Financial literacy Financial illiteracy among the population is a painful problem, probably in every country in the world, including Czech Republic. The first part of this work intends to define financial literacy as a subject of andragogy. The next parts are concerned with various researches regarding financial literacy, mostly from the United States and from the Czech Republic. Then, many projects, that shall improve financial literacy among Czech population, are going to be observed and compared. We will see how the main three sectors (the state, commercial subjects and the NGO's) are cooperating in order to achieve the common goals in spreading the financial literacy. The last part of this work is about dividing the population into various groups on the basis of their financial literacy level.

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It is sometimes purported that one of the factors affecting a firm's value is its capital structure. The event of the 1997 Asian financial crisis was expected to affect the firms' gearing level as the firms' earnings deteriorated and the capital market collapsed. The main objective of this research is to examine empirically the determinants of the capital structure of Malaysian firms. The main additional aim is to study the capital structure pattern following the 1997 financial crisis. Empirical tests were conducted on two different data sets: the first data set is the published data extracted from Datastream and consists of: 572 companies listed on the Kuala Lumpur Stock Exchange (KLSE) between 1994 and 2000. The second data set comprises finance managers' responses to a questionnaire survey. Chi-square, Kruskal-Wallis, ANOVA, multiple regression, stepwise regression and logistic regression were utilised to analyse the data. The multiple regression analysis was employed to find the determinants of the capital structure using various account data items provided by Datastream. The gearing differences between the two boards and within the sectors were also analysed using ANOVA and Krukal-Wallis tests. The panel data were evaluated with regard to the gearing pattern following the 1997 currency crisis. Overwhelming evidence on profit was found, with past profitability being the major determinant of gearing. In particular was the support for pecking order theory, in that finance managers had given internal funds the highest priority, followed by debt and equity as a last option. The statistical analysis found a strong negative correlation between liquidity and the gearing ratio for both boards, implying firms considered highly the excess current assets for funding, a conservative approach towards debt management policy. On the other hand, taxation items were not highly significant in capital structure decisions. The results indicate the existence of gearing differences between the main board and the second board gearing with high debt levels employed by second board companies. However, the second board's high gearing is dominated largely by short to medium term bank credit. Differences were also significant between different sectors of companies listed on the main board. Firms' gearing ratios increased significantly following the 1997 financial crisis, and the gearing tended to increase where the company's share prices were highly sensitive towards currency volatility. Also inflation is found to influence the changes in actual and target gearing ratios following the crisis. Recent emphasis on the development of private debt securities may affect the findings of this research in the near future.

M.Com. (Taxation) / Financial prices such as interest rates, currency exchange rates and equity prices have become more volatile In recent years making financial costs more difficult to predict and control. Just as commodity Mures exchanges grew out of the need for a mechanism to protect producers and users of commodities from the effects of fluctuations In prices, so the financial futures markets have developed to provide a means of lessening the Impact of fluctuations in interest rates, currency exchange rates and share Indices. A futures contract Is a transferable agreement to buy or sell a standardised amount of a commodity of standardised quality at a fixed price on a specific future date underterms and conditions ofarecognised exchange. A significant milestone was reached in the development of South Africa's financial markets with the simultaneous publication and the release to the public of the reports of the Stals and Jacobs Committees in July 1988. The road had not been all that smooth up to that point. The 1985 debt standstill and all the implications which flowed therefrom had made for a somewhat bumpy ride. However, by mid·1988 the markets were once again picking up the threads and making furtherstrides forward. Flowing from the recommendations of these two committees has been the establishment of the South African Futures Exchange and the South African Futures Clearing Company where financial Mures will be freely traded. The South African tax authorities could not provide the above committee with clear guidelines as to how Mures transactions would be treated for tax purposes In the South African context, except that Receivers of Revenue, having regard to decisions handed down by the courts In a variety of cases considered over a period of many years, would decide whether any particular transaction, or series of transactions, Is ofe~her a ·revenue" or "capital" nature. If the transaction is considered to be on "revenue" account, then the profit (or loss) Is taken Into account In the determination of taxable Income for Income tax purposes. The distinction becomes of paramount Importance when dealing In futures as no capital gains tax exists In South Africa and personal and company tax rates are relatively high.

M.Econ. / Please refer to full text to view abstract

This paper aims to make an empirical contribution to the discussion of the role of banks and to find out if banking is a declining industry. It takes into account that the role of banks is declining in the United States and the fact that the American economy usually sets the trend for the other economies. This implies that there are increasing trends of disintermediation, securitization and an increase in the importance of nonbank financial intermediaries (Schmidt, Hackethal and Tyrell 1997). This paper seeks to find out if this is indeed the case in the U.S and if so then is it happening in other European and African economies. Another important reason for this study is to find out what factors are causing the structures of financial systems to change and what impact these changes have on financial institution intermediation. Comparisons are made between developed countries in Europe and developing countries in Africa to observe the trends of intermediation/disintermediation.

