Essays On Forecasting With Survey Data And Many Predictors
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Essays On Forecasting With Survey Data And Many Predictors
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Author : Yongchen Zhao
language : en
Publisher:
Release Date : 2014
Essays On Forecasting With Survey Data And Many Predictors written by Yongchen Zhao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Consumers categories.
Essays On Forecasting Macroeconomic Variables Using Mixed Frequency Data
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Author : Kihwan Kim
language : en
Publisher:
Release Date : 2016
Essays On Forecasting Macroeconomic Variables Using Mixed Frequency Data written by Kihwan Kim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Economic forecasting categories.
This dissertation investigate the forecasting performance of mixed frequency factor models with mixed frequency dataset. In the first chapter, I consider the mixed fre- quency factor approach used in ADS (2009) to construct their co-incident activity index, and ask the question of whether a class of mixed frequency indexes is useful for predicting the future values of quarterly U.S. real GDP growth and monthly industrial production, unemployment and inflation. My forecasting assessment of the mixed frequency factor model is performed in conjunction with standard prediction models such as autoregression, multivariate distributed lag models, and diffu- sion index models of the variety examined by Stock and Watson (2002a). The main findings of the study are as follows. First, prediction models using only mixed frequency indexes show their best performance at short-term GDP forecasting horizons, and are particularly good during recessions. Second, prediction models using both mixed frequency indexes and diffusion indexes forecast monthly variables more accurately than models using single frequency type indexes. Third, model combi- nations perform relatively poorly in real GDP forecasting contexts, although they perform better when applied to the prediction of monthly variables. Fourth, survey information can be conveniently exploited with higher frequency variables such as daily and weekly variables, and mixed frequency indexes using such survey information are sometimes useful in forecasting lower frequency variables. In the second chapter, I evaluate the predictive performance of hybrid models for forecasting four economic variables. The hybrid approach takes into account the notion that simple autoregression and sophisticated factor models' predictive abilities may change according to the state of the econ- omy. I find that hybrid prediction models produce better forecasts than standard models and than combination models, in most cases, using the same menu of models discussed above. For example, in one-quarter ahead GDP forecasts, the best hybrid model reduces the mean squared forecast error of the best model combinations and the linear models by 14 and 11 percent, on average, respectively. More specifically, the mean squared forecast error of autoregression is reduced by approximately 35 percent. In 12-month ahead predictions of inflation, the best hybrid model improves the best model combinations and the linear models by 11 percent and 16 percent, on average, respectively. This number again increases, in this case to 36 percent, when comparing only with autoregression. One reason for these findings is that hybrid prediction models more effectively utilize survey information.
Essays In Honor Of Joon Y Park
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Author : Yoosoon Chang
language : en
Publisher: Emerald Group Publishing
Release Date : 2023-04-24
Essays In Honor Of Joon Y Park written by Yoosoon Chang and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-24 with Business & Economics categories.
Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.
Essays On The Use Of Business Survey And Expectations Data For Econometric Prediction
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Author : Susmita Dasgupta
language : en
Publisher:
Release Date : 19??
Essays On The Use Of Business Survey And Expectations Data For Econometric Prediction written by Susmita Dasgupta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 19?? with Business cycles categories.
Essays In Forecasting Financial Markets With Predictive Analytics Techniques
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Author : Azzam J. M. A. H. Alroomi
language : en
Publisher:
Release Date : 2018
Essays In Forecasting Financial Markets With Predictive Analytics Techniques written by Azzam J. M. A. H. Alroomi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Essays In Honor Of M Hashem Pesaran
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Author : Alexander Chudik
language : en
Publisher: Emerald Group Publishing
Release Date : 2022-01-18
Essays In Honor Of M Hashem Pesaran written by Alexander Chudik and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-18 with Business & Economics categories.
The collection of chapters in Volume 43 Part A of Advances in Econometrics serves as a tribute to one of the most innovative, influential, and productive econometricians of his generation, Professor M. Hashem Pesaran.
Essays In Forecasting
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Author : Nii Ayi Christian Armah
language : en
Publisher:
Release Date : 2009
Essays In Forecasting written by Nii Ayi Christian Armah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Economic forecasting categories.
