Evaluation of Volatility Forecasting Models in Vietnam Stock Markets

This study aims to find the most appropriate model(s) to estimate and forecast volatility in Vietnam stock markets. Considered volatility models in this study include RiskMetrics, GARCH, EGARCH, IGARCH, FIGARCH and APARCH. The forecast performance evaluations are conducted with two Vietnam stock indices – VNI-index and HNX-index. Selected data periods is from 01 March 2002 to 30 June 2011 for VNI-index and the period for HNX-index spans from 01 June 2006 through 30 June 2011. Symmetric loss functions and asymmetric loss functions are used as basic analysis criteria. Robust conclusions are achieved with the superior predictive ability (SPA) test, the model confidence set (MCS) procedure and Value-at-Risk (VaR) forecast evaluation. The general empirical results generated from symmetric loss functions, the SPA test and the MCS procedure demonstrate that for VNI-index, RiskMetrics and EGARCH have equally best forecast performance while for HNX-index, only EGARCH has the best. However, there are contrast findings resulted from different assessment criteria specifically with asymmetric loss functions and VaR forecast. Actually, the ranking of models is sensitive to the selected criterion. Therefore, selecting reasonable evaluation criteria is very critical and it must be established on the ultimate aims of the forecasting procedure.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Does transparency come at the cost of charitable services? Evidence from investigating British charities

Recent high-profile scandals related to misuse of funding and donations have raised the demand for scrutiny over financial transparency and operational activities of non-profit organizations in developed countries. Our analysis challenges the common practice in the sector of using programme ratios and overhead costs as indicators for non-profit accountability. Using Benford's Law to measure irregularities in financial data for a large sample of public charities we estimate that 25% of the sample potentially misreport their financial information. We show theoretically and empirically that charities with a higher programme ratio (their level of spending on charitable activities), will be less likely to misreport their financial information only when their overhead costs (spending on governing activities) are also sufficiently high. Tighter monitoring becomes ineffective in increasing the sectoral transparency and accountability unless accompanied by a sufficiently high level of charitable spending

Agentenbasierter Programmassistent zur Verwaltung von NC-Informationen in Produktionssystemen mit Kommunikationsnetzwerken

In den letzten Jahren hat sich die rapide Entwicklung der Elektrotechnik ebenso wie die der Softwaretechnologie auf die numerischen Steuerungen in den heutigen CNC-Maschinen groß ausgewirkt. Diese numerischen Steuerungen sind sowohl intelligenter und flexibler als auch mit größerer Internspeicherkapazität ausgerüstet. Dies führt zu einer Änderung der Art und Weise, wie DNC-Systeme zu etablieren sind, besonders solcher, die auf bisher verfügbaren, aber ungleichartigen DNC-Systemen basieren. In einem solch heterogenen DNC-System wird Datenspeicherungsfähigkeit stärker verteilt angeordnet, d.h., sie ist nicht nur in einem zentralen DNC-Server vorhanden, sondern auch in Terminals oder Steuerungen selbst angelagert. Diese Änderung des Archivierungsmittels benötigt neue DNC-Software, die die DNC-Grundfunktionen voll realisiert. Zudem sollte sie auch den neuen spezifischen Softwareanforderungen entsprechen und erlauben, neue Funktionen, z.B. Maschinendatenerfassung, Betriebsdatenerfassung usw., als Module hinzuzufügen. Derzeit wird die Agententechnologie bzw. ein MAS (Multiagentensystem) als ein aussichtsreicher Ansatz angesehen, um die Probleme der heutigen komplexen Softwaresysteme, wie ungleichartige Systemumgebungen und verteilte Strukturen, zu lösen. Die vorliegende Arbeit stellt die Idee zum Aufbau eines heterogenen DNC-Systems und die Konzipierung zur Gestaltung der agentenbasierten DNC-Software vor. Ausgehend von dem vorgestellten Lösungskonzept wird zudem der Programmassistent als erster Modul der agentenbasierten DNC-Software präsentiert.In the network-based DNC systems and especially heterogeneous DNC systems data get more distributed due to the ability to store not only in the DNC Server but also in the CNC controller or CNC Terminal. This leads a challenge to the DNC software in the implementation of its basic functions. The agent-based DNC software with assistants (ADNC) is suggested to solve the above problem. Its tasks are to collect distributed NC information and transfer data safely as well as performing other extended functions, i.e. NC program generation, machine data collection, production data collection, control machines in system, etc. The present work presented the concept to develop the ADNC and its first prototype. This prototype was developed in a process using a framework of agent-based assistants, called AgentAP. It is applicable on distributed manufacturing data and had been implemented on the agent platform JADE. The module Program Assistant, one of these prototype modules, which is responsible for management, bidirectional transfer, and monitoring change of NC programs, is also discussed

Exploring the ACIS Community through the Analysis of Co-authorship across Institutions

Population-focused care is gaining importance due to an increase in the number of people with long-term conditions. A population-focused care addresses the care needs of a group of patients who share a common trait. Primary health care (PHC) being the first point of contact with a health system, our work aims to predict and analyse this population-level workload at a PHC centre. We followed a design science research (DSR) to develop a workload prediction model. As a part of this work, we identified that current patient information models lack the ability to support population-level analysis. In this paper, we discuss an extended ontology of patient information models to support population-level workload analysis. We describe the three cycles of DSR applied to develop our ontology. Then, we discuss the existing health data models. Thus, this paper makes a domain-specific application of DSR to develop a patient information model that supports population-level analysis

Donors and recipients: charities, NGOs and aid

Non-profit organisations (NPOs) play an integral part in delivering public services and channelling development aid around the world. This thesis contains three papers on behaviour, motivations, and the accountability of these organisations. The first paper studies charitable spending and financial transparency of public charities in a developed NPO sector. Its accountability has attracted considerable scrutiny after high-profile scandals related to misuses of funding and donations. We use Benford's Law to evaluate the potential errors in public financial figures of approximately 10,000 UK charities. We estimate 25% of the sample misreport their financial information. We show unless spending on governing activities (commonly referred to as overhead cost) is sufficiently high, NPOs with higher spending on charitable activities (commonly referred to as programme ratio) will be more likely to misreport their financial information. We suggest that tighter monitoring might be ineffective to increase the sectoral transparency and accountability. Our analysis also challenges the common practice in the sector that programme ratios and overhead costs should be used as reliable indicators for non-profit accountability. The second paper focuses on performance evaluation in a development NGO context. Little has been done to understand the connection between the effectiveness of NGOs and their financial accountability. Using Benford’s Law and a representative survey of the Ugandan NGO sector, we also estimate 25% of the NGOs might provide misleading accounts. We observe NGOs with better ratings from their beneficiaries are more likely to submit credible financial data. The result contradicts the belief that upward accountability demands crowd out serving the client community. We find no evidence for a strong correlation between the decision to withhold requested financial information and the decision to report inaccurately, with the former potentially due to limited capacity and skills. The results suggest a more significant role for beneficiary assessments in monitoring the sector rather than increasing demand for financial reporting. The third paper studies behavioural motivators of development NGOs. We identify two motivations underlying NGO decision to diversify activities, namely to reduce idiosyncratic risk to funding and to derive personal gains. We exploit a historic flood in mid-2007 in Uganda and variations in contractual funding toward affected areas to show that NGOs diversify less in response to increased income from contractual funding. This result is consistent with a theoretical prediction that the decision is driven by the need to reduce risk rather than to capture private gains. Donors can help development NGOs focus on their primary mission by providing a commitment to funding