Web-Based Information Systems in the Stock Market Financial Information Domain

The information domain is a recognised sphere for the influence, ownership, and control of information and it's specifications, format, exploitation and explanation (Thompson, 1967). The article presents a description of the financial information domain issues related to the organisation and operation of a stock market. We review the strategic, institutional and standards dimensions of the stock market information domain in relation to the current semantic web knowledge and how and whether this could be used in modern web based stock market information systems to provide the quality of information that their stakeholders want. The analysis is based on the FINE model (Blanas, 2003). The analysis leads to a number of research questions for future research.

Managing the transition to IFRS-based financial reporting

This book provides a practical guide for accountants working in practice or in business faced with the complexity of moving to adopt IFRS-based financial reporting. The book offers not only an overview of the regulatory framework and the requirements to produce IFRS-compliant financial statements but also guidance on developing an implementation strategy including project management, identifying and responding to challenges, dealing with change management and communication with external stakeholders.

A válság mint negatív információ és bizonytalansági tényező. A válság hatása az egy részvényre jutó nyereség-előrejelzésekre (The financial crisis as negative information and a factor of uncertainty. Analysing the EPS forecasting error in Hungary and Austria)

A szerző a 2008-ban kezdődött gazdasági világválság hatását vizsgálja az egy részvényre jutó nyereség előrejelzésének hibájára. Számos publikáció bizonyította, hogy az elemzők a tényértékeknél szisztematikusan kedvezőbb tervértéket adnak meg az egy részvényre jutó előrejelzéseikben. Más vizsgálatok azt igazolták, hogy az egy részvényre jutó előrejelzési hiba bizonytalan környezetben növekszik, míg arra is számos bizonyítékot lehet találni, hogy a negatív hírek hatását az elemzők alulsúlyozzák. A gazdasági világválság miatt az elemzőknek számtalan negatív hírt kellett figyelembe venniük az előrejelzések készítésekor, továbbá a válság az egész gazdaságban jelentősen növelte a bizonytalanságot. A szerző azt vizsgálja, hogy miként hatott a gazdasági világválság az egy részvényre jutó nyereség- előrejelzés hibájára, megkülönböztetve azt az időszakot, amíg a válság negatív hír volt, attól, amikor már hatásaként jelentősen megnőtt a bizonytalanság. _____ The author investigated the impact of the financial crisis that started in 2008 on the forecasting error for earnings per share. There is plentiful evidence from the 1980s that analysts give systematically more favourable values in their earnings per share (EPS) forecasts than reality, i.e. they are generally optimistic. Other investigations have supported the idea that the EPS forecasting error is greater under uncertain environmental circumstances, while other researchers prove that the analysts under-react to the negative information in their forecasts. The financial crisis brought a myriad of negative information for analysts to consider in such forecasts, while also increasing the level of uncertainty for the entire economy. The article investigates the impact of the financial crisis on the EPS forecasting error, distinguishing the period when the crisis gave merely negative information, from the one when its effect of uncertainty was significantly increased over the entire economy.

The financial stability and access to financing of SMEs in Hungary

The present study was prepared within the framework of cooperation between the Competitiveness Research Centre, operating within the Institute of Business Economics of Corvinus University of Budapest, and the National Association of Entrepreneurs, based on a commission from the latter. Th e goal of the study was to survey the self-financing capabilities and borrowing opportunities of majority Hungarian-owned small and medium-sized enterprises (SMEs), and to identify potential problems. The results of the research revealed that the high proportion of owner’s equity in the financing structure is not due to difficulties with borrowing, but because enterprises that cover their fi nancing primarily from their own resources have other financing opportunities at their disposal. Although general satisfaction with banks shows a diminishing tendency, it can still be interpreted favourably. The majority of companies have not encountered serious borrowing difficulties. With regard to the system of competitive tenders, company managers have sensed some improvement, but general satisfaction is still lacking. Although the research results suggest that the primary obstacle to growth in 2013 was not the lack of credit or external funding, it is important to emphasize that start-ups, young enterprises and micro-enterprises, which struggle the most with financing worries, were not represented in the analysed database.

