Risk Measurement, Econometrics and Neural Networks
Risk Measurement, Econometrics and Neural Networks

Author: Georg Bol

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 316

ISBN-13: 3642582729

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This book comprises the articles of the 6th Econometric Workshop in Karlsruhe, Germany. In the first part approaches from traditional econometrics and innovative methods from machine learning such as neural nets are applied to financial issues. Neural Networks are successfully applied to different areas such as debtor analysis, forecasting and corporate finance. In the second part various aspects from Value-at-Risk are discussed. The proceedings describe the legal framework, review the basics and discuss new approaches such as shortfall measures and credit risk.

PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS. REGRESSION AND DECISION TREES
PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS. REGRESSION AND DECISION TREES

Author:

Publisher: CESAR PEREZ

Published:

Total Pages: 222

ISBN-13: 100897952X

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The essential aim of this book is to use predictive models to analyze risk. Models of decision trees, regression and neural networks are used to predict various risk categories. This book shows you how to build decision tree models to predict a categorical target and how to build regression tree models and neural network models to predict a continuous target. Successive chapters present examples that clarify the application of the models in the field of risk. The examples are solved step by step with SAS Enterprise Miner in order to make easier the understanding of the methodologies used. The book begins by introducing the basics of creating a project, manipulating data sources, and navigating through different results windows. Data Mining tools are used to build the main risk models: Decision Tree, Neural Network, and Regression.

Risk Management
Risk Management

Author: Michael Frenkel

Publisher: Springer Science & Business Media

Published: 2005-12-06

Total Pages: 842

ISBN-13: 3540269932

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Dealing with all aspects of risk management that have undergone significant innovation in recent years, this book aims at being a reference work in its field. Different to other books on the topic, it addresses the challenges and opportunities facing the different risk management types in banks, insurance companies, and the corporate sector. Due to the rising volatility in the financial markets as well as political and operational risks affecting the business sector in general, capital adequacy rules are equally important for non-financial companies. For the banking sector, the book emphasizes the modifications implied by the Basel II proposal. The volume has been written for academics as well as practitioners, in particular finance specialists. It is unique in bringing together such a wide array of experts and correspondingly offers a complete coverage of recent developments in risk management.

Scenario Analysis in Risk Management
Scenario Analysis in Risk Management

Author: Bertrand K. Hassani

Publisher: Springer

Published: 2016-10-26

Total Pages: 171

ISBN-13: 3319250566

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This book focuses on identifying and explaining the key determinants of scenario analysis in the context of operational risk, stress testing and systemic risk, as well as management and planning. Each chapter presents alternative solutions to perform reliable scenario analysis. The author also provides technical notes and describes applications and key characteristics for each of the solutions. In addition, the book includes a section to help practitioners interpret the results and adjust them to real-life management activities. Methodologies, including those derived from consensus strategies, extreme value theory, Bayesian networks, Neural networks, Fault Trees, frequentist statistics and data mining are introduced in such a way as to make them understandable to readers without a quantitative background. Particular emphasis is given to the added value of the implementation of these methodologies.

Operations Research Proceedings 2002
Operations Research Proceedings 2002

Author: Ulrike Leopold-Wildburger

Publisher: Springer Science & Business Media

Published: 2003-02-24

Total Pages: 572

ISBN-13: 9783540003878

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This proceedings volume contains a selection of papers presented at the International Conference on Operations Research (SOR 2002).The contributions cover the broad interdisciplinary spectrum of Operations Research and present recent advances in theory, development of methods, and applications in practice. Subjects covered are Production, Logistics and Supply Chain Production, Marketing and Data Analysis, Transportation and Traffic, Scheduling and Project Management, Telecommunication and Information Technology, Energy and Environment, Public Economy, Health, Agriculture, Education, Banking, Finance, Insurance, Risk Management, Continuous Optimization, Discrete and Combinatorial Optimization, Stochastic and Dynamic Programming, Simulation, Control Theory, Systems Dynamics, Dynamic Games, Game Theory, Auctioning and Bidding, Experimental Economics, Econometrics, Statistics and Mathematical Economics, Fuzzy Logic, Multicriteria Decision Making, Decision Theory.

Empirical Asset Pricing
Empirical Asset Pricing

Author: Wayne Ferson

Publisher: MIT Press

Published: 2019-03-12

Total Pages: 497

ISBN-13: 0262039370

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An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.

Advances in Pacific Basin Business, Economics and Finance
Advances in Pacific Basin Business, Economics and Finance

Author: Cheng-Few Lee

Publisher: Emerald Group Publishing

Published: 2020-09-09

Total Pages: 256

ISBN-13: 1838673636

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Advances in Pacific Basin Business, Economics, and Finance is an annual publication designed to focus on interdisciplinary research in finance, economics, accounting and management among Pacific Rim countries.

Floods in the Ganga–Brahmaputra–Meghna Delta
Floods in the Ganga–Brahmaputra–Meghna Delta

Author: Aznarul Islam

Publisher: Springer Nature

Published: 2023-02-14

Total Pages: 570

ISBN-13: 3031210867

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This volume covers the floods of the major rivers of the Ganga-Brahmaputra-Meghna (GBM) Delta, and storm surge related coastal floods in these regions. The book is dedicated to addressing floods from an integrated physical-social perspective to provide students and researchers with a holistic understanding of floods in terms of both human and geomorphological aspects. The systematic coverage of all the major rivers and coastal areas in the GBM delta and surrounding regions will foster a clear comprehension of this dense reservoir of population, where thousands of people are impacted every year due to flood hazards and agricultural destabilization. This comprehensive treatment of flood issues in the region covers flash floods, fluvial floods, fluvio-tidal floods, and coastal floods, and outlines flood management strategies to maintain ecological integrity and environmental stability, and prevent harmful impacts of future floods. The book is intended for students and researchers in earth and environmental sciences, especially geomorphology, hydrology, geography, geology, natural resources management, and regional planning.

Machine Learning for Financial Risk Management with Python
Machine Learning for Financial Risk Management with Python

Author: Abdullah Karasan

Publisher:

Published: 2021

Total Pages: 350

ISBN-13: 9781492085249

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Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how to compare results from ML models with results obtained by traditional financial risk models. Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models. Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learning Revisit and improve market risk models (VaR and expected shortfall) using machine learning techniques Develop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML models Capture different aspects of liquidity with a Gaussian mixture model Use machine learning models for fraud detection Identify corporate risk using the stock price crash metric Explore a synthetic data generation process to employ in financial risk.