Risk Management

This treatise delves into the latest advancements in stochastic volatility models, highlighting the utilization of Markov chain Monte Carlo simulations for estimating model parameters and forecasting the volatility and quantiles of financial asset returns. The modeling of financial time series volatility constitutes a crucial aspect of finance, as it plays a vital role in predicting return distributions and managing risks. Among the various econometric models available, the stochastic volatility model has been a popular choice, particularly in comparison to other models, such as GARCH models, as it has demonstrated superior performance in previous empirical studies in terms of fit, forecasting volatility, and evaluating tail risk measures such as Value-at-Risk and Expected Shortfall. The book also explores an extension of the basic stochastic volatility model, incorporating a skewed return error distribution and a realized volatility measurement equation. The concept of realized volatility, a newly established estimator of volatility using intraday returns data, is introduced, and a comprehensive description of the resulting realized stochastic volatility model is provided. The text contains a thorough explanation of several efficient sampling algorithms for latent log volatilities, as well as an illustration of parameter estimation and volatility prediction through empirical studies utilizing various asset return data, including the yen/US dollar exchange rate, the Dow Jones Industrial Average, and the Nikkei 225 stock index. This publication is highly recommended for readers with an interest in the latest developments in stochastic volatility models and realized stochastic volatility models, particularly in regards to financial risk management.

In Anbetracht der aktuellen Krisensituation besitzt die Risikoberichterstattung von Unternehmen weiterhin eine hohe Relevanz. Während bisherige Studien auf extern publizierte Risikoinformationen fokussieren, zeichnet die vorliegende Forschungsarbeit erstmals ein umfassendes Bild über die inhaltliche und prozessuale Ausgestaltung des internen Risiko-Reportings. Im Rahmen einer Feldstudie führte die Autorin dazu Interviews mit Risikomanagern aus 34 bedeutsamen Unternehmen der deutschen Wirtschaft, wodurch neben zumeist vertraulichen Daten auch interne Risikoberichte erhoben werden konnten. Die Ergebnisse der Studie zeigen, dass der Risikomanager eine zentrale Einflussgröße der Berichtsqualität darstellt und dadurch eine besondere Bedeutung im internen Risiko-Reporting-Prozess besitzt. Durch die Wahrnehmung verschiedener Rollen obliegen dem Risikomanager dabei zahlreiche Tätigkeiten, welche unterschiedliche Kompetenzen erfordern. Zudem werden aufgrund einer Vielzahl an Schnittstellen zu Unternehmensakteuren diverse Erwartungen an den Risikomanager gestellt, sodass sich ein umfassendes, komplexes und zum Teil heterogenes Anforderungsprofil ergibt. In Ableitung aus den Ergebnissen der Untersuchung zeichnet die Autorin ein Rollen-, Tätigkeits- und Kompetenzprofil des Risikomanagers sowie seine Einflussmöglichkeiten auf die Informationsqualität in der internen Risikoberichterstattung.

This book presents the selected proceedings of 2nd International Conference on Recent Advances in Manufacturing (RAM 2021). The book provides insights to current research trends and opportunities in modelling and optimization of manufacturing processes and systems. The topics covered include modelling analysis, computing and simulation, traditional and non-traditional optimization techniques, surface coating methods, additive manufacturing processes, CAD/CAM, robotics and automation, welding and joining processes, supply chain management and CAE and reverse engineering. This book will be a good reference for beginners, researchers and professionals interested in modelling and optimization related to manufacturing engineering and related fields.

This book covers sustainable development in smart society's 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.

This book addresses reliability, maintenance, risk, and safety issues of industrial systems with applications of the latest decision-making techniques. Thus, this book presents chapters that apply advanced tools, techniques, and computing models for optimizing the performance of industrial and manufacturing systems, along with other complex engineering equipment. Computing techniques like data analytics, failure mode and effects analysis, fuzzy set theory, petri-net, multi-criteria decision-making (MCDM), and soft computing are used for solving problems of reliability, risk, and safety related issues.