Putting Adequate Financial and Human Resources in Healthcare for Effective Universal Health Coverage in Kenya: Lessons and Experiences from China

In recent years, most low and middle-income countries, have adopted different approaches to universal health coverage (UHC), to ensure equity and financial risk protection in accessing essential healthcare services. UHC-related policies and delivery strategies are largely based on existing healthcare systems, a result of gradual development (based on local factors and priorities). Most countries have emphasized on health financing, and human resources for health (HRH) reform policies, based on good practices of several healthcare plans to deliver UHC for their population.

Health financing and labor market frameworks were used, to understand health financing, HRH dynamics, and to analyze key health policies implemented over the past decade in Kenya’s effort to achieve UHC. Through the understanding, policy options are proposed to Kenya; analyzing, and generating lessons from health financing, and HRH reforms experiences in China. Data was collected using mixed methods approach, utilizing both quantitative (documents and literature review), and qualitative (in-depth interviews) data collection techniques.

The problems in Kenya are substantial: high levels of out-of-pocket health expenditure, slow progress in expanding health insurance among informal sector workers, inefficiencies in pulling of health are revenues, inadequate deployed HRH, maldistribution of HRH, and inadequate quality measures in training health worker. The government has identified the critical role of strengthening primary health care and the National Hospital Insurance Fund (NHIF) in Kenya’s move towards UHC. Strengthening primary health care requires; re-defining the role of hospitals, and health insurance schemes, and training, deploying and retaining primary care professionals according to the health needs of the population; concepts not emphasized in Kenya’s healthcare reforms or programs design. Kenya’s top leadership commitment is urgently needed for tougher reforms implementation, and important lessons from China’s extensive health reforms in the past decade are beneficial. Key lessons from China include health insurance expansion through rigorous research, monitoring, and evaluation, substantially increasing government health expenditure, innovative primary healthcare strengthening, designing, and implementing health policy reforms that are responsive to the population, and regional approaches to strengthening HRH.

Student Financial Aid:The Roles of Loans and Grants (Working Paper 37)

This paper addresses the roles of loans and grants as forms of student financial aid. It begins with a simple choice model where individuals decide to pursue post-secondary studies if i) the net benefits of doing so are positive and ii) no financing or liquidity constraints stand in their way. The effects of loans and grants on these two elements of the schooling decision are then discussed. It is argued that based on equity, efficiency, and fiscal considerations, loans are generally best suited for helping those who want to go but face financing constraints, whereas grants are more appropriate for increasing the incentives for individuals from disadvantaged backgrounds to further their studies. Loan subsidies, which make loans part-loan and part-grant, are also discussed, including how they might be used to address “debt aversion”. Given that subsidised loans have a grant (subsidy) element, while grants help overcome the credit constraints upon which loans are targeted, the paper then attempts to establish some general rules for providing loans, for subsidising the loans awarded, and for giving “pure” grants. It concludes with an application of these principles in the form of a recent proposal for reforming the student financial system in Canada. *

La ética hacker frente al capitalismo netárquíco: software libre y peer production en las iniciativas de Economía Colaborativa en Andalucía

En los últimos años el término Economía Colaborativa se ha popularizado sin que, hasta el momento, haya sido definido de manera inequívoca. Bajo esta denominación se engloban experiencias tan diversas como bancos de tiempo, huertos urbanos, startups o grandes plataformas digitales. La proliferación de este tipo de iniciativas puede relacionarse con una multiplicidad de factores tales como el desarrollo tecnológico, la recesión económica y otras crisis superpuestas (medioambiental, de cuidados, de valores, de lo político) y un cierto cambio en los valores sociales. Entre 2014-2015 se han realizado dos investigaciones en Andalucía de manera casi paralela y con una metodología similar. La primera de ellas pretendía identificar prácticas de Economía Colaborativa en el entorno universitario. La segunda investigación identificaba experiencias de emprendimiento a nivel autonómico. A luz de los resultados obtenidos se plantea la siguiente cuestión sobre la naturaleza misma de la Economía Colaborativa: ¿nos encontramos ante prácticas postcapitalistas que abren el camino a una sociedad más justa e igualitaria o, más bien, estamos ante una respuesta del capital para, una vez más, seguir extrayendo de manera privada el valor que se genera socialmente? Este artículo, partiendo del análisis del conjunto de iniciativas detentadas en Andalucía, se centra en aquellas basadas en el software libre y la producción digital concluyendo cómo, gracias a la incorporación de ciertos aspectos de la ética hacker y las lógicas del conocimiento abierto, éstas pueden situarse dentro de un escenario de fomento de los comunes globales frente a las lógicas imperantes del capitalismo netárquico. 

