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We use a fractional difference model to reconcile two features of yields on US government bonds with modem asset pricing theory: the persistence of the short rate and variability of the long end of the yield curve. We suggest that this process might arise from the response of the heterogeneous agents to the changes in monetary policy.
We use parametric models of long memory in both the conditional mean and the conditional variance of inflation and monthly data in the USA, Japan and the UK for the period 1962-2001 to examine the relationship between inflation and inflation-uncertainty. In all countries, inflation significantly raises inflation-uncertainty as predicted by Friedman. Increased nominal uncertainty affects inflation in Japan and the UK but not in the same manner. The results from Japan support the Cukierman-Meltzer hypothesis. In the UK uncertainty surrounding the future inflation appears to have a mixed impact on inflation.
This article analyzes the inflation dynamics of several countries belonging to the European Monetary Union and of the UK. We estimate the two main parameters driving the degree of persistence in inflation and its uncertainty using a dual long memory process. We also investigate the possible existence of heterogeneity in inflation dynamics across Euro area countries and examine the link between nominal uncertainty and macroeconomic performance measured by the inflation and output growth rates. Strong evidence is provided for the hypothesis that increased inflation raises nominal uncertainty in all countries. However, we find that uncertainty surrounding future inflation has a mixed impact on output growth. This result brings out an important asymmetry in the transmission mechanism of monetary policy in Europe in addition to the difference in the economic sizes of the countries. We also investigate whether one can find a correlation between central bank independence and inflation policy. Our conclusion is that the most independent central banks are in countries where inflation falls in response to increased uncertainty.
The area of data analysis has been greatly affected by our computer age. For example, the issue of collecting and storing huge data sets has become quite simplified and has greatly affected such areas as finance and telecommunications. Even non-specialists try to analyze data sets and ask basic questions about their structure. One such question is whether one observes some type of invariance with respect to scale, a question that is closely related to the existence of long-range dependence in the data. This important topic of long-range dependence is the focus of this unique work, written by a number of specialists on the subject. The topics selected should give a good overview from the probabilistic and statistical perspective. Included will be articles on fractional Brownian motion, models, inequalities and limit theorems, periodic long-range dependence, parametric, semiparametric, and non-parametric estimation, long-memory stochastic volatility models, robust estimation, and prediction for long-range dependence sequences. For those graduate students and researchers who want to use the methodology and need to know the "tricks of the trade," there will be a special section called "Mathematical Techniques." Topics in the first part of the book are covered from probabilistic and statistical perspectives and include fractional Brownian motion, models, inequalities and limit theorems, periodic long-range dependence, parametric, semiparametric, and non-parametric estimation, long-memory stochastic volatility models, robust estimation, prediction for long-range dependence sequences. The reader is referred to more detailed proofs if already found in the literature. The last part of the book is devoted to applications in the areas of simulation, estimation and wavelet techniques, traffic in computer networks, econometry and finance, multifractal models, and hydrology. Diagrams and illustrations enhance the presentation. Each article begins with introductory background material and is accessible to mathematicians, a variety of practitioners, and graduate students. The work serves as a state-of-the art reference or graduate seminar text.
Following theseminal Palgrave Handbook of Econometrics: Volume I , this second volume brings together the finestacademicsworking in econometrics today andexploresapplied econometrics, containing contributions onsubjects includinggrowth/development econometrics and applied econometrics and computing.
Stochastic volatility is the main concept used in the fields of financial economics and mathematical finance to deal with time-varying volatility in financial markets. This work brings together some of the main papers that have influenced this field, andshows that the development of this subject has been highly multidisciplinary.
