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Future Perspectives in Risk Models and Finance

Future Perspectives in Risk Models and Finance PDF Author: Alain Bensoussan
Publisher:
ISBN: 9783319075259
Category :
Languages : en
Pages : 332

Book Description


Future Perspectives in Risk Models and Finance

Future Perspectives in Risk Models and Finance PDF Author: Alain Bensoussan
Publisher:
ISBN: 9783319075259
Category :
Languages : en
Pages : 332

Book Description


Risk Assessment and Financial Regulation in Emerging Markets' Banking

Risk Assessment and Financial Regulation in Emerging Markets' Banking PDF Author: Alexander M. Karminsky
Publisher: Springer Nature
ISBN: 3030697487
Category : Business & Economics
Languages : en
Pages : 395

Book Description
This book describes various approaches in modelling financial risks and compiling ratings. Focusing on emerging markets, it illustrates how risk assessment is performed and analyses the use of machine learning methods for financial risk assessment and measurement. It not only offers readers insights into the differences between emerging and developed markets, but also helps them understand the development of risk management approaches for banks. Highlighting current problems connected with the evaluation and modelling of financial risks in the banking sector of emerging markets, the book presents the methodologies applied to credit and market financial risks and integrated and payment risks, and discusses the outcomes. In addition it explores the systemic risks and innovations in banking and risk management by analyzing the features of risk measurement in emerging countries. Lastly, it demonstrates the aggregation of approaches to financial risk for emerging financial markets, comparing the experiences of various countries, including Russia, Belarus, China and Brazil.

Future Perspectives in Risk Models and Finance

Future Perspectives in Risk Models and Finance PDF Author: Alain Bensoussan
Publisher: Springer
ISBN: 3319075241
Category : Business & Economics
Languages : en
Pages : 315

Book Description
This book provides a perspective on a number of approaches to financial modelling and risk management. It examines both theoretical and practical issues. Theoretically, financial risks models are models of a real and a financial “uncertainty”, based on both common and private information and economic theories defining the rules that financial markets comply to. Financial models are thus challenged by their definitions and by a changing financial system fueled by globalization, technology growth, complexity, regulation and the many factors that contribute to rendering financial processes to be continuously questioned and re-assessed. The underlying mathematical foundations of financial risks models provide future guidelines for risk modeling. The book’s chapters provide selective insights and developments that can contribute to better understand the complexity of financial modelling and its ability to bridge financial theories and their practice. Future Perspectives in Risk Models and Finance begins with an extensive outline by Alain Bensoussan et al. of GLM estimation techniques combined with proofs of fundamental results. Applications to static and dynamic models provide a unified approach to the estimation of nonlinear risk models. A second section is concerned with the definition of risks and their management. In particular, Guegan and Hassani review a number of risk models definition emphasizing the importance of bi-modal distributions for financial regulation. An additional chapter provides a review of stress testing and their implications. Nassim Taleb and Sandis provide an anti-fragility approach based on “skin in the game”. To conclude, Raphael Douady discusses the noncyclical CAR (Capital Adequacy Rule) and their effects of aversion of systemic risks. A third section emphasizes analytic financial modelling approaches and techniques. Tapiero and Vallois provide an overview of mathematical systems and their use in financial modeling. These systems span the fundamental Arrow-Debreu framework underlying financial models of complete markets and subsequently, mathematical systems departing from this framework but yet generalizing their approach to dynamic financial models. Explicitly, models based on fractional calculus, on persistence (short memory) and on entropy-based non-extensiveness. Applications of these models are used to define a modeling approach to incomplete financial models and their potential use as a “measure of incompleteness”. Subsequently Bianchi and Pianese provide an extensive overview of multi-fractional models and their important applications to Asset price modeling. Finally, Tapiero and Jinquyi consider the binomial pricing model by discussing the effects of memory on the pricing of asset prices.

Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance

Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance PDF Author: El Bachir Boukherouaa
Publisher: International Monetary Fund
ISBN: 1589063953
Category : Business & Economics
Languages : en
Pages : 35

Book Description
This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.

The Future of Risk Management, Volume II

The Future of Risk Management, Volume II PDF Author: Paola De Vincentiis
Publisher: Palgrave Macmillan
ISBN: 9783030165253
Category : Business & Economics
Languages : en
Pages : 0

Book Description
With contributions presented during the Second International Risk Management Conference, this second volume addresses important areas of risk management from a variety of angles and perspectives. The book will cover two separate tracks—financial risk management and risk management and corporate strategies—and will be of interest to academic researchers and students in risk management, banking, and finance.

Handbook of Recent Advances in Commodity and Financial Modeling

Handbook of Recent Advances in Commodity and Financial Modeling PDF Author: Giorgio Consigli
Publisher: Springer
ISBN: 3319613200
Category : Business & Economics
Languages : en
Pages : 320

Book Description
This handbook includes contributions related to optimization, pricing and valuation problems, risk modeling and decision making problems arising in global financial and commodity markets from the perspective of Operations Research and Management Science. The book is structured in three parts, emphasizing common methodological approaches arising in the areas of interest: - Part I: Optimization techniques - Part II: Pricing and Valuation - Part III: Risk Modeling The book presents to a wide community of Academics and Practitioners a selection of theoretical and applied contributions on topics that have recently attracted increasing interest in commodity and financial markets. Within a structure based on the three parts, it presents recent state-of-the-art and original works related to: - The adoption of multi-criteria and dynamic optimization approaches in financial and insurance markets in presence of market stress and growing systemic risk; - Decision paradigms, based on behavioral finance or factor-based, or more classical stochastic optimization techniques, applied to portfolio selection problems including new asset classes such as alternative investments; - Risk measurement methodologies, including model risk assessment, recently applied to energy spot and future markets and new risk measures recently proposed to evaluate risk-reward trade-offs in global financial and commodity markets; and derivatives portfolio hedging and pricing methods recently put forward in the financial community in the aftermath of the global financial crisis.