Die Gestaltung des Anlaufs für neue Produkte gewinnt für die Unternehmen zunehmend an Bedeutung. Risiken und Störfaktoren nehmen Einfluss auf das Erreichen geplanter Zielstellungen. Insbesondere für Entscheidungsträger mittelständischer Unternehmen besteht vor diesem Hintergrund der Bedarf, eine strukturierte Vorgehensweise zur Unterstützung der Zielerreichung zu erhalten. Jörg Nagel untersucht entsprechend des zeitlichen Horizonts strategische und operative Inhalte eines risikoorientierten Anlaufmanagements. Er entwickelt eine Methodik zur Unterstützung der Planung und Steuerung des Anlaufs unter Risikogesichtspunkten.

While mainstream financial theories and applications assume that asset returns are normally distributed, overwhelming empirical evidence shows otherwise. Yet many professionals don't appreciate the highly statistical models that take this empirical evidence into consideration. Fat-Tailed and Skewed Asset Return Distributions examines this dilemma and offers readers a less technical look at how portfolio selection, risk management, and option pricing modeling should and can be undertaken when the assumption of a non-normal distribution for asset returns is violated. Topics covered in this comprehensive book include an extensive discussion of probability distributions, estimating probability distributions, portfolio selection, alternative risk measures, and much more. Fat-Tailed and Skewed Asset Return Distributions provides a bridge between the highly technical theory of statistical distributional analysis, stochastic processes, and econometrics of financial returns and real-world risk management and investments.

Inkl. CD-ROM

Schützen Sie Ihr Unternehmen: Sicherheit mit StrukturWer Sicherheit wie Flickenschusterei betreibt, handelt fahrlässig! Nachhaltige IT-Sicherheit im Unternehmen benötigt einen systematischen und strukturierten Ansatz, an dem Sie sich orientieren können. Der Rahmen der ISO 27001 hilft Ihnen, relevante Risiken zu identifizieren, geeignete Schutzmaßnahmen einzuführen und die Sicherheit kontinuierlich zu verbessern. In diesem praxisorientierten Leitfaden zeigt Ihnen Andreas Wisler Schritt für Schritt, wie ein Information Security Management System (ISMS) aufgebaut, gelebt und erfolgreich zertifiziert wird. Konkrete Beispiele zeigen Ihnen, wie Unternehmen unterschiedlicher Größe ein ISMS eingeführt haben, praktische Tipps von der Risikoanalyse bis zum Audit helfen Ihnen bei der Umsetzung.- ISMS aufbauen und praktisch umsetzen- Vorbereitung auf Audits und Zertifizierung- Schnittstellen zu anderen Normen und StandardsAus dem Inhalt:- Was ist ein ISMS: Definition und Ziele- Abgrenzungen und Schnittstellen- Begriffe der Informationssicherheit- Die Normreihe 27000: Geschichte, Aufbau und Inhalt- Die Anhänge der Norm: organisatorische, personenbezogene, physische und technologische Maßnahmen- ISMS umsetzen: Vorgehen, Beispieldokumente und Ressourcen- Informationssicherheit messen: Kennzahlen, Metriken und Reifemodelle

This textbook teaches methods of data analytics for technical reliability analyses and risk prognosis on the basis of probabilistics, statistics and modelling. The methods of Reliability Engineering are applied in the elementary phases of the product emergence process (concept and series development, production) as well as during the field use of technical products. This book contains a detailed outline of the basics of statistics, graphical visualisation and calculation methods. Numerous case studies are discussed, representing typical tasks of the engineer in reliability analysis during development/production as well as during the assessment of field damages. The target groups are thus both engineering students and practitioning engineers who deal with technical reliability in the context of the development and manufacturing of complex technical products as well as field data analyses. The presentation of the methods and procedures of Reliability Engineering follows theguideline "theory-guided - practice-oriented", so that this book can be used both as a reference work and as a textbook.

