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Gesamtkatalog

Catalogue complet

Nabil Nakbi

Assessing Credit Default Risk Using Logistic Regression. A Transparent Approach to Scoring with the UCI Dataset and SPSS

Miguel López

Impacto de la crisis demográfica en los países desarrollados y Costa Rica

A comprehensive and practical collection of tools and frameworks for risk governance at banks, insurance firms, asset managers, and other financial organizations In Risk Framework Design in Practice: Getting Risk Governance and Limits Right for Financial Institutions, veteran portfolio and risk manager, Michelle Beck, delivers a robust and functional approach to risk governance that's perfect for financial institution managers and executives. Beck skips the high-level bromides, &nbsp;avoids narrowly considering only one type of asset class or financial institution, and instead offers practical guidance for leaders across the full scope of the industry seeking to answer critical risk management questions: What types of risk limits are necessary? How many of them does my organization need? How should they be set? Are minimum regulatory standards sufficient to safeguard my company's interests? Risk Framework Design in Practice provides an effective structure for enterprise risk limits in different types of firms, including banks, asset managers, insurers, and corporate pensions. It explains how these types of firms should establish risk appetites, the essential pieces of their governance structures, and how to ensure the right information is in the right hands at the right times. It also includes: <ul> <li>Deep dives into the relevant limits for market, credit, and operational risks, including the implications of using alternative methods</li> <li>Detailed discussions of contemporary approaches to limiting economic capital, value at risk, stress tests, exposures, liquidity, concentrations, stop-losses, and drawdown limits</li> <li>Approaches to operational risk that avoid the expensive trap of attempting to police business efficiency, and instead focus on control strength for truly dangerous risks</li> </ul> Risk Framework Design in Practice is an effective resource for chief risk officers and professionals working in enterprise risk departments at banks, broker dealers, insurance companies, asset managers, and hedge funds.&nbsp; Also perfect for board members at banks and insurance companies, in-house counsel at financial firms, and bank and securities regulators.

Getting Risk Governance and Limits Right for Financial Institutions

Risk Framework Design in Practice

Integrating Artificial Intelligence for Next-Generation Financial Services

Deep Learning in Banking

 Anonymous

Central Bank Digital Currency. Eine kritische Analyse der ökonomischen und gesellschaftlichen Folgen

Business and Management (R0)

Fausto Pedro García Márquez

Benjamin Lev

Huchang Liao

From Theory to Practice

Outsourcing Using Operations Research and Management Science Methods

Decui Liang

Mingwei Wang

Zeshui Xu

Collective Wisdom-Driven Three-Way Decision in Risk Management

Contributions to Finance and Accounting

Banks play a crucial role in the global economy, yet they are vulnerable to failures that can have catastrophic effects. Key questions arise: What causes bank failures? What drives these failures? Can we avoid a banking crisis? What happens when a bank fails?This book explores the causes, consequences, and potential prevention of banking crises. It begins by examining the fundamental roles of banks in the economic system, focusing on their intermediary functions like liquidity provision, payment management, asset transformation, and borrower oversight. The book then delves into the challenges facing the banking sector, including cyber threats, climate change, and geopolitical instabilities.The second chapter addresses the primary risks banks face, such as liquidity, credit, market, interest rate, IT, and environmental risks, and how these contribute to banking failures. Chapter three shifts focus to financial statements, contrasting those of commercial and investment banks with non-financial companies, and discusses the impact of creative accounting in recent banking collapses.Governance issues and their role in banking failures are the focus of chapter four, highlighting the crucial need for effective risk monitoring by bank directors. The final chapter illustrates the process of bank resolution and the evolving strategies of resolution authorities in ensuring bank stability.Targeted at researchers, regulators, and practitioners, this book comprehensively covers the drivers of banking failures, regulatory improvement suggestions, and real-world case studies. It emphasizes the importance of banks in today’s economy, their unique risks, and the aftermath of their failure, aiming to provide a threefold contribution to understanding and managing banking crises.

The Role of Risk Management, Governance, Accounting, and More

Why Do Banks Fail and What to Do About It

Melanie Tippel

Finanzpolitik in der Bundesrepublik Deutschland. Theorie und Praxis am Beispiel der Schuldenbremse und des "Sondervermögens Bundeswehr"

Master Financial Risk Management and Protect Your Future

Financial risk is unavoidable, but understanding and managing it effectively can mean the difference between financial stability and crisis. From market fluctuations and credit defaults to liquidity shortages and operational failures, individuals and businesses face a range of challenges that can impact financial health and long-term success.
This book breaks down key financial risks, including market, credit, liquidity, operational, and systemic risks, while offering practical strategies to assess, mitigate, and manage them effectively. Learn how to navigate interest rate volatility, foreign exchange fluctuations, regulatory changes, and unforeseen global events with proven risk management techniques like hedging, diversification, credit analysis, and crisis planning.