This dissertation comprises three essays in macroeconomic forecasting. The first essay discusses model selection and predictive accuracy tests in the context of parameter and model uncertainty under recursive and rolling estimation schemes. Particular emphasis is placed on the construction of valid bootstrap procedures for calculating the impact of parameter estimation error on the class of test statistics with limiting distributions that are functionals of Gaussian processes. Results of an empirical investigation of the marginal predictive content of money for income are also presented. The second essay outlines a number of approaches to the selection of factor proxies (observed variables that proxy unobserved estimated factors) using statistics based on large sample datasets. This approach to factor proxy selection is examined via a small Monte Carlo experiment and a set of prediction experiments, where evidence supporting our proposed methodology is presented. The third essay compares the predictive content of a set of macroeconomic indicators with that of various other observable variables that act as proxies to factors constructed using diffusion index methodology. The analysis suggests that certain spreads constructed as the difference between short or long term debt instruments and the federal funds rate are found to be useful indicators. Surprisingly, traditional spreads, such as the yield curve slope and the reverse yield gap are not found to provide additional predictive power.
Essays In Forecasting Financial Markets With Predictive Analytics Techniques
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Author : Azzam Alroomi
language : en
Publisher:
Release Date : 2018
Essays In Forecasting Financial Markets With Predictive Analytics Techniques written by Azzam Alroomi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
This PhD dissertation comprises four essays on forecasting financial markets with unsupervised predictive analytics techniques, most notably time series extrapolation methods and artificial neural networks. Key objectives of the research were reproducibility and replicability, which are fundamental principles in management science and, as such, the implementation of all of the suggested algorithms has been fully automated and completely unsupervised in R.As with any predictive analytics exercise, computational intensiveness is a significant challenge and criterion of performance and, thus, both forecasting accuracy and uncertainty as well as computational times are reported in all essays. Multiple horizons, multiple methods and benchmarks and multiple metrics are employed as dictated by good practice in empirical forecasting exercises.The essays evolve in nature as each one is based on the previous one, testing one more condition as the essays progress, outlined in sequence as follows: which method wins overall in a very extensive evaluation over five frequencies (yearly, quarterly, monthly, weekly and daily data) over 18 time series of stocks with the biggest capitalization from the FTSE 100, over the last 20 years (first essay); the impact of horizon in this exercise and how this promotes different winners for different horizons (second essay); the impact of using uncertainty in the form of maximum-minimum values per period, despite still being interested in forecasting the mean expected value over the next period; and introducing a second variable capturing all other aspects of the behavioural nature of the financial environment - the trading volume - and evaluating whether this improves forecasting performance or not.The whole endeavour required the use of the High Performance Computing Wales (HPC Wales) for a significant amount of time, incurring computational costs that ultimately paid off in terms of increased forecasting accuracy for the AI approaches; the whole exercise for one series can be repeated on a fast laptop device (i7 with 16 GB of memory).Overall (forecasting) horses for (data) courses were once again proved to perform best, and the fact that one method cannot win under all conditions was once more evidenced. The introduction of uncertainty (in terms of range for every period), as well as volume as a second variable capturing environmental aspects, was beneficial with regard to forecasting accuracy and, overall, the research provided empirical evidence that predictive analytics approaches have a future in such a forecasting context.Given this was a predictive analytics exercise, focus was placed on forecasting levels (monetary values) and not log-returns; and out-of-sample forecasting accuracy, rather than causality, was a primary objective, thus multiple regression models were not considered as benchmarks.As in any empirical predicting analytics exercise, more time series, more artificial intelligence methods, more metrics and more data can be employed so as to allow for full generalization of the results, as long as all of these can be fully automated and forecast unsupervised in a freeware environment - in this thesis that being R.
Two Essays On Econometric Forecasting With An Econometric Model
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Author : A. C. Fenwick
language : en
Publisher:
Release Date : 1974
Two Essays On Econometric Forecasting With An Econometric Model written by A. C. Fenwick and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974 with Econometrics categories.
Understanding And Prediction
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Author : S. Nowak
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Understanding And Prediction written by S. Nowak and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Philosophy categories.
One of the more characteristic features of contemporary sociology is an increasing interest in theories. More and more theories are being developed in various areas of social investigation; we observe also an increasing number of verificational studies aimed primarily toward the verification of various theories. The essays presented in this volume deal with theories too, but they approach this problem from a methodological perspective. There fore it seems worthwhile in the preface to this volume to make a kind of general declaration about the author's aims and his approach to the subject of his interest, and about his view of the role of methodological reflection in the development of sciences. First let me say what methodology cannot do. It cannot be a substitute for the formulation of substantive theories, nor can it substitute for the empirical studies which confirm or reject such theories. Therefore its impact upon the development of any science, including the social sciences, is only indirect, by its undertaking the analysis of research tools and rules of scientific procedures. It can also propose certain standards for scientific procedures, but the application of these standards is the domain of substan tive researchers, and it is the substantive researchers who ultimately develop any science. Nevertheless the potential impact-of methodological reflection, even if only indirect, should not be underestimated.