negociados no mercado de uma ação (free float) distribuídos de acordo com os seus respectivos preços passados de compra. Para atingir esse objetivo, foi feito uso da modelagem dinâmica financeira aplicada a dados reais da bolsa de valores de São Paulo (Bovespa) e também a dados simulados por meio de um modelo de livro de ordens (order book). O valor do índice varia de acordo com a diferença entre a atual porcentagem do total de papéis existentes no mercado que foram comprados no passado a um preço maior do que o preço atual da ação e a sua respectiva contrapartida, que seria a atual porcentagem de papéis existentes no mercado que foram comprados no passado a um preço menor do que o preço atual da ação. Apesar de o modelo poder ser considerado matematicamente bastante simples, o mesmo foi capaz de melhorar significativamente a performance financeira de agentes operando com dados do mercado real e com dados simulados, o que contribui para demonstrar a sua racionalidade e a sua aplicabilidade. Baseados nos resultados obtidos, e também na lógica bastante intuitiva que está por trás deste modelo, acredita-se que o índice aqui proposto pode ser bastante útil na tarefa de ajudar os investidores a definir intervalos ideais para compra e venda de ações no mercado financeiro. / The importance of considering the volumes to analyze stock prices movements can be considered as a well-accepted practice in the financial area. However, when we look at the scientific production in this field, we still cannot find a unified model that includes volume and price variations for stock prices assessment purposes. In this paper we present a computer model that could fulfill this gap, proposing a new index to evaluate stock prices based on their historical prices and volumes traded. The aim of the model is to estimate the current proportions of the total volume of shares available in the market from a stock distributed according with their respective prices traded in the past. In order to do so, we made use of dynamic financial modeling and applied it to real financial data from the Sao Paulo Stock Exchange (Bovespa) and also to simulated data which was generated trough an order book model. The value of our index varies based on the difference between the current proportion of shares traded in the past for a price above the current price of the stock and its respective counterpart, which would be the proportion of shares traded in the past for a price below the current price of the stock. Besides the model can be considered mathematically very simple, it was able to improve significantly the financial performance of agents operating with real market data and with simulated data, which contributes to demonstrate its rationale and its applicability. Based on the results obtained, and also on the very intuitive logic of our model, we believe that the index proposed here can be very useful to help investors on the activity of determining ideal price ranges for buying and selling stocks in the financial market.

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 / D. Com. (Economics)

In this study, linear and nonlinear Granger causality tests are used to examine the dynamics, including return to return and volume to volume relationships, between warrants and their underlying stocks in Taiwan Stock Exchange (TSEC). Results of previous studies are mixed and they only focus on linear relationship between the two markets. Here we take nonlinear relationship into consideration to assist in investigating what the direction of information flow is. We use intraday five-minute high frequency data and the result tells that, overall, for both return to return and volume to volume relations, there is bidirectional but asymmetry linear causality and weak unidirectional nonlinear causality from stock to warrant market between these two markets. Combining the linear and nonlinear results we conclude that the direction of information flow is mainly from stock market to warrant market.