Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

This book provides an introductory treatment of time series econometrics, a subject that is of key importance to both students and practitioners of economics. It contains material that any serious student of economics and finance should be acquainted with if they are seeking to gain an understanding of a real functioning economy.

Palgrave Handbook of Econometrics comprises 'landmark' essays by the world's leading scholars and provides authoritative and definitive guidance in key areas of econometrics. With definitive contributions on the subject, the Handbook is an essential source of reference for professional econometricians, economists, researchers and students. Volume I covers developments in theoretical econometrics, including essays on the methodology and history of econometrics, developments in time-series and cross-section econometrics, modelling with integrated variables, Bayesian econometrics, simulation methods and a selection of special topics.

This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.

This authoritative and wide-ranging collection presents over fifty of the most important articles on forecasting - a technique that lies at the heart of economic policy and decision-making. This comprehensive two volume set presents the major papers in macroeconomic forecasting and policy making; time series forecasting; the econometrics of forecasting; forecast evaluation; forecasting with leading indicators; forecasting in finance and economic forecasting using surveys.

The behaviour of long term, secular trends and shorter run, business cycle, movements in economic data have long been a concern of economists, statisticians and econometricians. The isolation and interpretation of cyclical movements was the basis for early empirical work in economics, while the early dynamic models were constructed to reproduce cyclical fluctuations. The first econometric models analysed the cyclical path of economies, while focusing attention on the processes that generate trends in economic variables has led to the recent revolution in time series econometrics. Long Term Trends and Business Cycles brings together the key contributions in these various areas and comprises 54 papers published from 1923 to 1999. It will be of interest to economists and econometricians engaged in the analysis of macroeconomic time series.

The forecasting of financial markets has engaged the attention of market professionals and academic economists and statisticians for many years, and has also attracted the interest of numerous 'amateur' investors. This book brings together key papers in this wide field. After considering some of the earliest attempts at forecasting, it provides an insight into the theoretical underpinnings of the subject, investigates the random walk model, and examines various financial markets, volatility and density forecasting, the forecasting of extreme events, trading rules, technical analysis and high frequency data.

Modelling trends and cycles in economic time series has a long history, with the use of linear trends and moving averages forming the basic tool kit of economists until the 1970s. Several developments in econometrics then led to an overhaul of the techniques used to extract trends and cycles from time series. In this second edition, Terence Mills expands on the research in the area of trends and cycles over the last (almost) two decades, to highlight to students and researchers the variety of techniques and the considerations that underpin their choice for modelling trends and cycles.

This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.

"Palgrave Handbook of Econometrics" is comprised of landmark essays by the world's leading scholars and provides authoritative and definitive guidance in key areas of econometrics. With definitive contributions on the subject, the Handbook is an essential source of reference for professional econometricians, economists, researchers and students.
Volume I covers developments in theoretical econometrics, including essays on the methodology and history of econometrics, developments in time-series and cross-section econometrics, modelling with integrated variables, Bayesian econometrics, simulation methods and a selection of special topics.

Terence Mills' best-selling graduate textbook provides detailed coverage of the latest research techniques and findings relating to the empirical analysis of financial markets. In its previous editions it has become required reading for many graduate courses on the econometrics of financial modelling. The third edition, co-authored with Raphael Markellos, contains a wealth of new material reflecting the developments of the last decade. Particular attention is paid to the wide range of nonlinear models that are used to analyse financial data observed at high frequencies and to the long memory characteristics found in financial time series. The central material on unit root processes and the modelling of trends and structural breaks has been substantially expanded into a chapter of its own. There is also an extended discussion of the treatment of volatility, accompanied by a new chapter on nonlinearity and its testing.

The application of time series techniques in economics has become increasingly important, both for forecasting purposes and in the empirical analysis of time series in general. This book brings together recent research at the frontiers of the subject and analyzes the areas of time series analysis of most importance to applied economics. The author discusses three basic areas of time series analysis: univariate models, multivariate models, and nonlinear models. Particular emphasis is placed on applications of the theory to important areas of applied economics and on the computer software and programs needed to implement the techniques. It is an up-to-date text, extending the basic techniques of analysis to cover the development of methods that can be used to analyze a wide range of economic problems.