This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and n
The recent turmoil on financial markets has made evident the importance of efficient liquidity risk management for the stability of banks. The measurement and management of liquidity risk must take in
Risk management for financial institutions is one of the key topics the financial industry has to deal with. The present volume is a mathematically rigorous text on solvency modeling. Currently, there
The bulk of this volume deals with the four main aspects of risk management: market risk, credit risk, risk management - in macro-economy as well as within companies. It presents a number of approache
?Weather derivatives are financial instruments that can be used by organizations or individuals as part of a risk management strategy to minimize risk associated with adverse or unexpected weather con
?Weather derivatives are financial instruments that can be used by organizations or individuals as part of a risk management strategy to minimize risk associated with adverse or unexpected weather con
Investment and risk management problems are fundamental problems for financial institutions and involve both speculative and hedging decisions. A structured approach to these problems naturally leads
This book analyzes the impacts that family control of firms has on capital structure choices, leverage and the risk of financial distress, earnings management practices, and the relation between accou
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 mode
Investment and risk management problems are fundamental problems for financial institutions and involve both speculative and hedging decisions. A structured approach to these problems naturally leads
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the
This publication is a practical guidebook on environmental risk assessment, especially for watershed-scale management. It highlights case studies of watershed environmental risk in Malaysia, including
This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer
This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random for
With reliable guidance on corporate risk and safety management for aviation businesses at all levels, this volume explains how to implement the latest international regulations—a vital aid to smaller
Decision Support Systems for Risk-Based Management of Contaminated Sites addresses decision making in environmental risk management for contaminated sites, focusing on the potential role of decision s
Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and disc
Management of the Patient at High Risk for Breast Cancer provides a state-of-the art review of patients who are at high risk for breast cancer, how to identify them, the tools available for risk asses
The aim of the book is to provide an overview of risk management in life insurance companies. The focus is twofold: (1) to provide a broad view of the different topics needed for risk management and (
Decision Support Systems for Risk-Based Management of Contaminated Sites addresses decision making in environmental risk management for contaminated sites, focusing on the potential role of decision s
This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior.
This book points out why organisational or governance aspects are essential for implementing a broad and integrated flood risk management approach. It provides key conclusions on resilient, efficient
This book presents a broad overview of risk management in the banking industry, with a special focus on strategic thinking and decision-making. It reveals the broader context behind decision models a
This informative volume synthesizes the literatures on health economics, risk management, and health services into a concise guide to the financial and social basics of health insurance with an eye to
The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papersfrom the international Conference ML4CPS – Machine Learn
This second edition expands the first chapters, which focus on the approach to risk management issues discussed in the first edition, to offer readers a better understanding of the risk management pro
This textbook provides a thorough introduction to natural disaster risk management. Many aspects of disaster risk management, such as those involved in earthquakes, volcanic eruptions, floods, avalanc
This book presents basic ideas of machine learning in a way that is easy to understand, by providing hands-on practical advice, using simple examples, and motivating students with discussions of inter
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-
This book provides readers an understanding of the implementation of Enterprise Risk Management (ERM) for international construction operations. In an extended case study, it primarily focuses on Chin
The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector. It was written as a training companion and as a must-read, not onl
This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series co
This book is about the formulations, theoretical investigations, and practical applications of new stochastic models for fundamental concepts and operations of the discipline of risk management. It al
Covers the entire process of risk management by providing methodologies for determining the sources of engineering project risk, and once threats have been identified, managing them through: identific
In this age of climatic and financial uncertainty, it becomes increasingly important to balance the cost, benefits and risk of wildfire management. In the United States, increased wildland fire activi
Offering sequenced guidance for non-specialists on how to reap the benefits of machine learning in medicine and healthcare, this text harnesses the power of cutting-edge computing to maximize the acce
Machine learning is concerned with the analysis of large data and multiple variables. However, it is also often more sensitive than traditional statistical methods to analyze small data. The first vol
The media now regularly feature breakthroughs on the influence of prenatal hormones on the brain and behavior, for instance the link to financial performance or risk management. Based on these finding
A challenge facing society today is how to develop a meaningful strategy for integrated hazardous waste management. Meeting this challenge was the principal motivation for the conference on "Risk Asse
This book considers the one-factor copula model for credit portfolios that are used for pricing synthetic CDO structures as well as for risk management and measurement applications involving the gener