This paper explores the distinction between ‘equity’ and ‘liabilities’ in financial reporting in order to assess the merits of the current system of accounting for share-based payment transactions. It applies an interpretive methodology. Data were collected from a series of interviews with purposefully selected experts. Criticisms of and support for the current accounting regime are interpretively analysed and used to identify key themes or principles for evaluating the merits of three models proposed in the academic literature: the strict liability, narrow equity and ownership-settlement models. The study finds that the strict liability approach remains supported on the grounds that it provides decisionuseful information with which users are familiar. The other models are rejected as they are perceived as diminishing the usefulness of financial reporting. The study also identifies support for an obligation-centric approach, not fully developed in the literature, which may require detailed consideration by standard-setters. Overall, these findings will be useful for both practitioners and academics grappling with the difficulty of defining ‘equity’ and ‘liabilities’. In addition, the research makes a valuable contribution by addressing the need for interpretive-inspired financial reporting research. To the best of the author’s knowledge, this thesis is also the first South African study to investigate the appropriate classification criteria for instruments such as share-based payments and provide normative recommendations for the International Accounting Standards Board.

A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in the Faculty of Science, School of Computer Science and Applied Mathematics University of the Witwatersrand. October 2016. / Automated algorithmic trade execution is a central problem in modern financial markets, however finding and navigating optimal trajectories in this system is a non-trivial task. Many authors have developed exact analytical solutions by making simplifying assumptions regarding governing dynamics, however for practical feasibility and robustness, a more dynamic approach is needed to capture the spatial and temporal system complexity and adapt as intraday regimes change. This thesis aims to consolidate four key ideas: 1) the financial market as a complex adaptive system, where purposeful agents with varying system visibility collectively and simultaneously create and perceive their environment as they interact with it; 2) spin glass models as a tractable formalism to model phenomena in this complex system; 3) the multivariate Hawkes process as a candidate governing process for limit order book events; and 4) reinforcement learning as a framework for online, adaptive learning. Combined with the data and computational challenges of developing an efficient, machine-scale trading algorithm, we present a feasible scheme which systematically encodes these ideas. We first determine the efficacy of the proposed learning framework, under the conjecture of approximate Markovian dynamics in the equity market. We find that a simple lookup table Q-learning algorithm, with discrete state attributes and discrete actions, is able to improve post-trade implementation shortfall by adapting a typical static arrival-price volume trajectory with respect to prevailing market microstructure features streaming from the limit order book. To enumerate a scale-specific state space whilst avoiding the curse of dimensionality, we propose a novel approach to detect the intraday temporal financial market state at each decision point in the Q-learning algorithm, inspired by the complex adaptive system paradigm. A physical analogy to the ferromagnetic Potts model at thermal equilibrium is used to develop a high-speed maximum likelihood clustering algorithm, appropriate for measuring critical or near-critical temporal states in the financial system. State features are studied to extract time-scale-specific state signature vectors, which serve as low-dimensional state descriptors and enable online state detection. To assess the impact of agent interactions on the system, a multivariate Hawkes process is used to measure the resiliency of the limit order book with respect to liquidity-demand events of varying size. By studying the branching ratios associated with key quote replenishment intensities following trades, we ensure that the limit order book is expected to be resilient with respect to the maximum permissible trade executed by the agent. Finally we present a feasible scheme for unsupervised state discovery, state detection and online learning for high-frequency quantitative trading agents faced with a multifeatured, asynchronous market data feed. We provide a technique for enumerating the state space at the scale at which the agent interacts with the system, incorporating the effects of a live trading agent on limit order book dynamics into the market data feed, and hence the perceived state evolution. / LG2017

