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Risk Assessment
New developments in assessing and managing risk are discussed in this volume. Addressing both practitioners in the banking sector and research institutions, the book provides a manifold view on the most-discussed topics in finance. Among the subjects treated are important issues such as: risk measures and allocation of risks, factor modeling, risk premia in the hedge funds industry and credit risk management. The volume provides an overview of recent developments as well as future trends in the area of risk assessment.
Handbook of Computational and Numerical Methods in Finance
The subject of numerical methods in finance has recently emerged as a new discipline at the intersection of probability theory, finance, and numerical analysis. The methods employed bridge the gap between financial theory and computational practice, and provide solutions for complex problems that are difficult to solve by traditional analytical methods. Although numerical methods in finance have been studied intensively in recent years, many theoretical and practical financial aspects have yet to be explored. This volume presents current research and survey articles focusing on various numerical methods in finance. The book is designed for the academic community and will also serve professional investors.
Mathematical and Statistical Methods for Actuarial Sciences and Finance
The cooperation and contamination between mathematicians, statisticians and econometricians working in actuarial sciences and finance is improving the research on these topics and producing numerous meaningful scientific results. This volume presents new ideas, in the form of four- to six-page papers, presented at the International Conference eMAF2020 – Mathematical and Statistical Methods for Actuarial Sciences and Finance. Due to the now sadly famous COVID-19 pandemic, the conference was held remotely through the Zoom platform offered by the Department of Economics of the Ca’ Foscari University of Venice on September 18, 22 and 25, 2020. eMAF2020 is the ninth edition of an internationa...
Applied Quantitative Finance
Recent years have witnessed a growing importance of quantitative methods in both financial research and industry. This development requires the use of advanced techniques on a theoretical and applied level, especially when it comes to the quantification of risk and the valuation of modern financial products. Applied Quantitative Finance (2nd edition) provides a comprehensive and state-of-the-art treatment of cutting-edge topics and methods. It provides solutions to and presents theoretical developments in many practical problems such as risk management, pricing of credit derivatives, quantification of volatility and copula modelling. The synthesis of theory and practice supported by computat...
Statistical Tools for Finance and Insurance
Statistical Tools in Finance and Insurance presents ready-to-use solutions, theoretical developments and method construction for many practical problems in quantitative finance and insurance. Written by practitioners and leading academics in the field, this book offers a unique combination of topics from which every market analyst and risk manager will benefit. Covering topics such as heavy tailed distributions, implied trinomial trees, support vector machines, valuation of mortgage-backed securities, pricing of CAT bonds, simulation of risk processes and ruin probability approximation, the book does not only offer practitioners insight into new methods for their applications, but it also gi...
Mortality and the Provision of Retirement Income
This report analyses the development of mortality assumptions to build mortality tables to better protect retirement income provision. Mortality assumptions are necessary to ensure the sustainability of lifetime incomes.
Greatness in Waiting
Before they acquired Babe Ruth or won a single championship, the New York Yankees (née Highlanders) were a team that inspired the strongest of feelings in baseball circles. Stars such as Jack Chesbro, Hal Chase, and Brooklyner Willie Keeler drew loud followings, and the team made loyal fans of those who disliked the cross-town Giants or Dodgers. Even Ban Johnson prized the franchise, which gave his upstart American League a foothold in the nation’s most populous city. Baltimoreans, on the other hand, nurtured an animus toward the team, which only a few years earlier had been called the Orioles. And former Orioles manager John McGraw hatched a plan, along with Giants owner Andrew Freedman, to sabotage the new club. This heavily illustrated volume combines a fully documented history of the deadball-era Yankees with 195 photos of the people, places, and events that figured prominently in the story.
Nonparametric Econometric Methods
Contains a selection of papers presented initially at the 7th Annual Advances in Econometrics Conference held on the LSU campus in Baton Rouge, Louisiana during November 14-16, 2008. This work is suitable for those who wish to familiarize themselves with nonparametric methodology.
Before They Were the Bombers
Many histories of the New York Yankees only skim the early years in their rush to pick up with the 1919 season when Babe Ruth joined the team and go on to celebrate the careers of Lou Gehrig, Joe DiMaggio, Mickey Mantle, and Whitey Ford, and the team's World Series titles. But what about the Yankees before these big names? The early Yankees, who spent their first 12 years known as the Highlanders and were occasionally known as the Americans and the Invaders, get the attention they deserve in this work. It tells the story up until the sale of the Yankees in December 1914, beginning with 1903 when the team was formed from the remnants of the Baltimore Orioles. Led by future Hall of Famers "Wee" Willie Keeler, Jack Chesbro, and Clark Griffith, they were the most expensive major league team ever assembled--but they are remembered primarily for their terrible failures, which included losing a club-low 103 games in 1908 and finishing 55 games out of first place in 1912. Yes, the Yankees.
AI-enabled Technologies for Autonomous and Connected Vehicles
This book reports on cutting-edge research and advances in the field of intelligent vehicle systems. It presents a broad range of AI-enabled technologies, with a focus on automated, autonomous and connected vehicle systems. It covers advanced machine learning technologies, including deep and reinforcement learning algorithms, transfer learning and learning from big data, as well as control theory applied to mobility and vehicle systems. Furthermore, it reports on cutting-edge technologies for environmental perception and vehicle-to-everything (V2X), discussing socioeconomic and environmental implications, and aspects related to human factors and energy-efficiency alike, of automated mobility. Gathering chapters written by renowned researchers and professionals, this book offers a good balance of theoretical and practical knowledge. It provides researchers, practitioners and policy makers with a comprehensive and timely guide on the field of autonomous driving technologies.
