Esta dissertação busca verificar se existem práticas relacionadas a Gerenciamento de Resultados (a partir das Escolhas Contábeis) que sejam provenientes do impacto da contabilização de derivativos nas instituições bancárias em funcionamento no país sob a supervisão do Bacen, com posição em 1º/12/2008. Uma das inovações deste estudo é que, além da utilização de todos os Bancos na posição considerada, o que perfaz um censo, esta pesquisa possui enfoque com base na Teoria das Escolhas Contábeis. A abordagem desta dissertação é empírico-analítica, a hipótese geral é de que não existe Gerenciamento de Resultados para todas as instituições analisadas e o método utilizado considera a técnica de análise de dados em painel e regressões com variáveis dummy. As classificações para a utilização dessas variáveis compreendem: tamanho dos Bancos (por meio do Ativo Total e também da classificação já existente divulgada trimestralmente pelo Bacen); origem, segregando os Bancos em brasileiros e não brasileiros; níveis diferenciados de Governança Corporativa, em que se distinguem aqueles que são ou não adeptos dos Níveis 1, 2 ou Novo Mercado; e acompanhamento por analistas, em que se separaram as instituições entre aquelas que são ou não acompanhadas por profissionais (as informações foram retiradas do site da Thomson One Analytics). A base de dados estende-se de 2002 a 2008, para 158 Bancos, com 1.044 observações. As evidências apontam que, de modo geral, não foi possível identificar pelas variáveis utilizadas nos modelos, na maioria das situações testadas, Gerenciamento de Resultados, a partir das Escolhas Contábeis, isto é, não há evidência empírica, por essas variáveis, que os Bancos no Brasil, independentemente do tamanho, origem, níveis diferenciados de Governança Corporativa e acompanhamento por analistas, utilizem a contabilização de derivativos como instrumento de Gerenciamento de Resultados. / This dissertation aims at verifying whether there are Earnings Management practices (regarding Accounting Choices) resulting from the impact of accounting for derivatives in Bank institutions available in Brazil, with position on 12/01st/2008, under Brazils Central Bank supervision. One of the innovations of this study is that in addition to the use of all Banks in the mentioned position, which consists of a census, this practice has its focus on Accounting Choice Theory. The approach of this dissertation is an empirical-analytical one, and its general hypothesis is that there is no Earnings Management for all considered institutions. Additionally, the method considers the panel data analysis and regressions with dummy variables. The classification for the use of these variables includes: size (through Total Asset) of the Banks and also another existing classification, which Brazils Central Bank discloses trimestrally; origin, (Brazilians and non-Brazilians Banks); differenced levels of Corporate Governance, which distinguishes among those that are or are not placed on Level 1, 2 or New Market; and accompaniment by analysts, in which institutions are separated among those that are or are not accompanied by those professionals (the information is taken from the Thomson One Analytics website). The data basis ranges from 2002 up to 2008, for 158 Banks, with 1.044 observations. The evidences point out that it was not generally possible to identify, in the models, in the majority of the tested situations, Earnings Management through Accounting Choices, which means that it was not found empirical evidence that Banks in Brazil, regardless of the size, origin, differenced levels of Corporate Governance and accompaniment by analysts, use accounting for derivatives as a tool for Earnings Management.

Abstract This thesis investigates whether stock returns can help forecast macroeconomic activity. Future earnings and dividends and current stock prices should contain information about the future state of firms and the consumption possibilities of consumers. These activities are linked to aggregate economic development and, hence, the stock markets should improve economic forecasting. We review the theoretical points that justify the importance of stock markets in economic forecasting. Recent literature on the stochastic discount factor in asset pricing and the real business cycle models has approached this connection. We try to show that the direction between financial markets and macroeconomy could be from stock markets to real economy. We empirically test the forecasting ability of stock markets with respect to macroeconomy. The unexpected part of stock return can be revealed with economic tracking portfolios (ETP), which are constructed so that the unexpected portion of the portfolio return has the maximum correlation with revisions to expectations of the target variable. ETP's track how investors revise their expectations about relevant macroeconomic variables. The results show that specific stock portfolios track future changes in macroeconomic variables well. In the previous literature, stock returns have been connected to the business cycle. This connection is analysed by explaining stock returns with total factor productivity (TFP) as a factor. TFP is measured by corporate innovation variable, i.e. the change in a firm's gross profit margin unexplained by changes in firm's capital and labour. The TFP variable performs quite nicely in explaining stock returns and it can be related to stock market momentum. Next, the aim is to investigate the forecasting power of stock returns together with the TFP factor. Even though in our results the TFP contains no information relevant for economic forecasting, the stock returns continue to perform well.

