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Factor Forecasting Using International Targeted Predictors
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Book Synopsis Factor Forecasting Using International Targeted Predictors: the Case of German GDP by : Christian Schumacher
Download or read book Factor Forecasting Using International Targeted Predictors: the Case of German GDP written by Christian Schumacher and published by . This book was released on 2009 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting National Activity Using Lots of International Predictors by : Sandra Eickmeier
Download or read book Forecasting National Activity Using Lots of International Predictors written by Sandra Eickmeier and published by . This book was released on 2016 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: We look at how large international datasets can improve forecasts of national activity. We use the case of New Zealand, an archetypal small open economy. We apply "data-rich" factor and shrinkage methods to tackle the problem of efficiently handling hundreds of predictor data series from many countries. The methods covered are principal components, targeted predictors, weighted principal components, partial least squares, elastic net and ridge regression. Using these methods, we assess the marginal predictive content of international data for New Zealand GDP growth. We find that exploiting a large number of international predictors can improve forecasts of our target variable, compared to more traditional models based on small datasets. This is in spite of New Zealand survey data capturing a substantial proportion of the predictive information in the international data. The largest forecasting accuracy gains from including international predictors are at longer forecast horizons. The forecasting performance achievable with the data-rich methods differs widely, with shrinkage methods and partial least squares performing best. We also assess the type of international data that contains the most predictive information for New Zealand growth over our sample.
Book Synopsis Forecasting Economic Activity with Higher Frequency Targeted Predictors by : Guido Bulligan
Download or read book Forecasting Economic Activity with Higher Frequency Targeted Predictors written by Guido Bulligan and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting with Partial Least Squares When a Large Number of Predictors Are Available by : Seung C. Ahn
Download or read book Forecasting with Partial Least Squares When a Large Number of Predictors Are Available written by Seung C. Ahn and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider Partial Least Squares (PLS) estimation of a time-series forecasting model with the data containing a large number (T) of time series observations on each of a large number (N) of predictor variables. In the model, a subset or a whole set of the latent common factors in predictors are determinants of a single target variable to be forecasted. The factors relevant for forecasting the target variable, which we refer to as PLS factors, can be sequentially generated by a method called "Nonlinear Iterative Partial Least Squares" (NIPLS) algorithm. Two main findings from our asymptotic analysis are the following. First, the optimal number of the PLS factors for forecasting could be much smaller than the number of the common factors in the original predictor variables relevant for the target variable. Second, as more than the optimal number of PLS factors is used, the out-of-sample forecasting power of the factors could rather decrease while their in-sample explanatory power may increase. Our Monte Carlo simulation results confirm these asymptotic results. In addition, our simulation results indicate that unless very large samples are used, the out-of-sample forecasting power of the PLS factors is often higher when a smaller than the asymptotically optimal number of factors are used. We find that the out-of-sample forecasting power of the PLS factors often decreases as the second, third, and more factors are added, even if the asymptotically optimal number of the factors is greater than one.
Book Synopsis Macroeconomic Forecasting in the Era of Big Data by : Peter Fuleky
Download or read book Macroeconomic Forecasting in the Era of Big Data written by Peter Fuleky and published by Springer Nature. This book was released on 2019-11-28 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Book Synopsis The Use of Encompassing Tests for Forecast Combinations by : Turgut Kisinbay
Download or read book The Use of Encompassing Tests for Forecast Combinations written by Turgut Kisinbay and published by International Monetary Fund. This book was released on 2007-11 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper proposes an algorithm that uses forecast encompassing tests for combining forecasts. The algorithm excludes a forecast from the combination if it is encompassed by another forecast. To assess the usefulness of this approach, an extensive empirical analysis is undertaken using a U.S. macroecoomic data set. The results are encouraging as the algorithm forecasts outperform benchmark model forecasts, in a mean square error (MSE) sense, in a majority of cases.
Book Synopsis Economic Forecasts by : Ralf Brüggemann
Download or read book Economic Forecasts written by Ralf Brüggemann and published by Walter de Gruyter GmbH & Co KG. This book was released on 2016-11-21 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasts guide decisions in all areas of economics and finance. Economic policy makers base their decisions on business cycle forecasts, investment decisions of firms are based on demand forecasts, and portfolio managers try to outperform the market based on financial market forecasts. Forecasts extract relevant information from the past and help to reduce the inherent uncertainty of the future. The topic of this special issue of the Journal of Economics and Statistics is the theory and practise of forecasting and forecast evaluation and an overview of the state of the art of forecasting.
Book Synopsis Sufficient Forecasting Using Factor Models by : Jianqing Fan
Download or read book Sufficient Forecasting Using Factor Models written by Jianqing Fan and published by . This book was released on 2015 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional factor model implemented by the principal component analysis. Using the extracted factors, we develop a link-free forecasting method, called the sufficient forecasting, which provides several sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. Our method is also applicable to cross-sectional sufficient regression using extracted factors. {The connection between the sufficient forecasting and the deep learning architecture is explicitly stated.} The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We also show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables.
Book Synopsis Factor Forecasting Using International Targeted Predictors by : Christian Schumacher
Download or read book Factor Forecasting Using International Targeted Predictors written by Christian Schumacher and published by . This book was released on 2016 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper considers factor forecasting with national versus factor forecasting withinternational data. We forecast German GDP based on a large set of about 500 time series, consisting of German data as well as data from Euro-area and G7 countries. For factor estimation, we consider standard principal components as well as variable preselection prior to factor estimation using targeted predictors following Bai and Ng [Forecasting economic time series using targeted predictors, Journal of Econometrics 146 (2008), 304-317]. The results are as follows: Forecasting without data preselection favours the use of German data only, and no additional information content can be extracted from international data. However, when using targeted predictors for variable selection, international data generally improves the forecastability of German GDP.
