This book describes a laboratory experiment designed to test the causes and properties of bubbles in financial markets and explores the question whether it is possible to design markets which avoid such bubbles and crashes. In the experiment, subjects were given the opportunity to trade in a stock market modeled after the seminal work of Smith et al. (1988). To account for the increasing importance of online betting sites, subjects were also allowed to trade in a digital option market. The outcomes shed new light on how subjects form and update their expectations, placing special emphasis on the bounded rationality of investors. Various analytical bubble measures found in the literature are collected, calculated, classified and presented for the first time. The very interesting new bubble measures "Dispersion Ratio", "Overpriced Transactions" and "Underpriced Transactions" are developed, making the book an important step towards the research goal of preventing bubbles and crashes in financial markets.

This book describes a laboratory experiment designed to test the causes and properties of bubbles in financial markets and explores the question whether it is possible to design markets which avoid such bubbles and crashes. In the experiment, subjects were given the opportunity to trade in a stock market modeled after the seminal work of Smith et al. (1988). To account for the increasing importance of online betting sites, subjects were also allowed to trade in a digital option market. The outcomes shed new light on how subjects form and update their expectations, placing special emphasis on the bounded rationality of investors. Various analytical bubble measures found in the literature are collected, calculated, classified and presented for the first time. The very interesting new bubble measures "Dispersion Ratio", "Overpriced Transactions" and "Underpriced Transactions" are developed, making the book an important step towards the research goal of preventing bubbles and crashes in financial markets.

Advances in physics, computers, and mathematics have made it possible to illustrate an astonishing array of potential behavior that can occur when nonlinear interactions are present. As Prigogine explains from a physicist's perspective, the fundamental role of instability and bounded rationality provide more precise understanding for evolution and changes. This volume considers these developments from various fields in the context of economic science. The work starts with a general non-mathematical discussion, introducing the major themes--nonlinearity, dynamical systems, and evolution in economic processes. The work continues with nonlinear analysis of macroeconomic growth and fluctuations. It describes analyses of economic adaptation, learning, and self-organization. The volume also scrutinizes a specific market--equities using nonlinear analysis, controlled experiments, and statistical inference when nonlinearity plays an essential role in data generation. The volume closes with an historical reflection by Richard Goodwin and a roundtable discussion on basic issues and new challenges in nonlinear economic dynamics.

This book reviews the latest research from psychology, neuroscience, and behavioral economics evaluating how people make financial choices in real-life circumstances. The volume is divided into three sections investigating financial decision making at the level of the brain, the level of an individual decision maker, and the level of the society, concluding with a discussion of the implications for further research. Among the topics discussed: Neural and hormonal bases of financial decision making Personality, cognitive abilities, emotions, and financial decisions Aging and financial decision making Coping methods for making financial choices under uncertainty Stock market crashes and market bubbles Psychological perspectives on borrowing, paying taxes, gambling, and charitable giving Psychological Perspectives on Financial Decision Making is a useful reference for researchers both in and outside of psychology, including decision-making experts, consumer psychologists, and behavioral economists.

The role of information is central to the academic debate on finance. This book provides a detailed, current survey of theoretical research into the effect on stock prices of the distribution of information, comparing and contrasting major models. It examines theoretical models that explain bubbles, technical analysis, and herding behavior. It also provides rational explanations for stock market crashes. Analyzing the implications of asymmetries in information is crucial in this area. This book provides a useful survey for graduate students.

The Handbook on Systemic Risk, written by experts in the field, provides researchers with an introduction to the multifaceted aspects of systemic risks facing the global financial markets. The Handbook explores the multidisciplinary approaches to analyzing this risk, the data requirements for further research, and the recommendations being made to avert financial crisis. The Handbook is designed to encourage new researchers to investigate a topic with immense societal implications as well as to provide, for those already actively involved within their own academic discipline, an introduction to the research being undertaken in other disciplines. Each chapter in the Handbook will provide researchers with a superior introduction to the field and with references to more advanced research articles. It is the hope of the editors that this Handbook will stimulate greater interdisciplinary academic research on the critically important topic of systemic risk in the global financial markets.

Recent years have seen the widespread application of Natural Computing algorithms (broadly defined in this context as computer algorithms whose design draws inspiration from phenomena in the natural world) for the purposes of financial modelling and optimisation. A related stream of work has also seen the application of learning mechanisms drawn from Natural Computing algorithms for the purposes of agent-based modelling in finance and economics. In this book we have collected a series of chapters which illustrate these two faces of Natural Computing. The first part of the book illustrates how algorithms inspired by the natural world can be used as problem solvers to uncover and optimise financial models. The second part of the book examines a number agent-based simulations of financial systems. This book follows on from Natural Computing in Computational Finance (Volume 100 in Springer’s Studies in Computational Intelligence series) which in turn arose from the success of EvoFIN 2007, the very first European Workshop on Evolutionary Computation in Finance & Economics held in Valencia, Spain in April 2007.