Analysis of operational risk of banks – catastrophe modelling

Nowadays financial institutions due to regulation and internal motivations care more intensively on their risks. Besides previously dominating market and credit risk new trend is to handle operational risk systematically. Operational risk is the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events. First we show the basic features of operational risk and its modelling and regulatory approaches, and after we will analyse operational risk in an own developed simulation model framework. Our approach is based on the analysis of latent risk process instead of manifest risk process, which widely popular in risk literature. In our model the latent risk process is a stochastic risk process, so called Ornstein- Uhlenbeck process, which is a mean reversion process. In the model framework we define catastrophe as breach of a critical barrier by the process. We analyse the distributions of catastrophe frequency, severity and first time to hit, not only for single process, but for dual process as well. Based on our first results we could not falsify the Poisson feature of frequency, and long tail feature of severity. Distribution of “first time to hit” requires more sophisticated analysis. At the end of paper we examine advantages of simulation based forecasting, and finally we concluding with the possible, further research directions to be done in the future.

Az európai uniós támogatások hatékonysága és hatásossága közötti különbség a ROP 1.2 intézkedésnél (The difference between the efficiency and effectiveness of using the EU-subsidies at Regional Operational Program)

A szerző cikkében megpróbál rávilágítani annak fontosságára, hogy az Európai Unióból érkező fejlesztési támogatások hasznosulása és a támogatási rendszer hatékonysága között jelentős különbség van. Ha nem tudjuk hatékonyan és hatásosan felhasználni az Unióból érkező pénzügyi eszközöket, akkor a cél: a kohézió, a konvergencia az Európai Unió régi tagállamainak fejlettségi szintjéhez, jólétéhez még nehezebben és lassabban érhető el. Az uniós támogatások hatékonysága alapvetően a rendelkezésre álló pénz lekötésének, lehívásának arányából, illetve a lekötött, lehívott és esetleg visszafizetett összeg arányából állapítható meg (kvantitatív megközelítés). A támogatások felhasználásának hatékonyságánál bonyolultabb, jóval összetettebb megközelítést igényel a hatásosság fogalma. A felhasználás hatásosságát a projektszinten a támogatás hatására megtermelt hozzáadott értékkel, programszinten a GDP hozzáadott növekedéssel lehet kifejezni. A cikk alapvetően a ROP 1.2 "Turisztikai fogadóképesség javítása" pályázati kiírás nyertes projektjeinél végzett kutatás eredményein keresztül kívánja szemléltetni a projektszintű vagy mikro hatásosság fontosságára (kvalitatív megközelítés). _________ The author tries to highlight the importance the difference between the efficiency and effectiveness of using the EU-subsidies. If Hungary cannot use the financial means of the EU efficiently and effectively, than the goal: cohesion and convergence to the level of the old, developed countries of the EU will be much harder and slowly. The efficiency of the EU-subsidies can be measured by the ratio of the amount of money obliged and the amount of money spent, and by the amount of money withdrawn by the Commission, which is actually lost (quantitative approach). The effectiveness of EU-subsidies needs a much more complicated and complex approach, than the efficiency. The effectiveness of usage on project level can be measured by the "added value" of the project, on program level by the added GDP growth or employment. The article is analysing basically the results of a survey made among the winner project of the application ROP 1.2 (Regional Operational Program 1.2) Improving the capacity for tourism (project level or micro effectiveness – qualitative approach).

The impact of external market factors on operational practices and performance of companies

The links between operational practices and performance are well studied in the literature, both theoretically and empirically. However, mostly internal factors are inspected more closely as the basis of operational performance, even if the impact of external, environmental factors is often emphasized. Our research fills a part of this existing gap in the literature. We examine how two environmental factors, market dynamism and competition impact the use of some operational practices (such as quality improvement, product development, automation, etc.) and the resulting operations and business performance. The method of path analysis is used. Data were acquired through an international survey (IMSS – International Manufacturing Strategy Survey), which was executed in 2005, in 23 participating countries in so called "innovative" industries (ISIC 28-35) with a sample of 711 firms. Results show that both market dynamism and competition have large impact on business performance, but the indirect effects, through operations practices are rather weak compared to direct ones. The most influential practices are from the area of process and control, and quality management.