Book Synopsis The Econometric Analysis of Seasonal Time Series by : Eric Ghysels
Download or read book The Econometric Analysis of Seasonal Time Series written by Eric Ghysels and published by Cambridge University Press. This book was released on 2001-06-18 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eric Ghysels and Denise R. Osborn provide a thorough and timely review of the recent developments in the econometric analysis of seasonal economic time series, summarizing a decade of theoretical advances in the area. The authors discuss the asymptotic distribution theory for linear nonstationary seasonal stochastic processes. They also cover the latest contributions to the theory and practice of seasonal adjustment, together with its implications for estimation and hypothesis testing. Moreover, a comprehensive analysis of periodic models is provided, including stationary and nonstationary cases. The book concludes with a discussion of some nonlinear seasonal and periodic models. The treatment is designed for an audience of researchers and advanced graduate students.
Book Synopsis Nowcasting and Forecasting GDP in Emerging Markets Using Global Financial and Macroeconomic Diffusion Indexes by : Oguzhan Cepni
Download or read book Nowcasting and Forecasting GDP in Emerging Markets Using Global Financial and Macroeconomic Diffusion Indexes written by Oguzhan Cepni and published by . This book was released on 2018 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we contribute to the nascent literature on nowcasting and forecasting GDP in emerging market economies using big data methods. This is done by analyzing the usefulness of various dimension reduction, machine learning and shrinkage methods including sparse principal component analysis (SPCA), the elastic net, the least absolute shrinkage operator, and least angle regression when constructing predictions using latent global macroeconomic and financial factors (diffusion indexes) in a dynamic factor model (DFM). We also utilize a judgmental dimension reduction method called the Bloomberg Relevance Index (BBG), which is an index that assigns a measure of importance to each variable in a dataset depending on the variable's usage by market participants. In our empirical analysis, we show that DFMs, when specified using dimension reduction methods (particularly BBG and SPCA), yield superior predictions, relative to benchmark linear econometric or simple DFMs. Moreover, global financial and macroeconomic (business cycle) diffusion indexes constructed using targeted predictors are found to be important in four of the five emerging market economies (including Brazil, Mexico, South Africa, and Turkey) that we study. These findings point to the importance of spillover effects across emerging market economies, and underscore the importance of parsimoniously characterizing such linkages when utilizing high dimensional global datasets.
Book Synopsis Practical Statistics for Data Scientists by : Peter Bruce
Download or read book Practical Statistics for Data Scientists written by Peter Bruce and published by "O'Reilly Media, Inc.". This book was released on 2017-05-10 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Book Synopsis Diagnosing Cloudiness from Global Numerical Weather Prediction Model Forecasts by :
Download or read book Diagnosing Cloudiness from Global Numerical Weather Prediction Model Forecasts written by and published by . This book was released on 1994 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monthly Report written by and published by . This book was released on 2009-05 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Predictive Inference by : Seymour Geisser
Download or read book Predictive Inference written by Seymour Geisser and published by Routledge. This book was released on 2017-11-22 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author's research has been directed towards inference involving observables rather than parameters. In this book, he brings together his views on predictive or observable inference and its advantages over parametric inference. While the book discusses a variety of approaches to prediction including those based on parametric, nonparametric, and nonstochastic statistical models, it is devoted mainly to predictive applications of the Bayesian approach. It not only substitutes predictive analyses for parametric analyses, but it also presents predictive analyses that have no real parametric analogues. It demonstrates that predictive inference can be a critical component of even strict parametric inference when dealing with interim analyses. This approach to predictive inference will be of interest to statisticians, psychologists, econometricians, and sociologists.
Book Synopsis Advances in Materials and Pavement Prediction by : Eyad Masad
Download or read book Advances in Materials and Pavement Prediction written by Eyad Masad and published by CRC Press. This book was released on 2018-07-16 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Materials and Pavement Performance Prediction contains the papers presented at the International Conference on Advances in Materials and Pavement Performance Prediction (AM3P, Doha, Qatar, 16- 18 April 2018). There has been an increasing emphasis internationally in the design and construction of sustainable pavement systems. Advances in Materials and Pavement Prediction reflects this development highlighting various approaches to predict pavement performance. The contributions discuss links and interactions between material characterization methods, empirical predictions, mechanistic modeling, and statistically-sound calibration and validation methods. There is also emphasis on comparisons between modeling results and observed performance. The topics of the book include (but are not limited to): • Experimental laboratory material characterization • Field measurements and in situ material characterization • Constitutive modeling and simulation • Innovative pavement materials and interface systems • Non-destructive measurement techniques • Surface characterization, tire-surface interaction, pavement noise • Pavement rehabilitation • Case studies Advances in Materials and Pavement Performance Prediction will be of interest to academics and engineers involved in pavement engineering.
Book Synopsis Deep learning to disease prediction on next generation sequencing and biomedical imaging data by : Saurav Mallik
Download or read book Deep learning to disease prediction on next generation sequencing and biomedical imaging data written by Saurav Mallik and published by Frontiers Media SA. This book was released on 2023-08-31 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:
