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.

Download or read book Introduction to Financial Forecasting in Investment Analysis written by John B. Guerard, Jr. and published by Springer Science & Business Media. This book was released on 2013-01-04 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction.

Download or read book Synoptic Analysis and Forecasting written by Shawn Milrad and published by Elsevier. This book was released on 2017-11-16 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Synoptic Analysis and Forecasting: An Introductory Toolkit provides the bridge between the introductory fundamentals of a meteorology course and advanced synoptic-dynamic analysis for undergraduate students. It helps students to understand the principles of weather analysis, which will complement computer forecast models. This valuable reference also imparts qualitative weather analysis and forecasting tools and techniques to non-meteorologist end users, such as emergency/disaster managers, aviation experts, and environmental health and safety experts who need to have a foundational knowledge of weather forecasting. - Presents the fundamentals of weather analysis and forecasting - Offers clear accessible writing aimed at students from a variety of mathematical backgrounds - Discusses the reading and interpretation of surface observations and METAR code, processes associated with the motion and intensity of cyclones and anticyclones, and quantitative and/or qualitative diagnosis of processes associated with ascent and descent

Download or read book Applied Time Series Analysis written by Terence C. Mills and published by Academic Press. This book was released on 2019-01-24 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written for those who need an introduction, Applied Time Series Analysis reviews applications of the popular econometric analysis technique across disciplines. Carefully balancing accessibility with rigor, it spans economics, finance, economic history, climatology, meteorology, and public health. Terence Mills provides a practical, step-by-step approach that emphasizes core theories and results without becoming bogged down by excessive technical details. Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.

Download or read book Cash Flow Analysis and Forecasting written by Timothy Jury and published by John Wiley & Sons. This book was released on 2012-04-30 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the definitive guide to cash flow statement analysis and forecasting. It takes the reader from an introduction about how cash flows move within a business, through to a detailed review of the contents of a cash flow statement. This is followed by detailed guidance on how to restate cash flows into a template format. The book shows how to use the template to analyse the data from start up, growth, mature and declining companies, and those using US GAAP and IAS reporting. The book includes real world examples from such companies as Black and Decker (US), Fiat (Italy) and Tesco (UK). A section on cash flow forecasting includes full coverage of spreadsheet risk and good practice. Complete with chapters of particular interest to those involved in credit markets as lenders or counter-parties, those running businesses and those in equity investing, this book is the definitive guide to understanding and interpreting cash flow data.

Download or read book Financial Forecasting Analysis and Modelling written by Michael Samonas and published by John Wiley & Sons. This book was released on 2015-01-20 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Risk analysis has become critical to modern financial planning Financial Forecasting, Analysis and Modelling provides a complete framework of long-term financial forecasts in a practical and accessible way, helping finance professionals include uncertainty in their planning and budgeting process. With thorough coverage of financial statement simulation models and clear, concise implementation instruction, this book guides readers step-by-step through the entire projection plan development process. Readers learn the tools, techniques, and special considerations that increase accuracy and smooth the workflow, and develop a more robust analysis process that improves financial strategy. The companion website provides a complete operational model that can be customised to develop financial projections or a range of other key financial measures, giving readers an immediately-applicable tool to facilitate effective decision-making. In the aftermath of the recent financial crisis, the need for experienced financial modelling professionals has steadily increased as organisations rush to adjust to economic volatility and uncertainty. This book provides the deeper level of understanding needed to develop stronger financial planning, with techniques tailored to real-life situations. Develop long-term projection plans using Excel Use appropriate models to develop a more proactive strategy Apply risk and uncertainty projections more accurately Master the Excel Scenario Manager, Sensitivity Analysis, Monte Carlo Simulation, and more Risk plays a larger role in financial planning than ever before, and possible outcomes must be measured before decisions are made. Uncertainty has become a critical component in financial planning, and accuracy demands it be used appropriately. With special focus on uncertainty in modelling and planning, Financial Forecasting, Analysis and Modelling is a comprehensive guide to the mechanics of modern finance.

Download or read book Introduction to Time Series Analysis and Forecasting written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-04-21 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both popular and modern time series methodologies as well as an introduction to Bayesian methods in forecasting. Introduction to Time Series Analysis and Forecasting, Second Edition also includes: Over 300 exercises from diverse disciplines including health care, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®, and R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data New material on frequency domain and spatial temporal data analysis Expanded coverage of the variogram and spectrum with applications as well as transfer and intervention model functions A supplementary website featuring PowerPoint® slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, Second Edition is an ideal textbook upper-undergraduate and graduate-levels courses in forecasting and time series. The book is also an excellent reference for practitioners and researchers who need to model and analyze time series data to generate forecasts.