The dissertation focuses on different institutional models of financial regulation. It aims to ascertain whether any of the institutional models responds better to the current nature of financial markets.

The aim of this thesis is to analyse the increased correlation within four major asset groups (Government Bonds, Equity Indices, Commodities and Currencies) from the beginning of Great Recession till July 2014. The effect of increased correlation is called Risk-On Risk-Off and is connected to problems, where investors struggle to create risk-oriented portfolios and instead minimalize loss. The methods analysing the correlations are Absolute Average Value Index (AAVI) and Heat-map analysis. The AAVI is transforming correlation matrix into a single number and investigating the intensity of correlations. The Heat-map is studying the relationship between any two assets. The results from this study were that the RORO effect was present during Great Recession with intensity never seen before and that in June 2014 the values are close to pre-recession levels.

This master’s thesis predicts the development and assesses the potential of cryptocurrencies in the areas of investment, trade and technology based on their technical, economic and legal analysis. Although the thesis deals with cryptocurrencies in general, the key focus is placed on their most prominent representative (Bitcoin) in trying to predict the effects on the future of financial markets from a wide, multidisciplinary perspective.

This dissertation is structured as three essays on various aspects of equity option introduction. Topics addressed include the relative predictability of introduction, the relationship between predictability of introduction and the price effect associated with introduction, and a comparison of the price response of optioned versus nonoptioned stocks to changes in dividends. Essay 1 involves use of firm-specific variables in a LOGIT model to allow assignment of a probability of equity option introduction. Two samples were developed: one of firms that were optioned, the other of firms which met the objective standards but were not optioned. A LOGIT model is used to assign a probability of optioning to each firm. A holdout sample is used to test the out-of-sample predictive power of the model. Firms were correctly classified as optioned or nonoptioned in about 85 percent of cases. Various researchers have detected abnormal positive returns associated with stock option introduction. In an efficient market context, this would indicate that option introduction is "good" news to financial markets. If optioning is predictable, stocks with a higher probability of optioning would be expected to show less price response when options are introduced. In Essay 2, the relationship between the probability of optioning and abnormal returns is tested using a standard event methodology. Utilizing nonparametric statistics, no significant differences were detected among abnormal returns of portfolios formed on the basis of probability of option introduction. Essay 3 compares abnormal returns of optioned and nonoptioned stocks around announced dividend changes. Two samples were obtained. Firms in the first (second) sample had significant dividend changes while options were (were not) available on their stocks. Standard event methodology is used to compare price responses of the two samples. If the price response of optioned stocks is less pronounced than the price response of nonoptioned stocks, this may indicate that optioned stocks are more efficiently priced. Reasons for this increased efficiency are examined in the study. Abnormal returns for the optioned sample were not significantly different from zero. Those for the nonoptioned sample were significantly different from zero for all event windows tested.