Facets of operational performance in an emergency room (ER)

This paper, using detailed time measurements of patients complemented by interviews with hospital management and staff, examines three facets of an emergency room's (ER) operational performance: (1) effectiveness of the triage system in rationing patient treatment; (2) factors influencing ER's operational performance in general and the trade-offs in flow times, inventory levels (that is the number of patients waiting in the system), and resource utilization; (3) the impacts of potential process and staffing changes to improve the ER's performance. Specifically, the paper discusses four proposals for streamlining the patient flow: establishing designated tracks (fast track, diagnostic track), creating a holding area for certain type of patients, introducing a protocol that would reduce the load on physicians by allowing a registered nurse to order testing and treatment for some patients, and potentially and in the longer term, moving from non-ER specialist physicians to ER specialists. The paper's findings are based on analyzing the paths and flow times of close to two thousand patients in the emergency room of the Medical Center of Leeuwarden (MCL), The Netherlands. Using exploratory data analysis the paper presents generalizable findings about the impacts of various factors on ER's lead-time performance and shows how the proposals fit with well-documented process improvement theories. © 2010 Elsevier B.V. All rights reserved.

A disztribúció kiszervezéséhez kapcsolódó ellátási és működési kockázatok (Supply and operational risks in the outsourcing of distribution management)

A cikk célja, hogy elemző bemutatását adja az ellátási láncok működéséhez, különösen a disztribúciós tevékenység kiszervezéséhez kapcsolódó működési kockázatoknak. Az írás első része az irodalomkutatás eredményeit feldolgozva az ellátási láncok kockázati kitettségének növekedése mögött rejlő okokat törekszik feltárni, s röviden bemutatja a vállalati kockázatkezelés lehetséges lépéseit e téren. A cikk második gondolati egysége mélyinterjúk segítségével összefoglalja és rendszerezi a disztribúció kiszervezéséhez kapcsolódó kockázatokat, számba veszi a kapcsolódó kockázatkezelési lehetőségeket, s bemutatja a megkérdezett vállalatok által alkalmazott kockázat-megelőzési alternatívákat. ______ The aim of this paper is to introduce operational risks of supply chains, especially risks deriving from the outsourcing of distribution management. Based on literature review the first part of the paper talks about the potential reasons of increasing global supply chain risks, and the general business activities of risk assessment. Analyzing the results of semi-structured qualitative interviews, the second part summarizes the risks belonging to the outsourcing of distribution and introduces the potential risk assessment and avoidance opportunities and alternatives in practice.

eBEST platform a KKV-klaszterek operatív és együttműködési folyamatainak támogatására (eBEST platform for supporting operational and cooperative processes of SME's clusters)

Az Európai Bizottság jelentése szerint a magyar kis- és középvállalkozások helyzete 2005 óta stagnál. Bár ezek a vállalkozások adják a magyar vállalkozások 99%-át, mégis a közbeszerzési, valamint a növekvő piacokhoz való hozzáférés terén számos akadállyal kerülnek szembe. Az eBEST projekten (Empowering Business Ecosystems of Small Service Enterprises to Face the Economic Crisis) belül kialakított platform olyan funkcionalitással bír, ami mindamellett, hogy lehetővé teszi a vállalkozások szervezett csoportokba, azaz ökoszisztémákba rendeződését, hozzá tud járulni a fogyasztói igények kielégítése érdekében létrejövő ellátási lánc, illetve egyedi folyamatok mentén fellépő információszerzési, kommunikációs vagy együttműködési akadályok lebontásához. ____ It is widely recognised that the most important factor for increasing the productivity of small companies is a deep adoption of computer-based applications and services. The FP7 SME eBEST project proposed a new operational environment specifically conceived for net worked small companies, supported by an advanced suite of ICT services, the eBEST platform. The paper aims at presenting the projects achievements that are validated by a number of company clusters of different EU countries and industry sectors. The general objectives of the eBEST project are attracting customers to work with the clustered companies, facilitating companies to collaborate with each other, and enabling associations to foster the devised innovation.

