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. Eugenie Hol develops various extensions of the SV model, which allow for additional variables in both the mean and the variance equation. In addition, the forecasting performance of SV models is compared not only to that of the well-established GARCH model but also to implied volatility and so-called realised volatility models which are based on intraday volatility measures. The intended readers are financial professionals who seek to obtain more accurate volatility forecasts and wish to gain insight about state-of-the-art volatility modelling techniques and their empirical value, and academic researchers and students who are interested in financial market volatility and want to obtain an updated overview of the various methods available in this area.
Assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; and models from economic theory providing plausible micro foundations for the occurrence of long memory in economics.
Connections among different assets, asset classes, portfolios, and the stocks of individual institutions are critical in examining financial markets. Interest in financial markets implies interest in underlying macroeconomic fundamentals. In Financial and Macroeconomic Connectedness, Frank Diebold and Kamil Yilmaz propose a simple framework for defining, measuring, and monitoring connectedness, which is central to finance and macroeconomics. These measures of connectedness are theoretically rigorous yet empirically relevant. The approach to connectedness proposed by the authors is intimately related to the familiar econometric notion of variance decomposition. The full set of variance decompositions from vector auto-regressions produces the core of the 'connectedness table.' The connectedness table makes clear how one can begin with the most disaggregated pair-wise directional connectedness measures and aggregate them in various ways to obtain total connectedness measures. The authors also show that variance decompositions define weighted, directed networks, so that these proposed connectedness measures are intimately related to key measures of connectedness used in the network literature. After describing their methods in the first part of the book, the authors proceed to characterize daily return and volatility connectedness across major asset (stock, bond, foreign exchange and commodity) markets as well as the financial institutions within the U.S. and across countries since late 1990s. These specific measures of volatility connectedness show that stock markets played a critical role in spreading the volatility shocks from the U.S. to other countries. Furthermore, while the return connectedness across stock markets increased gradually over time the volatility connectedness measures were subject to significant jumps during major crisis events. This book examines not only financial connectedness, but also real fundamental connectedness. In particular, the authors show that global business cycle connectedness is economically significant and time-varying, that the U.S. has disproportionately high connectedness to others, and that pairwise country connectedness is inversely related to bilateral trade surpluses.
Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel
From the Introduction: This volume is dedicated to the remarkable career of Professor Peter Schmidt and the role he has played in mentoring us, his PhD students. Peter’s accomplishments are legendary among his students and the profession. Each of the papers in this Festschrift is a research work executed by a former PhD student of Peter’s, from his days at the University of North Carolina at Chapel Hill to his time at Michigan State University. Most of the papers were presented at The Conference in Honor of Peter Schmidt, June 30 - July 2, 2011. The conference was largely attended by his former students and one current student, who traveled from as far as Europe and Asia to honor Peter. This was a conference to celebrate Peter’s contribution to our contributions. By “our contributions” we mean the research papers that make up this Festschrift and the countless other publications by his students represented and not represented in this volume. Peter’s students may have their families to thank for much that is positive in their lives. However, if we think about it, our professional lives would not be the same without the lessons and the approaches to decision making that we learned from Peter. We spent our days together at Peter’s conference and the months since reminded of these aspects of our personalities and life goals that were enhanced, fostered, and nurtured by the very singular experiences we have had as Peter’s students. We recognized in 2011 that it was unlikely we would all be together again to celebrate such a wonderful moment in ours and Peter’s lives and pledged then to take full advantage of it. We did then, and we are now in the form of this volume.
This work is an exploration of the global market dynamics, their intrinsic natures, common trends and dynamic interlinkages during the stock market crises over the last twelve years. The study isolates different phases of crisis and differentiates between any crisis that remains confined to the region and those that take up a global dimension. The latent structure of the global stock market, the inter-regional and intra-regional stock market dynamics around the crises are analyzed to get a complete picture of the structure of the global stock market. The study further probing into the inherent nature of the global stock market in generating crisis finds the global market to be chaotic thus making the system intrinsically unstable or at best to follow knife-edge stability. The findings have significant bearing at theoretical level and on policy decisions.
An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.
This book provides fresh insights into concepts, methods and new research findings on the causes of excessive food price volatility. It also discusses the implications for food security and policy responses to mitigate excessive volatility. The approaches applied by the contributors range from on-the-ground surveys, to panel econometrics and innovative high-frequency time series analysis as well as computational economics methods. It offers policy analysts and decision-makers guidance on dealing with extreme volatility.
The classical ARMA models have limitations when applied to the field of financial and monetary economics. Financial time series present nonlinear dynamic characteristics and the ARCH models offer a more adaptive framework for this type of problem. This book surveys the recent work in this area from the perspective of statistical theory, financial models, and applications and will be of interest to theorists and practitioners. From the view point of statistical theory, ARCH models may be considered as specific nonlinear time series models which allow for an exhaustive study of the underlying dynamics. It is possible to reexamine a number of classical questions such as the random walk hypothesis, prediction interval building, presence of latent variables etc., and to test the validity of the previously studied results. There are two main categories of potential applications. One is testing several economic or financial theories concerning the stocks, bonds, and currencies markets, or studying the links between the short and long run. The second is related to the interventions of the banks on the markets, such as choice of optimal portfolios, hedging portfolios, values at risk, and the size and times of block trading.