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Financial Inclusion of The Small and Marginal Farmers by the Banking Sector in Kerala

Financial inclusion for inclusive growth is central to the developmental philosophy of most of the nations over the past decade. It has been a priority for policy makers and regulators in financial sector development for improving access and usage of financial services to achieve comprehensive financial inclusion. The initiatives taken towards financial inclusion can promote a more effective and efficient process to achieve significant improvements in financial inclusion are to establish and achieve shared and sustainable development and growth. Realising this, an increasing number of countries are committing to promote financial inclusion, encouraged by the growing body of country level experiences (World Bank, 2012). Financial inclusion basically means, broad based growth through participation as well as sharing the benefits from the growth process along with the under privileged and marginal segments of the economy. Evidence suggests that it has substantial benefits for equitable and sustainable growth. Inclusive growth ensures that while economy grows rapidly, all segments of society are involved in this growth process, ensuring equal opportunities, devoid of any regional or sectoral disparitiesIt is widely acknowledged that the objective ofinclusive growth is accomplished through the process of financial inclusion. Financial inclusion envisages bringing everyone, irrespective of financial status, into the banking fold for the individual progress and development and thereby achieving comprehensive growth with equity

Il crowdfunding come forma alternativa ed innovativa al finanziamento di una start-up: il caso Look Ahead

Il seguente percorso di tesi si articola in due parti. Nella prima si andranno ad illustrare le varie possibili fonti di finanziamento alle quali uno o più imprenditori potranno rivolgersi nella creazione di una nuova impresa, con una attenzione particolare a quello che è il crowdfunding, o finanziamento collettivo, considerato una alternativa valida e innovativa alle forme tradizionali per raccogliere i capitali necessari. Nella seconda parte sarà presentata la startup italiana Look Ahead, di cui il sottoscritto ne rappresenta una delle menti, come esempio di una startup che ha scelto di usufruire di questo particolare tipo di finanziamento. In particolare, ne sarà ricostruito l’intero Business Plan redatto in sede accademica, in modo da mettere in evidenza le caratteristiche del prodotto offerto, il segmento di mercato servito, il modello di business e l’analisi finanziaria.

Effects of IFRS adoption on the financial statements of Nigerian listed entities: the case of oil and gas companies

On 28 July 2010, the Nigerian Federal Executive Council approved January 1, 2012 as the effective date for the convergence of Nigerian Statement of Accounting Standards (SAS) or Nigerian GAAP (NG-GAAP) with International Financial Reporting Standards (IFRS). By this pronouncement, all publicly listed companies and significant public interest entities in Nigeria were statutorily required to issue IFRS based financial statements for the year ended December, 2012. This study investigates the impact of the adoption of IFRS on the financial statements of Nigerian listed Oil and Gas entities using six years of data which covers three years before and three years after IFRS adoption in Nigeria and other African countries. First, the study evaluates the impact of IFRS adoption on the Exploration and Evaluation (E&E) expenditures of listed Oil and Gas companies. Second, it examines the impact of IFRS adoption on the provision for decommissioning of Oil and Gas installations and environmental rehabilitation expenditures. Third, the study analyses the impact of the adoption of IFRS on the average daily Crude Oil production cost per Barrel. Fourth, it examines the extent to which the adoption and implementation of IFRS affects the Key Performance Indicators (KPIs) of listed Oil and Gas companies. The study further explores the impact of IFRS adoption on the contractual relationships between Nigerian Government and Oil and Gas companies in terms of Joint Ventures (JVs) and Production Sharing Contracts (PSCs) as it relates to taxes, royalties, bonuses and Profit Oil Split. A Paired Samples t-test, Wilcoxon Signed Rank test and Gray’s (Gray, 1980) Index of Conservatism analyses were conducted simultaneously where the accounting numbers, financial ratios and industry specific performance measures of GAAP and IFRS were computed and analysed and the significance of the differences of the mean, median and Conservatism Index values were compared before and after IFRS adoption. Questionnaires were then administered to the key stakeholders in the adoption and implementation of IFRS and the responses collated and analysed. The results of the analyses reveal that most of the accounting numbers, financial ratios and industry specific performance measures examined changed significantly as a result of the transition from GAAP to IFRS. The E&E expenditures and the mean cost of Crude Oil production per barrel of Oil and Gas companies increased significantly. The GAAP values of inventories, GPM, ROA, Equity and TA were also significantly different from the IFRS values. However, the differences in the provision for decommissioning expenditures were not statistically significant. Gray’s (Gray, 1980) Conservatism Index shows that Oil and Gas companies were more conservative under GAAP when compared to the IFRS regime. The Questionnaire analyses reveal that IFRS based financial statements are of higher quality, easier to prepare and present to management and easier to compare among competitors across the Oil and Gas sector but slightly more difficult to audit compared to GAAP based financial statements. To my knowledge, this is the first empirical research to investigate the impact of IFRS adoption on the financial statements of listed Oil and Gas companies. The study will therefore make an enormous contribution to academic literature and body of knowledge and void the existing knowledge gap regarding the impact and implications of IFRS adoption on the financial statements of Oil and Gas companies.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.