Download or read book Understanding Economic Forecasts written by David F. Hendry and published by MIT Press. This book was released on 2003 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to interpret and evaluate economic forecasts and the uncertainties inherent in them.

Download or read book Weather Analysis and Forecasting written by Christo Georgiev and published by Elsevier. This book was released on 2005-07-05 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Weather Analysis and Forecasting is a practical guide to using potential vorticity fields and water vapor imagery from satellites to elucidate complex weather patterns and train meteorologists to improve operational forecasting. In particular, it details the use of the close relationship between satellite imagery and the potential vorticity fields in the upper troposphere and lower stratosphere. It shows how to interpret water vapor patterns in terms of dynamical processes in the atmosphere and their relation to diagnostics available from weather prediction models. The book explores topics including: a dynamical view of synoptic development; the interpretation problem of satellite water vapor imagery; practical use of water vapor imagery and dynamical fields; significant water vapor imagery features associated with synoptic dynamical structures; and use of water vapor imagery for assessing NWP model behavior and improving forecasts. Applications are illustrated with color images based on real meteorological situations. The book's step-by-step pedagogy makes this an essential training manual for forecasters in meteorological services worldwide, and a valuable text for graduate students in atmospheric physics and satellite meteorology. * Shows how to analyze current satellite images for assessing weather models' behavior and improving forecasts * Provides step-by-step pedagogy for understanding and interpreting meteorological processes * Includes full-color throughout to highlight "real-world" models, patterns, and examples

Download or read book Practical Time Series Analysis written by Aileen Nielsen and published by O'Reilly Media. This book was released on 2019-09-20 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance

Download or read book Principles of Forecasting written by J.S. Armstrong and published by Springer Science & Business Media. This book was released on 2001 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook summarises knowledge from experts and empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. Includes a comprehensive forecasting dictionary.

Download or read book Statistical Postprocessing of Ensemble Forecasts written by Stéphane Vannitsem and published by Elsevier. This book was released on 2018-05-17 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Postprocessing of Ensemble Forecasts brings together chapters contributed by international subject-matter experts describing the current state of the art in the statistical postprocessing of ensemble forecasts. The book illustrates the use of these methods in several important applications including weather, hydrological and climate forecasts, and renewable energy forecasting. After an introductory section on ensemble forecasts and prediction systems, the second section of the book is devoted to exposition of the methods available for statistical postprocessing of ensemble forecasts: univariate and multivariate ensemble postprocessing are first reviewed by Wilks (Chapters 3), then Schefzik and Möller (Chapter 4), and the more specialized perspective necessary for postprocessing forecasts for extremes is presented by Friederichs, Wahl, and Buschow (Chapter 5). The second section concludes with a discussion of forecast verification methods devised specifically for evaluation of ensemble forecasts (Chapter 6 by Thorarinsdottir and Schuhen). The third section of this book is devoted to applications of ensemble postprocessing. Practical aspects of ensemble postprocessing are first detailed in Chapter 7 (Hamill), including an extended and illustrative case study. Chapters 8 (Hemri), 9 (Pinson and Messner), and 10 (Van Schaeybroeck and Vannitsem) discuss ensemble postprocessing specifically for hydrological applications, postprocessing in support of renewable energy applications, and postprocessing of long-range forecasts from months to decades. Finally, Chapter 11 (Messner) provides a guide to the ensemble-postprocessing software available in the R programming language, which should greatly help readers implement many of the ideas presented in this book. Edited by three experts with strong and complementary expertise in statistical postprocessing of ensemble forecasts, this book assesses the new and rapidly developing field of ensemble forecast postprocessing as an extension of the use of statistical corrections to traditional deterministic forecasts. Statistical Postprocessing of Ensemble Forecasts is an essential resource for researchers, operational practitioners, and students in weather, seasonal, and climate forecasting, as well as users of such forecasts in fields involving renewable energy, conventional energy, hydrology, environmental engineering, and agriculture. - Consolidates, for the first time, the methodologies and applications of ensemble forecasts in one succinct place - Provides real-world examples of methods used to formulate forecasts - Presents the tools needed to make the best use of multiple model forecasts in a timely and efficient manner