The Future of Finance

The Future of Finance PDF Author: Moorad Choudhry
Publisher: John Wiley & Sons
ISBN: 0470906464
Category : Business & Economics
Languages : en
Pages : 53

Book Description
New banking and investment business models to navigate the post-financial crisis environment The financial crisis of 2007-2008 has discredited business models in the banking and fund management industries. In The Future of Finance, Moorad Choudhry and Gino Landuyt argue that banks must realign their business models, implying a lower return-on-equity; diversifying their funding sources; and increasing liquidity reserves. On the investment side, the authors discuss how diversification did not reduce risk, but rather amplified it, and failed to stabilize returns. The authors conclude that the clear lesson from the crisis is to know one's risk. A lesson that is best served by concentrating on assets and sectors that you understand. Examines the weaknesses in the business models of many institutions, as well as the theoretical foundation for professionals in the field of finance Identifies the shortcomings of Modern Portfolio Theory Addresses how investment managers can find new strategies for creating "alpha" and why they need to re-vamp their fee structures Filled with in-depth insights and practical advice, The Future of Finance will provide bankers and investment managers with a guide to realigning their businesses in order to prosper in the post-crisis financial markets.

Operational Risk Modeling in Financial Services

Operational Risk Modeling in Financial Services PDF Author: Patrick Naim
Publisher: John Wiley & Sons
ISBN: 1119508436
Category : Business & Economics
Languages : en
Pages : 390

Book Description
Transform your approach to oprisk modelling with a proven, non-statistical methodology Operational Risk Modeling in Financial Services provides risk professionals with a forward-looking approach to risk modelling, based on structured management judgement over obsolete statistical methods. Proven over a decade’s use in significant banks and financial services firms in Europe and the US, the Exposure, Occurrence, Impact (XOI) method of operational risk modelling played an instrumental role in reshaping their oprisk modelling approaches; in this book, the expert team that developed this methodology offers practical, in-depth guidance on XOI use and applications for a variety of major risks. The Basel Committee has dismissed statistical approaches to risk modelling, leaving regulators and practitioners searching for the next generation of oprisk quantification. The XOI method is ideally suited to fulfil this need, as a calculated, coordinated, consistent approach designed to bridge the gap between risk quantification and risk management. This book details the XOI framework and provides essential guidance for practitioners looking to change the oprisk modelling paradigm. Survey the range of current practices in operational risk analysis and modelling Track recent regulatory trends including capital modelling, stress testing and more Understand the XOI oprisk modelling method, and transition away from statistical approaches Apply XOI to major operational risks, such as disasters, fraud, conduct, legal and cyber risk The financial services industry is in dire need of a new standard — a proven, transformational approach to operational risk that eliminates or mitigates the common issues with traditional approaches. Operational Risk Modeling in Financial Services provides practical, real-world guidance toward a more reliable methodology, shifting the conversation toward the future with a new kind of oprisk modelling.

Recent Applications of Financial Risk Modelling and Portfolio Management

Recent Applications of Financial Risk Modelling and Portfolio Management PDF Author: Škrinjari?, Tihana
Publisher: IGI Global
ISBN: 1799850846
Category : Business & Economics
Languages : en
Pages : 432

Book Description
In today’s financial market, portfolio and risk management are facing an array of challenges. This is due to increasing levels of knowledge and data that are being made available that have caused a multitude of different investment models to be explored and implemented. Professionals and researchers in this field are in need of up-to-date research that analyzes these contemporary models of practice and keeps pace with the advancements being made within financial risk modelling and portfolio control. Recent Applications of Financial Risk Modelling and Portfolio Management is a pivotal reference source that provides vital research on the use of modern data analysis as well as quantitative methods for developing successful portfolio and risk management techniques. While highlighting topics such as credit scoring, investment strategies, and budgeting, this publication explores diverse models for achieving investment goals as well as improving upon traditional financial modelling methods. This book is ideally designed for researchers, financial analysts, executives, practitioners, policymakers, academicians, and students seeking current research on contemporary risk management strategies in the financial sector.

Bayesian Risk Management

Bayesian Risk Management PDF Author: Matt Sekerke
Publisher: John Wiley & Sons
ISBN: 1118708601
Category : Business & Economics
Languages : en
Pages : 228

Book Description
A risk measurement and management framework that takes model risk seriously Most financial risk models assume the future will look like the past, but effective risk management depends on identifying fundamental changes in the marketplace as they occur. Bayesian Risk Management details a more flexible approach to risk management, and provides tools to measure financial risk in a dynamic market environment. This book opens discussion about uncertainty in model parameters, model specifications, and model-driven forecasts in a way that standard statistical risk measurement does not. And unlike current machine learning-based methods, the framework presented here allows you to measure risk in a fully-Bayesian setting without losing the structure afforded by parametric risk and asset-pricing models. Recognize the assumptions embodied in classical statistics Quantify model risk along multiple dimensions without backtesting Model time series without assuming stationarity Estimate state-space time series models online with simulation methods Uncover uncertainty in workhorse risk and asset-pricing models Embed Bayesian thinking about risk within a complex organization Ignoring uncertainty in risk modeling creates an illusion of mastery and fosters erroneous decision-making. Firms who ignore the many dimensions of model risk measure too little risk, and end up taking on too much. Bayesian Risk Management provides a roadmap to better risk management through more circumspect measurement, with comprehensive treatment of model uncertainty.