Calvet and Fisher present a powerful, new technique for volatility forecasting that draws on insights from the use of multifractals in the natural sciences and mathematics and provides a unified treatment of the use of multifractal techniques in finance. A large existing literature (e.g., Engle, 1982; Rossi, 1995) models volatility as an average of past shocks, possibly with a noise component. This approach often has difficulty capturing sharp discontinuities and large changes in financial volatility. Their research has shown the advantages of modelling volatility as subject to abrupt regime changes of heterogeneous durations. Using the intuition that some economic phenomena are long-lasting while others are more transient, they permit regimes to have varying degrees of persistence. By drawing on insights from the use of multifractals in the natural sciences and mathematics, they show how to construct high-dimensional regime-switching models that are easy to estimate, and substantially outperform some of the best traditional forecasting models such as GARCH. The goal of Multifractal Volatility is to popularize the approach by presenting these exciting new developments to a wider audience. They emphasize both theoretical and empirical applications, beginning with a style that is easily accessible and intuitive in early chapters, and extending to the most rigorous continuous-time and equilibrium pricing formulations in final chapters. Presents a powerful new technique for forecasting volatility Leads the reader intuitively from existing volatility techniques to the frontier of research in this field by top scholars at major universities The first comprehensive book on multifractal techniques in finance, a cutting-edge field of research
Eric Barthalon applies the neglected theory of psychological time and memory decay of Nobel Prize–winning economist Maurice Allais (1911–2010) to model investors' psychology in the present context of recurrent financial crises. Shaped by the behavior of the demand for money during episodes of hyperinflation, Allais's theory suggests economic agents perceive the flow of clocks' time and forget the past at a context-dependent pace: rapidly in the presence of persistent and accelerating inflation and slowly in the event of the opposite situation. Barthalon recasts Allais's work as a general theory of "expectations" under uncertainty, narrowing the gap between economic theory and investors' behavior. Barthalon extends Allais's theory to the field of financial instability, demonstrating its relevance to nominal interest rates in a variety of empirical scenarios and the positive nonlinear feedback that exists between asset price inflation and the demand for risky assets. Reviewing the works of the leading protagonists in the expectations controversy, Barthalon exposes the limitations of adaptive and rational expectations models and, by means of the perceived risk of loss, calls attention to the speculative bubbles that lacked the positive displacement discussed in Kindleberger's model of financial crises. He ultimately extrapolates Allaisian theory into a pragmatic approach to investor behavior and the natural instability of financial markets. He concludes with the policy implications for governments and regulators. Balanced and coherent, this book will be invaluable to researchers working in macreconomics, financial economics, behavioral finance, decision theory, and the history of economic thought.
Unlike uncertain dynamical systems in physical sciences where models for prediction are somewhat given to us by physical laws, uncertain dynamical systems in economics need statistical models. In this context, modeling and optimization surface as basic ingredients for fruitful applications. This volume concentrates on the current methodology of copulas and maximum entropy optimization. This volume contains main research presentations at the Sixth International Conference of the Thailand Econometrics Society held at the Faculty of Economics, Chiang Mai University, Thailand, during January 10-11, 2013. It consists of keynote addresses, theoretical and applied contributions. These contributions to Econometrics are somewhat centered around the theme of Copulas and Maximum Entropy Econometrics. The method of copulas is applied to a variety of economic problems where multivariate model building and correlation analysis are needed. As for the art of choosing copulas in practical problems, the principle of maximum entropy surfaces as a potential way to do so. The state-of-the-art of Maximum Entropy Econometrics is presented in the first keynote address, while the second keynote address focusses on testing stationarity in economic time series data.
The stochastic calculus of variations of Paul Malliavin (1925 - 2010), known today as the Malliavin Calculus, has found many applications, within and beyond the core mathematical discipline. Stochastic analysis provides a fruitful interpretation of this calculus, particularly as described by David Nualart and the scores of mathematicians he influences and with whom he collaborates. Many of these, including leading stochastic analysts and junior researchers, presented their cutting-edge research at an international conference in honor of David Nualart's career, on March 19-21, 2011, at the University of Kansas, USA. These scholars and other top-level mathematicians have kindly contributed research articles for this refereed volume.