With real-world examples, expert insights, and actionable strategies, this guide is an essential resource for investors, business leaders, and financial professionals looking to minimize losses and maximize financial security.

Prepare for the unexpected, mitigate risk, and make smarter financial decisions-because a strong risk management strategy is the key to financial success.

Identifying, Assessing, and Mitigating Uncertainty for Stability and Success

Financial Risk Management Modeling [AI]

Studienarbeit aus dem Jahr 2022 im Fachbereich VWL - Finanzwissenschaft, Note: 1,0, IU Internationale Hochschule, Veranstaltung: Finanzierung, Sprache: Deutsch, Abstract: Ziel dieser Literaturübersichtsarbeit ist es, die Vorteile einer aktiven Steuerung der Kapitalstruktur für Unternehmen aufzuzeigen. Verschiedene Faktoren beeinflussen Kapitalstrukturentscheidungen. Zu diesen Faktoren zählen beispielsweise Branche, Größe, Zugangsmöglichkeiten zum Kapitalmarkt, Kapitalintensität, regulatorische Aspekte, Ertragspotential oder Geschäftsstrategie eines Unternehmens. Mit dieser Arbeit soll ein Einstieg und erster Überblick zum breiten Themengebiet der Kapitalstruktur und dessen Bedeutung gegeben werden.Die Arbeit ist hierzu wie folgt gegliedert: Im zweiten Kapitel werden finanztheoretische Grundlagen vorgestellt. Dabei wird der Begriff der Kapitalstruktur definiert und auf den Aufbau der Bilanz, unterschiedliche Finanzierungsarten sowie den Leverage-Effekt eingegangen. Anschließend werden verschiedene Theorien vorgestellt, die sich mit der Kapitalstruktur von Unternehmen beschäftigen. Die Theorien beleuchten die Bedeutung beziehungsweise Auswirkungen verschiedener Kapitalstrukturen. Auf Grundlage der Kapitalstrukturtheorien sowie Studien zum Vorgehen in der Unternehmenspraxis werden im dritten Kapitel Vorteile aufgezeigt, die sich für Unternehmen durch eine aktive Steuerung der Kapitalstruktur ergeben. Das letzte Kapitel fasst die Ergebnisse der Arbeit zusammen und gibt einen Ausblick auf weiterführende Fragestellungen.

Maurice Reinartz

Die Vorteile einer aktiven Kapitalstruktursteuerung für Unternehmen. Eine umfassende Literaturübersicht und theoretische Analyse

Tom Stephan

Wie wirkt sich Extraversion auf Organizational Citizenship Behavior aus unter der Berücksichtigung von Selbstwertgefühl und Selbstkontrollanstrengungen im Arbeitskontext?

This book discusses the evolution of technical features in decentralized finance and focuses on machine-learning finance in emerging economies. As technological advancement evolves at an unpredictable pace, the financial industry, like every other sector, must adapt accordingly. Furthermore, the rapid expansion of diverse financial products and services is creating new applications and markets. Alongside technological progress, the exploration of complex patterns in vast amounts of data, known as big data, is facilitated by its commonly acknowledged characteristics: volume, variety, veracity, value, and velocity.

Overall, machine learning has become crucial in the financial industry, allowing businesses to automate operations, gain insights from data, and make more informed decisions in real time. This edited book covers algorithmic trading, risk management, fraud detection, customer service and personalization, portfolio management, credit scoring, sentiment analysis, and algorithmic pricing. The book connects theoretical concepts with practical real-world applications, benefiting professionals looking to enhance their proficiency in using these methods efficiently. It offers insightful guidance for theorists, market participants, and policymakers by exploring financial theories and practices in light of contemporary machine-learning approaches, with a special emphasis on emerging economies.

This book discusses the evolution of technical features in decentralized finance and focuses on machine-learning finance in emerging economies. As technological advancement evolves at an unpredictable pace, the financial industry, like every other sector, must adapt accordingly. Furthermore, the rapid expansion of diverse financial products and services is creating new applications and markets. Alongside technological progress, the exploration of complex patterns in vast amounts of data, known as big data, is facilitated by its commonly acknowledged characteristics: volume, variety, veracity, value, and velocity.Overall, machine learning has become crucial in the financial industry, allowing businesses to automate operations, gain insights from data, and make more informed decisions in real time. This edited book&nbsp;covers algorithmic trading, risk management, fraud detection, customer service and personalization, portfolio management, credit scoring, sentiment analysis, and algorithmic pricing. The book connects theoretical concepts with practical real-world applications, benefiting professionals looking to enhance their proficiency in using these methods efficiently. It offers insightful guidance for theorists, market participants, and policymakers by exploring financial theories and practices in light of contemporary machine-learning approaches, with a special emphasis on emerging economies.

Trends, Developments and Business Practices in the Financial Sector

Machine Learning in Finance

Assessing Credit Default Risk Using Logistic Regression. A Transparent Approach to Scoring with the UCI Dataset and SPSS

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