Development of operational performance models for truck-lane restrictions on freeway corridors

Highways are generally designed to serve a mixed traffic flow that consists of passenger cars, trucks, buses, recreational vehicles, etc. The fact that the impacts of these different vehicle types are not uniform creates problems in highway operations and safety. A common approach to reducing the impacts of truck traffic on freeways has been to restrict trucks to certain lane(s) to minimize the interaction between trucks and other vehicles and to compensate for their differences in operational characteristics. ^ The performance of different truck lane restriction alternatives differs under different traffic and geometric conditions. Thus, a good estimate of the operational performance of different truck lane restriction alternatives under prevailing conditions is needed to help make informed decisions on truck lane restriction alternatives. This study develops operational performance models that can be applied to help identify the most operationally efficient truck lane restriction alternative on a freeway under prevailing conditions. The operational performance measures examined in this study include average speed, throughput, speed difference, and lane changes. Prevailing conditions include number of lanes, interchange density, free-flow speeds, volumes, truck percentages, and ramp volumes. ^ Recognizing the difficulty of collecting sufficient data for an empirical modeling procedure that involves a high number of variables, the simulation approach was used to estimate the performance values for various truck lane restriction alternatives under various scenarios. Both the CORSIM and VISSIM simulation models were examined for their ability to model truck lane restrictions. Due to a major problem found in the CORSIM model for truck lane modeling, the VISSIM model was adopted as the simulator for this study. ^ The VISSIM model was calibrated mainly to replicate the capacity given in the 2000 Highway Capacity Manual (HCM) for various free-flow speeds under the ideal basic freeway section conditions. Non-linear regression models for average speed, throughput, average number of lane changes, and speed difference between the lane groups were developed. Based on the performance models developed, a simple decision procedure was recommended to select the desired truck lane restriction alternative for prevailing conditions. ^

High frequency electric machine models for the evaluation of operational impacts in integrated drives

A high frequency physical phase variable electric machine model was developed using FE analysis. The model was implemented in a machine drive environment with hardware-in-the-loop. The novelty of the proposed model is that it is derived based on the actual geometrical and other physical information of the motor, considering each individual turn in the winding. This is the first attempt to develop such a model to obtain high frequency machine parameters without resorting to expensive experimental procedures currently in use. The model was used in a dynamic simulation environment to predict inverter-motor interaction. This includes motor terminal overvoltage, current spikes, as well as switching effects. In addition, a complete drive model was developed for electromagnetic interference (EMI) analysis and evaluation. This consists of the lumped parameter models of different system components, such as cable, inverter, and motor. The lumped parameter models enable faster simulations. The results obtained were verified by experimental measurements and excellent agreements were obtained. A change in the winding arrangement and its influence on the motor high frequency behavior has also been investigated. This was shown to have a little effect on the parameter values and in the motor high frequency behavior for equal number of turns. An accurate prediction of overvoltage and EMI in the design stages of the drive system would reduce the time required for the design modifications as well as for the evaluation of EMC compliance issues. The model can be utilized in the design optimization and insulation selection for motors. Use of this procedure could prove economical, as it would help designers develop and test new motor designs for the evaluation of operational impacts in various motor drive applications.

Text analytics of social media: Sentiment analysis, event detection and summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. ^ Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. ^ In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data. ^

Development of distributed generation infrastructure for microgrid connectivity to operational power systems

Distributed Generation (DG) from alternate sources and smart grid technologies represent good solutions for the increase in energy demands. Employment of these DG assets requires solutions for the new technical challenges that are accompanied by the integration and interconnection into operational power systems. A DG infrastructure comprised of alternate energy sources in addition to conventional sources, is developed as a test bed. The test bed is operated by synchronizing, wind, photovoltaic, fuel cell, micro generator and energy storage assets, in addition to standard AC generators. Connectivity of these DG assets is tested for viability and for their operational characteristics. The control and communication layers for dynamic operations are developed to improve the connectivity of alternates to the power system. A real time application for the operation of alternate sources in microgrids is developed. Multi agent approach is utilized to improve stability and sequences of actions for black start are implemented. Experiments for control and stability issues related to dynamic operation under load conditions have been conducted and verified.

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

Classificazione e selezione di tecniche di visualizzazione per Big Data Analytics

La tesi presenta uno studio della libreria grafica per web D3, sviluppata in javascript, e ne presenta una catalogazione dei grafici implementati e reperibili sul web. Lo scopo è quello di valutare la libreria e studiarne i pregi e difetti per capire se sia opportuno utilizzarla nell'ambito di un progetto Europeo. Per fare questo vengono studiati i metodi di classificazione dei grafici presenti in letteratura e viene esposto e descritto lo stato dell'arte del data visualization. Viene poi descritto il metodo di classificazione proposto dal team di progettazione e catalogata la galleria di grafici presente sul sito della libreria D3. Infine viene presentato e studiato in maniera formale un algoritmo per selezionare un grafico in base alle esigenze dell'utente.