Thesis (Ph.D.)--Boston University / This thesis theoretically and empirically analyzes the nature and consequences of interactions between family members. The first chapter tests whether children's human capital accumulation was significantly affected by earnings shocks to their nonresident kin in the context of the 1997-8 financial crisis in Indonesia. The crisis produced sudden, heterogeneous shocks that facilitate the construction of an exogenous measure of earnings changes. Results indicate that earnings shocks to nonresident kin - including extended family and relatives living in other districts- significantly affected children's human capital accumulation between 1997 and 2000, and ultimate educational attainment measured nearly a decade after the crisis hit. Supplementary results point to intra-family transfers, underpinned by ex post altruism, as an important channel of causation. The second chapter develops a theoretical model of private transfers underpinned by ex post altruism among members of a network. I use this model to analyze equilibrium transfer patterns and inequality under alternative income distributions and network structures. I demonstrate the general intuition that transfers obtain in equilibrium when the amount of altruism is sufficiently strong relative to income inequality. Within the networks that I analyze, every equilibrium involving transfers takes the same form: unique income thresholds separate senders from receivers. Effective risk sharing takes place among senders and receivers, while those at intermediate incomes remain in autarky. Every equilibrium gives rise to the same set of allocations. I contrast these predictions with insurance-based theories of transfers in which risk sharing is operative for small in come differences and may fall apart at large income differences. The third chapter uses longitudinal data spanning nearly fifteen years to test whether transfers among family members within Indonesia are consistent with ex post altruism, against the alternative of insurance. I use the predicted effects of permanent versus transitory income on transfers, as well as theoretical predictions from the second chapter regarding the shape of transfer functions , to carry out this test. The results provide some evidence that transfer motives are inconsistent with insurance but consistent with ex post altruism.

Thesis advisor: Zhijie Xiao / This dissertation contains three essays. It provides an application of quantile regression in Financial Economics. The first essay investigates whether tail dependence makes a difference in the estimation of systemic risk. This chapter develops a common framework based on a copula model to estimate several popular return-based systemic risk measures: Delta Conditional Value at Risk (ΔCoVaR) and its modification; and Marginal Expected Shortfall (MES) and its extension, systemic risk measure (SRISK). By eliminating the discrepancy of the marginal distribution, copula models provide the flexibility to concentrate only on the effects of dependence structure on the systemic risk measure. We estimate the systemic risk contributions of four financial industries consisting of a large number of institutions for the sample period from January 2000 to December 2010. First, we found that the linear quantile regression estimation of ΔCoVaR, proposed by Adrian and Brunnermeier (AB hereafter) (2011), is inadequate to completely capture the non-linear contagion tail effect, which tends to underestimate systemic risk in the presence of lower tail dependence. Second, ΔCoVaR originally proposed by AB (2011) is in conflict with dependence measures. By comparison, the modified version of ΔCoVaR put forward by Girardi et al. (2011) and MES, proposed by Acharya et al. (2010), are more consistent with dependence measures, which conforms with the widely held notion that stronger dependence strength results in higher systemic risk. Third, the modified ΔCoVaR is observed to have a strong correlation with tail dependence. In contrast, MES is found to have a strong empirical relationship with firms' conditional CAPM beta. SRISK, however, provides further connection with firms' level characteristics by accounting for information on market capitalization and liability. This stylized fact seems to imply that ΔCoVaR is more in line with the ``too interconnected to fail" paradigm, while SRISK is more related to the ``too big to fail" paradigm. In contrast, MES offers a compromise between these two paradigms. The second essay proposes a quantile regression approach to stock return prediction. I show that incorporating distributional information together with combining model information can produce a superior forecast for the conditional mean as well as the entire distribution of future equity premium, which significantly outperforms the forecast that utilizes either source of information alone. Meanwhile, the order of combination strategies appears to make a difference in the efficiency of pooling both distributional information and model information. It turns out that aggregating distributional information in the first step, followed by combining model information in the second step is more advantageous in return forecast than the alternative combination strategies which reverse the order of combination strategy. Furthermore, the forecast based on LASSO model selection can be significantly improved as well if the distributional information is further incorporated. In other word, aggregating distributional information via combining multiple quantiles estimators contributes to the improvement of forecasts obtained either from model combination or model selection. This paper not only investigates the forecast of conditional mean, but also studies the forecast of the whole distribution of future stock returns. The approaches of quantile combination together with either model combination or model selection turn out to deliver statistically and economically significant out-of-sample forecasts relative to a historical average benchmark. The third essay proposes a quantile-based approach to efficiently estimate the conditional beta coefficient without assuming a parametric structure on the distribution of data generating process. Multiple quantiles estimates are combined in a weighting scheme to utilize distributional information across different quantile of the distribution. Monte Carlo simulation demonstrated that combining multiple quantile estimates can substantially improve the estimation efficiency for beta risk estimates in the absence of Gaussian distribution. The robustness of quantile-based beta estimates are pronounced during financial crisis when the distribution of stock returns deviates most from normality. I also explored the performance of different beta estimators in an application of portfolio management analysis and found that beta estimates from the proposed quantile combination approaches are superior to the OLS estimates in constructing Global Minimum Variance Portfolio, which generates lower variance of portfolio but does not come at the expense of persistent lower returns. / Thesis (PhD) — Boston College, 2013. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.