Nonlinear modelling has become increasingly important and widely used in economics. This valuable book brings together recent advances in the area including contributions covering cross-sectional studies of income distribution and discrete choice models, time series models of exchange rate dynamics and jump processes, and artificial neural network and genetic algorithm models of financial markets. Attention is given to the development of theoretical models as well as estimation and testing methods with a wide range of applications in micro and macroeconomics, labour and finance. The book provides valuable introductory material that is accessible to students and scholars interested in this exciting research area, as well as presenting the results of new and original research. Nonlinear Economic Models provides a sequel to Chaos and Nonlinear Models in Economics by the same editors.

Financial crises often transmit across geographical borders and different asset classes. Modeling these interactions is empirically challenging, and many of the proposed methods give different results when applied to the same data sets. In this book the authors set out their work on a general framework for modeling the transmission of financial crises using latent factor models. They show how their framework encompasses a number of other empirical contagion models and why the results between the models differ. The book builds a framework which begins from considering contagion in the bond markets during 1997-1998 across a number of countries, and culminates in a model which encompasses multiple assets across multiple countries through over a decade of crisis events from East Asia in 1997-1998 to the sub prime crisis during 2008. Program code to support implementation of similar models is available.

Financial econometrics brings financial theory and econometric methods together with the power of data to advance understanding of the global financial universe upon which all modern economies depend. Financial Econometric Modeling is an introductory text that meets the learning challenge of integrating theory, measurement, data, and software to understand the modern world of finance. Empirical applications with financial data play a central position in this book's exposition. Each chapter is a how-to guide that takes readers from ideas and theories through to the practical realities of modeling, interpreting, and forecasting financial data. The book reaches out to a wide audience of students, applied researchers, and industry practitioners, guiding readers of diverse backgrounds on the models, methods, and empirical practice of modern financial econometrics. Financial Econometric Modeling delivers a self-contained first course in financial econometrics, providing foundational ideas from financial theory and relevant econometric technique. From this foundation, the book covers a vast arena of modern financial econometrics that opens up empirical applications with data of the many different types that are now generated in financial markets. Every chapter follows the same principle ensuring that all results reported in the book may be reproduced using standard econometric software packages such as Stata or EViews, with a full set of data and programs provided to ensure easy implementation.