A thesis submitted to the Faculty of Commerce, Administration and Law, in fulfillment of the requirement for the Degree of Doctor of Philosophy in Economics at the University of Zululand, 2019. / The extent of the damage caused by the 2007/08 global financial crisis (GFC) has forced policymakers all over the world to respond promptly in order to mitigate its effect, a process in which they are still engaged in, particularly in advanced economies. The main objective of this study is to measure systemic risk in African emerging economies and develop a macroprudential regulatory framework to mitigate or limit the effect of such risk. More specifically, the study intends to1) Developing financial stress index (FSI) for the Emerging African economy; 2) Investigate the possibility of Early Warning Signal (EWS) helping in predicting and preventing or minimising the effects of the crisis on financial institutions; 3) Assess the resilience of individual banking companies to adverse macroeconomic and financial market conditions using stress testing technique; 4) Identify the source of fluctuation within the system; 5) Identify and measure systemic risk emanating from the capital flow (surge) as well as its effects on financial stability. This study contributed to the body of knowledge by measuring systemic risk in emerging African economies. To the best of my knowledge, there have not been any studies that have been conducted for the measure of systemic risk with the context of emerging African economies. The target economies include South Africa, Egypt, Nigeria, and Kenya. The first objective of the study is to construct a financial stress index (FSI) for emerging African economies. The FSI which is aimed at revealing the functionality of the financial system a single aggregate indicator that is constructed to reflect the systemic nature of financial instability and as well to measure the vulnerability of the financial system to both internal and external shocks. The result shows that both the domestic and international shocks created uncertainty in the economies under consideration. On the international scene, we have the financial crisis while on the domestic scene; we have slow growth, banking crisis, energy crisis, labour crisis, coupled with political uncertainty. The FSI is also useful and appropriate as the dependent variable in an early signal warning model, and as well be used to gauge the effectiveness of government measures to mitigate financial stress. The models forecasting performance was tested using the ordinary least square methods and it affirmed that the model is reliable and that the FSI can be used for prediction of a future crisis. v The aim of the second objective is to develop an early warning signal (EWS) model to predict the possibility of the occurrence of a financial crisis in emerging African countries. The multinomial logit model built by Bussiere and Fratzscher (2006) was adopted to afford policy makers ample time to prevent or mitigate potential financial crisis. In summary, the result suggests that emerging African economies are more likely to face financial crisis as debts continue to rise without a corresponding capacity to withstand capital flow reversal as well as excessive FX risk due to currency exposure. The result further indicates that rising debt exposure increases the probability or likelihood of the economies remaining in a state of crisis. This result confirms the significance of a financial stability framework that fits Africa’s emerging economies characteristics such as rising debt profile liquidity and currency risk exposure. The third objective is to test the resilience of the financial sector using stress testing technique. Macro stress testing is a multi-step simulation process aimed at estimating the impact of credit risk shock on macroeconomic as well as financial sectors. In this study, a two-step approach was employed in this chapter. The first step involves analyzing the determinants of credit risk in 4 Emerging African economies during the period 2006m1 to 2012m12 using the panel Auto Regressive Distribution Lag (ARDL) model. Second, the vector autoregressive (VAR) models were employed to assess the resilience of the financial system as well as the economy to adverse credit risk shocks. The result shows that all the variables under both the macro and financial model jointly determine credit risk, although when examined on an individual basis only, UMP, IBR, and INF have a significant impact on NPL in the long run. For the macro stress testing, the VAR methodology was employed to stress test the emerging African economy financial sector and the result indicated that there a significant relationship between changes in output gap (GAP) and the nonperforming loans. A significant relationship was also established between inflation and nonperforming loans. In all, South Africa and Nigeria’s financial system seems more resilient to credit losses associated with this scenario without threatening financial stability compared to Kenya and Egypt. The fourth objective examined the sources of capital flows surge and their impact on macroeconomic variables. This study employed a ��−�������� to investigate the source capital flow surge within the system. The main findings of the result indicate that capital flow, which is vi proxied by FDI, is influenced by a wide variety of macroeconomic variables such as inflation, export growth and unemployment. There is therefore need for the implementation of capital controls framework tame massive capital inflows. Nevertheless, such a mechanism should not undermine the impact of capital inflows on employment, growth and financial stability. The fifth objective of the study is aimed at identifying and measuring the sources of systematic risk and its impact on the stability of the financial system using the Conditional Value-at-Risk methodology. The main finding of the study indicates that at the normal and extreme event the banking sector contributes positively and significantly to the real economy for all the countries except for Nigeria at the extreme event or 1 percent quantile. This study, therefore, concludes that the banking sector, stock market volatility contributes greatly to systemic risk in emerging African economies. The individual bank also contributes significantly to systemic risk for all the economies although the magnitudes are relatively different across economies. This finding is of great interest to policymakers since it shows that the banking sectors as well as stock market volatility have a negative impact on the real economy. This result is plausible as the banking and financial sector for most emerging economies constitute a greater proportion of the real economy. There is, therefore, need for a regulatory framework to reduce risk emanating from the banking sector as well as the financial markets. In summary, due to huge capital flows and rising debt level in emerging African economies, there is, therefore, a need for a macroprudential policy that will fit African economies as well as the implementation of capital controls framework tame massive capital inflows. Efforts should be made to reduce the rising debts profile of most countries and that will require a greater level of commitment from their respective government and central banks. However, these should be in the interest of the growth and stability of the financial system and the real economy at large. In the case of the banking sector, since it has a great impact on triggering systemic risk, more effort should be utilized to continue to monitor its performance so that potential risk can be detected early and nip in the bud.

