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This contributed volume combines approaches of the current inequality debate with aspects of finance based on profound macroeconomic model analyses. With the financial crisis from 2007, not only output decreased tremendously, but also inequality has risen since then.
This book provides an investor-friendly presentation of the premises and applications of the quantitative finance models governing investment in one asset class of publicly traded stocks, specifically real estate investment trusts (REITs). The models provide highly advanced analytics for REIT investment, including: portfolio optimization using both historic and predictive return estimation; model backtesting; a complete spectrum of risk assessment and management tools with an emphasis on early warning systems, risk budgeting, estimating tail risk, and factor analysis; derivative valuation; and incorporating ESG ratings into REIT investment. These quantitative finance models are presented in a unified framework consistent with dynamic asset pricing (rational finance). Given its scope and practical orientation, this book will appeal to investors interested in portfolio optimization and innovative tools for investment risk assessment.
The field of econometrics has gone through remarkable changes during the last thirty-five years. This development becomes apparent when looking at the biography of an econometrician whose illustrious research and teaching career started about thirty-five years ago and who will retire very soon after his 65th birthday.
Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade.
Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts.
The book presents applications of stochastic calculus to derivative security pricing and interest rate modelling.
This volume is centered around the issue of market design and resulting market dynamics. Computational methods are used to replicate and understand market dynamics emerging from interaction of heterogeneous agents, and to develop models that have predictive power for complex market dynamics.
This volume is centered around the issue of market design and resulting market dynamics. Computational methods are used to replicate and understand market dynamics emerging from interaction of heterogeneous agents, and to develop models that have predictive power for complex market dynamics.
The basic characteristic of Modern Linear and Nonlinear Econometrics is that it presents a unified approach of modern linear and nonlinear econometrics in a concise and intuitive way.
Provides the reader with both the statistical background and the software tools for detecting nonlinear behavior in time series data. This book describes various detection techniques including Engle's LaGrange Multiplier test for conditional hetero-skedasticity and tests based on the correlation dimension and on the estimated bispectrum.
Empirical Studies on Volatility in International Stock Markets describes the existing techniques for the measurement and estimation of volatility in international stock markets with emphasis on the SV model and its empirical application.
Some recent developments in the mathematics of optimization, including the concepts of invexity and quasimax, have not yet been applied to models of economic growth, and to finance and investment. Their applications to these areas are shown in this book.
This book demonstrates how public debt shows feedback effects affecting economic growth and welfare. It gives insights into the sustainability of public debt in developed and developing countries.
Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade.
The purpose of Dynamic Programming in Economics is twofold: (a) to provide a rigorous, but not too complicated, treatment of optimal growth models in infinite discrete time horizon, (b) to train the reader to the use of optimal growth models and hence to help him to go further in his research.
Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts.
The uneven geographical distribution of economic activities is a huge challenge worldwide and also for the European Union. In Krugman's New Economic Geography economic systems have a simple spatial structure. At the highest level, economic geography models give a bird eye's view of spatial dynamics.
In recent years nonlinearities have gained increasing importance in economic and econometric research, particularly after the financial crisis and the economic downturn after 2007. This book contains theoretical, computational and empirical papers that incorporate nonlinearities in econometric models and apply them to real economic problems.
The book examines problems associated with green growth and sustainable development on the basis of recent contributions in economics, natural sciences and applied mathematics, especially optimal control theory.
In recent years nonlinearities have gained increasing importance in economic and econometric research, particularly after the financial crisis and the economic downturn after 2007. This book contains theoretical, computational and empirical papers that incorporate nonlinearities in econometric models and apply them to real economic problems.
The book examines problems associated with green growth and sustainable development on the basis of recent contributions in economics, natural sciences and applied mathematics, especially optimal control theory.
This contributed volume combines approaches of the current inequality debate with aspects of finance based on profound macroeconomic model analyses. With the financial crisis from 2007, not only output decreased tremendously, but also inequality has risen since then.
The major goal of the book is to create an environment for matching different d- ciplinary approaches to studying economic growth.
The uneven geographical distribution of economic activities is a huge challenge worldwide and also for the European Union. In Krugman's New Economic Geography economic systems have a simple spatial structure. At the highest level, economic geography models give a bird eye's view of spatial dynamics.
Dynamic Modeling of Monetary and Fiscal Cooperation Among Nations analyzes coordination of monetary and fiscal stabilization policies between countries and currency areas using a dynamic game approach.
The major goal of the book is to create an environment for matching different d- ciplinary approaches to studying economic growth.
The authors give an advanced treatment of macroeconomic topics such as the Phillips curve, forward and backward looking behavior, open economy macrodynamics, structural macroeconometric model building as well as the empirics of Keynesian oriented macro models.
Written in honor of Emeritus Professor Georges Prat (University of Paris Nanterre, France), this book includes contributions from eminent authors on a range of topics that are of interest to researchers and graduates, as well as investors and portfolio managers. The topics discussed include the effects of information and transaction costs on informational and allocative market efficiency, bubbles and stock price dynamics, paradox of rational expectations and the principle of limited information, uncertainty and expectation hypotheses, oil price dynamics, and nonlinearity in asset price dynamics.
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