Download or read book Evaluation of Forecast Error Covariance Matrix written by Florence Rabier and published by . This book was released on 1993 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Test of Covariance Matrix Forecasting Methods written by Valeriy Zakamulin and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing a more accurate covariance matrix forecast can substantially improve the performance of optimized portfolios. Using out-of-sample tests, in this paper, we evaluate alternative covariance matrix forecasting methods by looking at (1) their forecast accuracy, (2) their ability to track the volatility of the minimum-variance portfolio, and (3) their ability to keep the volatility of the minimum-variance portfolio at a target level. We find large differences between the methods. Our results suggest that shrinkage of the sample covariance matrix improves neither the forecast accuracy nor the performance of minimum-variance portfolios. In contrast, switching from the sample covariance matrix forecast to a multivariate GARCH forecast reduces forecasting error and portfolio tracking error by at least half. Our findings also reveal that the exponentially weighted covariance matrix forecast performs only slightly worse than the multivariate GARCH forecast.
Download or read book Small Sample Estimates of the Variance Covariance Matrix of Forecast Error for Large Econometric Models written by George Roland Schink and published by . This book was released on 1971 with total page 958 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The National Meteorological Center written by National Meteorological Center (U.S.) and published by . This book was released on 1963 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computational Methods for Data Evaluation and Assimilation written by Dan Gabriel Cacuci and published by CRC Press. This book was released on 2016-04-19 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data evaluation and data combination require the use of a wide range of probability theory concepts and tools, from deductive statistics mainly concerning frequencies and sample tallies to inductive inference for assimilating non-frequency data and a priori knowledge. Computational Methods for Data Evaluation and Assimilation presents interdiscipli
Download or read book Evaluating Forecasts of Correlation Using Option Pricing written by Michael S. Gibson and published by . This book was released on 1997 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Estimating the Covariance Matrices of Analysis and Forecast Error in Variational Data Assimilation written by Michael Fisher and published by . This book was released on 1995 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Error Covariance Matrix Inflation in Ensemble Kalman Filter written by Guocan Wu and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The estimation accuracy of ensemble forecast errors is crucial to the assimilation results for all ensemble-based schemes. The ensemble Kalman filter (EnKF) is a widely used scheme in land surface data assimilation, without using the adjoint of a dynamical model. In EnKF, the forecast error covariance matrix is estimated as the sampling covariance matrix of the ensemble forecast states. However, past researches on EnKF have found that it can generally lead to an underestimate of the forecast error covariance matrix, due to the limited ensemble size, as well as the poor initial perturbations and model error. This can eventually result in filter divergence. Therefore, using inflation to further adjust the forecast error covariance matrix becomes increasingly important. In this chapter, a new structure of the forecast error covariance matrix is proposed to mitigate the problems with limited ensemble size and model error. An adaptive procedure equipped with a second-order least squares method is applied to estimate the inflation factors of forecast and observational error covariance matrices. The proposed method is tested on the well-known atmosphere-like Lorenz-96 model with spatially correlated observational systems. The experiment results show that the new structure of the forecast error covariance matrix and the adaptive estimation procedure lead to improvement of the analysis states.
Download or read book Efficient Estimation of Forecast Uncertainty Based on Recent Forecast Errors written by Malte Knüppel and published by . This book was released on 2016 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-step-ahead forecasts of forecast uncertainty in practice are often based on the horizon-specific sample means of recent squared forecast errors, where the number of available past forecast errors decreases one-to-one with the forecast horizon. In this paper, the efficiency gains from the joint estimation of forecast uncertainty for all horizons in such samples are investigated. Considering optimal forecasts, the efficiency gains can be substantial if the sample is not too large. If forecast uncertainty is estimated by seemingly unrelated regressions, the covariance matrix of the squared forecast errors does not have to be estimated, but simply needs to have a certain structure. In Monte Carlo studies it is found that seemingly unrelated regressions mostly yield estimates which are more efficient than the sample means even if the forecasts are not optimal. Seemingly unrelated regressions are used to address questions concerning the inflation forecast uncertainty of the Bank of England.
Download or read book A Companion to Economic Forecasting written by Michael P. Clements and published by Wiley-Blackwell. This book was released on 2002-03-15 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Companion to Economic Forecasting provides an accessible and comprehensive account of recent developments in economic forecasting. Each of the chapters has been specially written by an expert in the field, bringing together in a single volume a range of contrasting approaches and views. Uniquely surveying forecasting in a single volume, the Companion provides a comprehensive account of the leading approaches and modeling strategies that are routinely employed.
Download or read book Monthly Weather Review written by and published by . This book was released on 2007 with total page 1652 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evaluating Covariance Matrix Forecasts in a Value at Risk Framework written by Jose A. Lopez and published by . This book was released on 2002 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models, ranging from matrices of simple summary measures to covariance matrices implied from option prices, are available for generating such forecasts. In this paper, we evaluate the relative accuracy of different covariance matrix forecasts using standard statistical loss functions and a value-at-risk (VaR) framework. This framework consists of hypothesis tests examining various properties of VaR models based on these forecasts as well as an evaluation using a regulatory loss function.Using a foreign exchange portfolio, we find that implied covariance matrix forecasts appear to perform best under standard statistical loss functions. However, within the economic context of a VaR framework, the performance of VaR models depends more on their distributional assumptions than on their covariance matrix specification. Of the forecasts examined, simple specifications, such as exponentially-weighted moving averages of past observations, perform best with regard to the magnitude of VaR exceptions and regulatory capital requirements. These results provide empirical support for the commonly-used VaR models based on simple covariance matrix forecasts and distributional assumptions.
Download or read book Handbook of Economic Forecasting written by Graham Elliott and published by Elsevier. This book was released on 2013-08-23 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. Focuses on innovation in economic forecasting via industry applications Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications Makes details about economic forecasting accessible to scholars in fields outside economics
Download or read book Econometric Model Performance in Forecasting and Policy Assessment written by W. Allen Spivey and published by A E I Press. This book was released on 1979 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monograph on current econometric models used in economic forecasting and economic policy assessment - presents the methodology of linear and nonlinear simulation models, and includes a statistical analysis of forecast errors of major econometric models. Bibliography pp. 73 to 77, graphs and statistical tables.
Download or read book Data Assimilation written by Geir Evensen and published by Springer Science & Business Media. This book was released on 2006-12-22 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.
Download or read book Statistical Methods for Forecasting written by Bovas Abraham and published by John Wiley & Sons. This book was released on 2009-09-25 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.
Download or read book Handbook of Environmental and Ecological Statistics written by Alan E. Gelfand and published by CRC Press. This book was released on 2019-01-15 with total page 679 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.