Kenya has over the last few years witnessed tremendous growth as an emerging market with the GDP growing at 5% and the capital markets having a year on year growth of 19%. Despite the growth and sophistication of the financial markets, a host of hurdles have kept Kenya off the mainstream Responsible Investing agenda. This has resulted in no Socially Responsible Investment (SRI) fund assets and none of the market players being signatories to the United Nations Principles for Responsible Investing (PRI). One of the building blocks to this journey could be introducing a Sustainability Index for listed companies on the Nairobi Securities Exchange (NSE). This would form a basis for integrating Environmental, Social and Governance (ESG) aspects into the private sector and other proponents of the society, including the public sector. This research is thus aimed at linking the growing sophistication of the financial markets in Kenya with the possible creation of a Sustainability Index. In this sense, financial markets are seen to have the power to affect social, economic, and environmental outcomes in which a Sustainability Index could become a good tool in measuring such outcomes. The study adopted a qualitative research design which was used to obtain information based on the key research questions of the study. The research findings suggest that Responsible Investing (RI) is understood within the realm of business ethics and corporate governance. RI is inferred to as a manner of doing business that goes beyond short term financial returns and also takes into account the needs of other stakeholders. ESG aspects identified from the study provide for the requisite issues out of which a Sustainability Index can be developed for measuring the impact of Responsible Investing. Within the framework of a Sustainability Index, it is clear that companies will be made more accountable; redefine their corporate boundaries and through shared value, measure the social and environmental impact of their business model. However, there is still need for increased awareness on RI, stakeholder activism and an improved regulatory framework. Embedding Responsible Investing in Kenya will entail understanding the system of actors, so as to look at opportunities of Creating Shared Value whilst setting this up in the right disclosure model.

Thesis advisor: Rosen Valchev / This thesis explores the impact of Donald Trump’s tweets related to China on the financial markets in the United States and China, particularly during the U.S.-China trade war period. The study collects financial variables of interest, including the USC-CNY exchange rate and several stock indices from both countries, at hourly intervals from January 2018 to December 2020, and uses OLS regression models to examine the immediate impact of Trump’s tweets on these variables. The study finds that Trump’s tweets related to China had an immediate impact on several financial variables, including a slight negative impact on the USD-CNY exchange rate, the U.S. stock market (S&P 500), the Chinese A-share stock market (CSI 300), and the U.S. industrials sector (MSCI USA Industrials index). Multiple regression analyses show that the number of tweets has a significant impact on the U.S. stock market and the U.S. industrials sector, while the number of retweets appears to be more market-moving than the number of favorites. The study concludes that Trump’s tweets during the trade war period were perceived by the market as a signal of a potential shift in U.S. trade policy towards China, leading to uncertainty and volatility in the financial markets. / Thesis (BA) — Boston College, 2023. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Economics.

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