Download or read book SAS for Forecasting Time Series Third Edition written by John C. Brocklebank, Ph.D. and published by SAS Institute. This book was released on 2018-03-14 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: To use statistical methods and SAS applications to forecast the future values of data taken over time, you need only follow this thoroughly updated classic on the subject. With this third edition of SAS for Forecasting Time Series, intermediate-to-advanced SAS users—such as statisticians, economists, and data scientists—can now match the most sophisticated forecasting methods to the most current SAS applications. Starting with fundamentals, this new edition presents methods for modeling both univariate and multivariate data taken over time. From the well-known ARIMA models to unobserved components, methods that span the range from simple to complex are discussed and illustrated. Many of the newer methods are variations on the basic ARIMA structures. Completely updated, this new edition includes fresh, interesting business situations and data sets, and new sections on these up-to-date statistical methods: ARIMA models Vector autoregressive models Exponential smoothing models Unobserved component and state-space models Seasonal adjustment Spectral analysis Focusing on application, this guide teaches a wide range of forecasting techniques by example. The examples provide the statistical underpinnings necessary to put the methods into practice. The following up-to-date SAS applications are covered in this edition: The ARIMA procedure The AUTOREG procedure The VARMAX procedure The ESM procedure The UCM and SSM procedures The X13 procedure The SPECTRA procedure SAS Forecast Studio Each SAS application is presented with explanation of its strengths, weaknesses, and best uses. Even users of automated forecasting systems will benefit from this knowledge of what is done and why. Moreover, the accompanying examples can serve as templates that you easily adjust to fit your specific forecasting needs. This book is part of the SAS Press program.

Download or read book Financial Risk Forecasting written by Jon Danielsson and published by John Wiley & Sons. This book was released on 2011-04-20 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Risk Forecasting is a complete introduction to practical quantitative risk management, with a focus on market risk. Derived from the authors teaching notes and years spent training practitioners in risk management techniques, it brings together the three key disciplines of finance, statistics and modeling (programming), to provide a thorough grounding in risk management techniques. Written by renowned risk expert Jon Danielsson, the book begins with an introduction to financial markets and market prices, volatility clusters, fat tails and nonlinear dependence. It then goes on to present volatility forecasting with both univatiate and multivatiate methods, discussing the various methods used by industry, with a special focus on the GARCH family of models. The evaluation of the quality of forecasts is discussed in detail. Next, the main concepts in risk and models to forecast risk are discussed, especially volatility, value-at-risk and expected shortfall. The focus is both on risk in basic assets such as stocks and foreign exchange, but also calculations of risk in bonds and options, with analytical methods such as delta-normal VaR and duration-normal VaR and Monte Carlo simulation. The book then moves on to the evaluation of risk models with methods like backtesting, followed by a discussion on stress testing. The book concludes by focussing on the forecasting of risk in very large and uncommon events with extreme value theory and considering the underlying assumptions behind almost every risk model in practical use – that risk is exogenous – and what happens when those assumptions are violated. Every method presented brings together theoretical discussion and derivation of key equations and a discussion of issues in practical implementation. Each method is implemented in both MATLAB and R, two of the most commonly used mathematical programming languages for risk forecasting with which the reader can implement the models illustrated in the book. The book includes four appendices. The first introduces basic concepts in statistics and financial time series referred to throughout the book. The second and third introduce R and MATLAB, providing a discussion of the basic implementation of the software packages. And the final looks at the concept of maximum likelihood, especially issues in implementation and testing. The book is accompanied by a website - www.financialriskforecasting.com – which features downloadable code as used in the book.

Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Download or read book Time Series Analysis Forecasting Control 3 E written by and published by Pearson Education India. This book was released on 1994-09 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a complete revision of a classic, seminal, and authoritative text that has been the model for most books on the topic written since 1970. It explores the building of stochastic (statistical) models for time series and their use in important areas of application -forecasting, model specification, estimation, and checking, transfer function modeling of dynamic relationships, modeling the effects of intervention events, and process control.

Download or read book Fashion Trends written by Eundeok Kim and published by Bloomsbury Publishing. This book was released on 2021-01-14 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a fast-moving global industry, how can anyone know what the next trend will be? Fashion Trends: Analysis and Forecasting offers a clear pathway into the theory and practice of forecasting fashion, using professional case studies to demonstrate each technique and concept. This revised edition includes an updated model of the fashion trend analysis and forecasting process and expanded coverage of social media, digital influencers, sustainability and social responsibility. There are also first-hand visual materials relating to forecasts from leading firms. With the rise of individualism and concern for the sustainable world, the authors also walk you through the 'end of fashion' and what comes next, including: recycled and upcycled fashion, garment rental, subscription services, the circular economy, transparency and traceability, and the role of forecasting in encouraging sustainable lifestyles. Key topics – The characteristics of an innovation – The influence of consumer groups – Long- and short-term fashion forecasting – Sociocultural factors and their influence on trends – Fashion professionals' roles in creating and supporting trends – Consumer and industry trends accelerating product innovation and diffusion – Changing trend forecasting formats – The influence of trend forecasting on business decisions