Forecasting exchange rates in the presence of instabilities

Many exchange rate papers articulate the view that instabilities constitute a major impediment to exchange rate predictability. In this thesis we implement Bayesian and other techniques to account for such instabilities, and examine some of the main obstacles to exchange rate models' predictive ability. We first consider in Chapter 2 a time-varying parameter model in which fluctuations in exchange rates are related to short-term nominal interest rates ensuing from monetary policy rules, such as Taylor rules. Unlike the existing exchange rate studies, the parameters of our Taylor rules are allowed to change over time, in light of the widespread evidence of shifts in fundamentals - for example in the aftermath of the Global Financial Crisis. Focusing on quarterly data frequency from the crisis, we detect forecast improvements upon a random walk (RW) benchmark for at least half, and for as many as seven out of 10, of the currencies considered. Results are stronger when we allow the time-varying parameters of the Taylor rules to differ between countries. In Chapter 3 we look closely at the role of time-variation in parameters and other sources of uncertainty in hindering exchange rate models' predictive power. We apply a Bayesian setup that incorporates the notion that the relevant set of exchange rate determinants and their corresponding coefficients, change over time. Using statistical and economic measures of performance, we first find that predictive models which allow for sudden, rather than smooth, changes in the coefficients yield significant forecast improvements and economic gains at horizons beyond 1-month. At shorter horizons, however, our methods fail to forecast better than the RW. And we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients variability to incorporate in the models, as the main factors obstructing predictive ability. Chapter 4 focus on the problem of the time-varying predictive ability of economic fundamentals for exchange rates. It uses bootstrap-based methods to uncover the time-specific conditioning information for predicting fluctuations in exchange rates. Employing several metrics for statistical and economic evaluation of forecasting performance, we find that our approach based on pre-selecting and validating fundamentals across bootstrap replications generates more accurate forecasts than the RW. The approach, known as bumping, robustly reveals parsimonious models with out-of-sample predictive power at 1-month horizon; and outperforms alternative methods, including Bayesian, bagging, and standard forecast combinations. Chapter 5 exploits the predictive content of daily commodity prices for monthly commodity-currency exchange rates. It builds on the idea that the effect of daily commodity price fluctuations on commodity currencies is short-lived, and therefore harder to pin down at low frequencies. Using MIxed DAta Sampling (MIDAS) models, and Bayesian estimation methods to account for time-variation in predictive ability, the chapter demonstrates the usefulness of suitably exploiting such short-lived effects in improving exchange rate forecasts. It further shows that the usual low-frequency predictors, such as money supplies and interest rates differentials, typically receive little support from the data at monthly frequency, whereas MIDAS models featuring daily commodity prices are highly likely. The chapter also introduces the random walk Metropolis-Hastings technique as a new tool to estimate MIDAS regressions.

Potential of civic crowdfunding to the intelligence of cities and social innovation: an exploratory study

The concepts of smart city and social innovation in combination with the increasing use of ICT by citizens and public authorities could enhance the involvement of people on the decisions that directly affect their daily life. A case study approach was adopted to illustrate the potential of civic crowdfunding for increasing the participation and collaboration between citizens, firms and government. The analysis of two exemplary cases shows that civic crowdfunding platforms could be used by public administration to engage communities in the search of solutions to local problems. Likewise, it could be used to reinforce the community ties and to leverage the bonds among the stakeholders and the partners of the community ecosystem.