The objective of the book is to adopt the application of data analytics to enhance the sustainability and resilience of the green supply chain networks. To demonstrate the applicability and usefulness of the method, the book adopts different data analytic models and approaches against the backdrop of case studies. In summary, this book attempts to address the question of methods, tools, and techniques that can be used to create resilient, anti-fragile, reliable, and invulnerable green supply chain networks.

"Cardiac Data Mining for Heart Disease Prediction from Biomedical Warehouses" by Mujtaba Ashraf Qureshi is a comprehensive study on the use of data mining techniques to predict heart disease using biomedical warehouses. Qureshi discusses the importance of data mining in healthcare and the potential benefits it can provide in the field of cardiac health.Through an extensive review of literature and experimentation, Qureshi explores the most effective data mining algorithms for heart disease prediction and examines the role of various risk factors. The author also discusses the challenges and limitations of cardiac data mining and offers potential solutions to overcome these obstacles.Whether you are a healthcare professional, researcher, or data scientist interested in the latest advancements in heart disease prediction, "Cardiac Data Mining for Heart Disease Prediction from Biomedical Warehouses" is an essential resource. Order your copy today and discover how data mining can help improve cardiac health outcomes.

This book covers recent research advances, methods and techniques, applications and projects in financial analytics, with a focus on the effects of the health crisis on banking activities and financial engineering. It explores the latest developments in banking regulation, banking and financial systems, financial engineering, and corporate finance in order to provide financial analytics that assess financial stability and sustainability. Written for researchers and practitioners alike, the book is intended to promote stimulating scientific exchanges, ideas and experiences in the field of financial analytics for economics and management.

This book presents body of knowledge on the economic, social and environmental impacts of the new Industry 4.0 technology use in view of regulating the related risks to ensure inclusive and sustainable growth in the Post-Soviet and selected developing countries while transition to a new technological order. The book brings together collected empirical evidence and pilot innovative research projects run by the author team that illustrate functional abilities, application potential and challenges of Industry 4.0 key enabling technologies (e.g., artificial intelligence, neural networks, blockchain, nanotechnology, etc.) and provides useful applied recommendations on managing the risks of their use in order to achieve economic growth fairly across society in the developed and developing countries. It presents suggestions to improve national legislation and existing economic regulations, which would also ensure boosting scientific research and training highly qualified personnel in computer, economic, administrative, legal and social sciences at the advanced universities and research institutions in the Post-Soviet area.

This book discusses the payout phase of the old-age pension saving scheme, the so-called effective premium, and offers detailed actuarial models and analyses of five old-age pension saving products used in practice. These include the basic permanent monthly annuity, without any benefits for survivors, as well as products which, in addition, also include benefits for survivors or authorized persons in the event of the pensioner's death. The purpose of the book is to point out the method of determining future old-age pensions from old-age pension savings, and to present the advantages and disadvantages of such a pension. The book also emphasizes the role of the profitability testing of the products and answers questions concerning the effectiveness of old-age pension savings and insurance. The book is primarily intended for students of actuarial and financial mathematics and future economists.

