Short-Term Forecasting for Empirical Economists

Short-Term Forecasting for Empirical Economists

Author: Maximo Camacho

Publisher:

Published: 2013-11-01

Total Pages: 74

ISBN-13: 9781601987426

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Short-term Forecasting for Empirical Economists seeks to close the gap between research and applied short-term forecasting. The authors review some of the key theoretical results and empirical findings in the recent literature on short-term forecasting, and translate these findings into economically meaningful techniques to facilitate their widespread application to compute short-term forecasts in economics, and to monitor the ongoing business cycle developments in real time.


Empirical Methods in Short-Term Climate Prediction

Empirical Methods in Short-Term Climate Prediction

Author: Huug M. Van den Dool

Publisher: Oxford University Press

Published: 2007

Total Pages: 252

ISBN-13: 0199202788

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The author describes the methods underlying short-term climate prediction at time scales of two weeks to a year. With an emphasis on the empirical approach, this text covers empirical wave propagation, teleconnections, empirical orthogonal functions, and constructed analogue.


Principles of Forecasting

Principles of Forecasting

Author: J.S. Armstrong

Publisher: Springer Science & Business Media

Published: 2001-05-31

Total Pages: 840

ISBN-13: 0306476304

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Principles of Forecasting: A Handbook for Researchers and Practitioners summarizes knowledge from experts and from empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. It applies to problems such as those in finance (How much is this company worth?), marketing (Will a new product be successful?), personnel (How can we identify the best job candidates?), and production (What level of inventories should be kept?). The book is edited by Professor J. Scott Armstrong of the Wharton School, University of Pennsylvania. Contributions were written by 40 leading experts in forecasting, and the 30 chapters cover all types of forecasting methods. There are judgmental methods such as Delphi, role-playing, and intentions studies. Quantitative methods include econometric methods, expert systems, and extrapolation. Some methods, such as conjoint analysis, analogies, and rule-based forecasting, integrate quantitative and judgmental procedures. In each area, the authors identify what is known in the form of `if-then principles', and they summarize evidence on these principles. The project, developed over a four-year period, represents the first book to summarize all that is known about forecasting and to present it so that it can be used by researchers and practitioners. To ensure that the principles are correct, the authors reviewed one another's papers. In addition, external reviews were provided by more than 120 experts, some of whom reviewed many of the papers. The book includes the first comprehensive forecasting dictionary.


Economic Forecasting for Management

Economic Forecasting for Management

Author: Hans G. Graf

Publisher: Bloomsbury Publishing USA

Published: 2002-08-30

Total Pages: 264

ISBN-13: 0313017417

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Before future-oriented information can be used as a basis for decision making in economics or business administration, it must be understood on a methodological level. This book provides decision makers with a thorough understanding of the possibilities offered by various forecasting methods as well as their limitations. If managers rely on a forecast with a long-term perspective to guide them in making short-term decisions, planning deficiencies will likely result. Likewise, if managers use short-term forecasts to inform their long-term strategic vision, failure could easily ensue. Graf provides the tools necessary to sidestep the common pitfall of using the wrong forecasting technique for the wrong purpose. This is not a detailed examination of the mathematical and statistical tools of empirical economic research. Instead, forecasting methods are explained so that they can be understood by the managers who employ them in their decision making. Graf demonstrates that understanding and—in special cases—cooperation between forecast developers and users is crucial to creating an effective forecast that results in informed management decisions. He discusses traditional, long-term, macroeconomic, and global economic forecasting; the scenario technique as a central instrument of long-term forecasting; and short-term economic and market forecasting.


Precision in Predicting the Stock Prices - An Empirical Approach to Accuracy in Forecasting

Precision in Predicting the Stock Prices - An Empirical Approach to Accuracy in Forecasting

Author: Dr. Suresh Kumar S

Publisher:

Published: 2017

Total Pages: 20

ISBN-13:

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Forecasting the future prices of stock by analyzing the past and current price movements in determining the trend are always areas of interest of Chartists who believe in studying the action of the market itself rather than the past and current performances of the company. Stock price prediction has ignited the interest of researchers who strive to develop better predictive models with a fair degree of accuracy. The autoregressive integrated moving average (ARIMA)model introduced by Box and Jenkins in 1970has been in the limelight in econometrics literature for time series prediction, which has been at the core of explaining many economic and finance phenomena. ARIMA models in the research domain of finance and economics, especially stock markets, have shown an efficient capability to generate short-term forecasts and have hence beenable to outperform complex structural models in short-term prediction.This paper presents a stock price predictive model using the ARIMA model to analyze the sensitivity of such models to different time horizons used in the estimation of trends and verifies the validity of such forecasts in terms of their degree of precision. Published historical stock data, on an actively traded public sector bank's share and historical movements in the banking sector index in which the selected bank is a constituent, obtained from National Stock Exchange(NSE), India andwebsites of Yahoo finance are used to build and develop stock price forecasts and index movement predictive models. The experiments with dynamic as well as static forecasting methods used revealed that the ARIMA model has a strong potential for short-term prediction and can offer better precision than from long term trend estimates. As a stock price prediction or index movement forecast tool, it can be relied extensively in deciding entry and exit to and from the volatile markets,notwithstanding the fact the risk the investor faces on account of noise or shocks still can be erroneous making the entire prediction irrespective of its degree of precision irrelevant.


Intermittent Demand Forecasting

Intermittent Demand Forecasting

Author: John E. Boylan

Publisher: John Wiley & Sons

Published: 2021-06-02

Total Pages: 403

ISBN-13: 1119135303

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INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits. No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software. “Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —Spyros Makridakis, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC). “We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.” —Suresh Acharya, VP, Research and Development, Blue Yonder. “As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.” —Thomas R. Willemain, Professor Emeritus, Rensselaer Polytechnic Institute.