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Robust Forecast Comparison
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Book Synopsis Robust Forecast Comparison by : Sainan Jin
Download or read book Robust Forecast Comparison written by Sainan Jin and published by . This book was released on 2016 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence of the use of misspecified models in multiple model comparisons, relative forecast rankings are loss function dependent. This paper addresses this issue by using a novel criterion for forecast evaluation which is based on the entire distribution of forecast errors. We introduce the concepts of general-loss (GL) forecast superiority and convex-loss (CL) forecast superiority; and develop tests for GL (CL) superiority that are based on an out-of-sample generalization of the tests introduced by Linton, Maasoumi and Whang (2005). The asymptotic null distributions of our test statistics are nonstandard, and resampling procedures are used to obtain critical values. Additionally, the tests are consistent and have nontrivial local power under a sequence of local alternatives. In addition to the stationary case, we outline theory extending our tests to the case of heterogeneity induced by distributional change over time. Monte Carlo simulations suggest that the tests perform reasonably well in finite samples; and an application to exchange rate data indicates that our tests can help identify superior forecasting models, regardless of loss function.
Book Synopsis Comparing Forecast Performance with State Dependence by : Florens Odendahl
Download or read book Comparing Forecast Performance with State Dependence written by Florens Odendahl and published by . This book was released on 2020 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a novel forecast comparison methodology to evaluate models' relative forecasting performance when the latter is a state-dependent function of economic variables. In our bench-mark case, the relative forecasting performance, measured by the forecast loss differential, is modeled via a threshold model. Importantly, we allow the threshold that triggers the switch from one state to the next to be unknown, leading to a non-standard test statistic due to the presence of a nuisance parameter. Existing tests either assume a constant out-of-sample forecast performance or use non-parametric techniques robust to time-variation; consequently, they may lack power against state-dependent predictability. Importantly, our approach is applicable to point forecasts as well as predictive densities. Monte Carlo results suggest that our proposed test statistics perform well in finite samples and have better power than existing tests in selecting the best forecasting model in the presence of state dependence. Our test statistics uncover "pockets of predictability" in U.S. equity premia forecasts; the pockets are a state-dependent function of stock market volatility. Models using economic predictors perform significantly worse than a simple mean forecast in periods of high volatility, but, in periods of low volatility, the use of economic predictors may lead to small forecast improvements.
Book Synopsis Robust Forecasting by : Timothy Christensen
Download or read book Robust Forecasting written by Timothy Christensen and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Evaluating CPB's Published GDP Growth Forecasts by :
Download or read book Evaluating CPB's Published GDP Growth Forecasts written by and published by . This book was released on 2008 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Forecast Methods and Monitoring During Structural Change by : Jana Eklund
Download or read book Robust Forecast Methods and Monitoring During Structural Change written by Jana Eklund and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We examine how to forecast after a recent break, introducing a new approach, monitoring for change and then combining forecasts from a model using the full sample and another using post-break data. We compare this to some robust techniques: rolling regressions, forecast averaging over all possible windows and exponentially weighted forecasts. We examine relative efficacy with Monte Carlo experiments given single deterministic or multiple stochastic location shifts, and for many UK and US macroeconomic series. No single method is uniformly superior. Monitoring brings only small improvements, so robust methods are preferred.
Book Synopsis Forecasting: principles and practice by : Rob J Hyndman
Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Book Synopsis Robustness in Statistical Forecasting by : Yuriy Kharin
Download or read book Robustness in Statistical Forecasting written by Yuriy Kharin and published by Springer Science & Business Media. This book was released on 2013-09-04 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers solutions to such topical problems as developing mathematical models and descriptions of typical distortions in applied forecasting problems; evaluating robustness for traditional forecasting procedures under distortionism and more.
Book Synopsis Robustness in Econometrics by : Vladik Kreinovich
Download or read book Robustness in Econometrics written by Vladik Kreinovich and published by Springer. This book was released on 2017-02-11 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.
Book Synopsis Volatility Forecast Comparison Using Imperfect Volatility Proxies by : Andrew J. Patton
Download or read book Volatility Forecast Comparison Using Imperfect Volatility Proxies written by Andrew J. Patton and published by . This book was released on 2010 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcomes in standard methods for comparing conditional variance forecasts. We derive necessary and sufficient conditions on functional form of the loss function for the ranking of competing volatility forecasts to be robust to the presence of noise in the volatility proxy, and derive some interesting special cases of this class of quot;robustquot; loss functions. We motivate the theory with analytical results on the distortions caused by some widely-used loss functions, when used with standard volatility proxies such as squared returns, the intra-daily range or realised volatility. The methods are illustrated with an application to the volatility of returns on IBM over the period 1993 to 2003.
Book Synopsis Guidelines on Ensemble Prediction Systems and Forecasting by : World Meteorological Organization
Download or read book Guidelines on Ensemble Prediction Systems and Forecasting written by World Meteorological Organization and published by . This book was released on 2012 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Handbook of Economic Forecasting by : Graham Elliott
Download or read book Handbook of Economic Forecasting written by Graham Elliott and published by Elsevier. This book was released on 2013-10-24 with total page 1386 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
Book Synopsis Forecasting Exchange Rates by : Arie Preminger
Download or read book Forecasting Exchange Rates written by Arie Preminger and published by . This book was released on 2010 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictability of two exchange rates at the 1-, 3- and 6-month horizon. We compare the predictive ability of the robust models to those of the random walk (RW), the standard linear autoregressive (AR) and neural networks (NN) models in terms of forecast accuracy and sign predictability measures. We find that robust models tend to improve the forecasting accuracy of the AR and of the NN at all time horizons, and even of the RW for forecasts carried out at the 1-month horizon. Robust models are also shown to have significant market timing ability at all forecast horizons.
Book Synopsis Handbook of Economic Forecasting by : G. Elliott
Download or read book Handbook of Economic Forecasting written by G. Elliott and published by Elsevier. This book was released on 2006-07-14 with total page 1071 pages. Available in PDF, EPUB and Kindle. Book excerpt: Section headings in this handbook include: 'Forecasting Methodology; 'Forecasting Models'; 'Forecasting with Different Data Structures'; and 'Applications of Forecasting Methods.'.
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 Working Papers by : Rutgers University Department of Economics
Download or read book Working Papers written by Rutgers University Department of Economics and published by . This book was released on 1995 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting in the Presence of Structural Breaks and Model Uncertainty by : David E. Rapach
Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach and published by Emerald Group Publishing. This book was released on 2008-02-29 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.
Book Synopsis A Forecast Comparison of Volatility Models Using Realized Volatility by : Takahiro Hattori
Download or read book A Forecast Comparison of Volatility Models Using Realized Volatility written by Takahiro Hattori and published by . This book was released on 2018 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper first evaluates the volatility modeling in the Bitcoin market in terms of its realized volatility, which is considered to be a reliable proxy of its true volatility. In addition, we also rely on the important work by Patton (2011), which shows good measures for making the forecast accuracy robust to noise in the imperfect volatility proxy. We empirically show that (1) the asymmetric volatility models such as EGARCH and APARCH have a higher predictability, and (2) the volatility model with normal distribution performs better than the fat-tailed distribution such as skewed t distribution.