This book, besides discussing challenges and opportunities, will reveal the microbe-metal interactions and strategies for e-waste remediation in different ecosystems. It will unveil the recent biotechnological advancement and microbiological approach to sustainable biorecycling of e-waste such as bioleaching for heavy metal extraction, valorization of precious metal, biodegradation of e-plastic, the role of the diverse microbial community in e-waste remediation, genetically engineered microbes for e-waste management, the importance of microbial exopolysaccharides in metal biosorption, next-generation technologies, omics-based technologies etc. It also holds the promise to discuss the conservation, utilization and cataloging indigenous microbes in e-waste-polluted niches and promising hybrid technology for sustainable e-waste management.Revolution in the area of information technology and communication is constantly evolving due to scientific research and development.Concurrently, the production of new electrical and electronic equipment also thus uplifting in this era of revolution. These technological advancements certainly have problematic consequences which is the rise of huge amounts of electronic obsoletes or electronic waste (e-waste). Improper management of both hazardous and nonhazardous substances of e-waste led to a major concern in our digital society and environment. Therefore, a sustainable approach including microbial candidates to tackle e-waste is the need of the hour.Nevertheless, the continuous demand for new-generation gadgets and electronics set this high-tech evolution to a new frontier in the last few years. With this continuing trend of technological development, e-waste is expanding exponentially worldwide. In the year of 2019, the worldwide generation of e-waste was approximately 53.6 Mt, of which only about 17.4% of e-waste was collected and recycled, and the other 82.6% was not even documented. E-waste containsvarious heterogeneous waste complexes such as metals (60%), blends of many polymers (30%) and halogenated compounds, radioactive elements and other pollutants (10%), respectively. The sustainable, efficient, and economic management of e-waste is thus, a challenging task today and in the coming decades. Conventional techniques such as the use of chemicals, incineration and informal ways of e-waste dismantling trigger serious health risks and contamination to the human population and environment, respectively due to the liberation of toxic and hazardous substances from the waste. In this context, bio-candidates especially microorganisms could be sharp-edged biological recycling tools to manage e-waste sustainably. As microbes are omnipresent and diverse in their physiology and functional aspects, they offer a wide range of bioremediation.

Learn how to deploy information assurance risk management strategies that align with the National Institute of Standards and Technology's recommendations. This book will show you how to implement information assurance risk management strategies within your organization. Aimed at system administrators and cybersecurity practitioners, author Bradley Fowler first walks you through how to assess known risks in your organization, understand why using a risk mitigation security strategy control profile is essential, and how to create one for your organization. You will then learn how to develop a risk factor table, outlining descriptions for each risk factor within your organization and which software applications you'll need to rely on for daily business communication and operations. You will also see how to assess and categorize the level of risk within each technology tool, as well as the impact of an information security breach on the organization. As you progress through the book, you'll review privacy issues relating to your organization, develop and manage a privacy compliance risk profile, and develop and manage a privacy compliance control profile. Additionally, you will gain insight into creating a privacy compliance risk mitigation strategy that helps protect your organization even as security threats evolve. Take the first step to safeguarding your company's highly valuable information assets today! What You'll LearnUnderstand what information assurance is and how it relates to risk management strategiesAssess, develop, implement, and manage risk management strategies for corporate information systems, technology, and cloud environmentsDevelop and utilize information usage profiles and risk factor tablesUnderstand the value of data encryption and usage of private and public key exchange for information assurance and security Who This Book Is ForInformation system and cloud architects responsible for developing, implementing, and managing corporate information systems and cloud environments.

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This open access book on infodemic management reviews the current discussions about this evolving area of public health from a variety of perspectives. Infodemic management is an evidence-based practice underpinned by the science of infodemiology that offers guidance to better manage pandemic and epidemic risks and more quickly tackle new and resurgent health threats. Infodemic management has added much visibility and recognition for the importance of social-behavioural sciences, health communication, participatory and human-centered approaches, and digital health as complementary scientific and practical approaches that also must be strengthened in public health practice through a whole-of-society and whole information ecosystem approach. This volume makes a case that health of the information ecosystem in the digital age has emerged as the fourth ecosystem that public health is challenged by, along with the triad of environment-human-animal health. The bookbrings together scientists and practitioners across disciplines to offer insights on infodemic management. The tools, methods, analytics, and interventions that they discuss in the context of acute health events also can be applied to other public health areas. Topics covered include:People's Experience of Information Overload and Its Impact on Infodemic HarmsSmart Health! Expanding the Need for New LiteraciesTo Debunk or Not to Debunk? Correcting (Mis)informationPartnering with Communities for Effective Management of Health EmergenciesManaging Infodemics in the 21st Century is required reading for public health practitioners in need of an overview of this evolving field of practice that has made major scientific and practical leaps forward since early 2020. Global, regional, and local health authorities are increasingly recognizing the need to expand their capacities for infodemic management in their efforts to better prepare for future health emergencies. This book is the resource they need to build toward a mature infodemic management process. The text also can be used as supplemental reading for graduate programs and courses in public health.

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study.The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice.The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.