Water quantity—too much in the case of floods, or too little in the case of droughts—grabs public attention and the media spotlight. Water quality—being predominantly invisible and hard to detect—goes largely unnoticed. Quality Unknown: The Invisible Water Crisis presents new evidence and new data that call urgent attention to the hidden dangers lying beneath water’s surface. It shows how poor water quality stalls economic progress, stymies human potential, and reduces food production. Quality Unknown examines the effects of water quality on economic growth and finds upstream pollution lowers growth in downstream regions. It reveals that some of the most ubiquitous contaminants in water, such as nitrates and salt, have impacts that are larger, deeper, and wider than has been acknowledged. And it traces the damage to crop yields and the stark implications for food security in affected regions. An important step toward tackling the world’s water quality challenge is recognizing its scale. The world needs reliable, accurate, and comprehensive information so that policy makers can have new insights, decision making can be evidence based, and citizens can call for action. The report calls for a paradigm shift that emphasizes safer, and often more cost-effective remedies that prevent pollution by combining smarter policies with newer technologies. A key message of Quality Unknown is that such solutions exist and change is possible.

Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.

This book highlights mathematical research interests that appear in real life, such as the study and modeling of random and deterministic phenomena. As such, it provides current research in mathematics, with applications in biological and environmental sciences, ecology, epidemiology and social perspectives. The chapters can be read independently of each other, with dedicated references specific to each chapter. The book is organized in two main parts. The first is devoted to some advanced mathematical problems regarding epidemic models; predictions of biomass; space-time modeling of extreme rainfall; modeling with the piecewise deterministic Markov process; optimal control problems; evolution equations in a periodic environment; and the analysis of the heat equation. The second is devoted to a modelization with interdisciplinarity in ecological, socio-economic, epistemological, demographic and social problems. Mathematical Modeling of Random and Deterministic Phenomena is aimed at expert readers, young researchers, plus graduate and advanced undergraduate students who are interested in probability, statistics, modeling and mathematical analysis.

This book identifies the central problems of crisis research, assesses the progress of work in the area, and discusses prospects for the future. It addresses Soviet, Chinese, and U.S. crisis management patterns, computer-based early warning systems, terrorism, and the Rapid Deployment Force.

Chapter 7: Air transport scenarios for the Paris region up to 1990.

The first twenty years of the European Central Bank offer a unique insight into how a central bank can navigate macroeconomic insecurity and crisis. This volume examines the structures and decision-making processes behind the complex measures taken by the ECB to tackle some of the toughest economic challenges in the history of modern Europe.

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.