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William Mallios Sports Metric Forecasting. Guides to Beating the Spreads in Major League Baseball, Basketball, and Football Games


Книга "Sports Metric Forecasting. Guides to Beating the Spreads in Major League Baseball, Basketball, and Football Games".

1952 RUR

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William Mallios S. Forecasting in Financial and Sports Gambling Markets. Adaptive Drift Modeling


A guide to modeling analyses for financial and sports gambling markets, with a focus on major current events Addressing the highly competitive and risky environments of current-day financial and sports gambling markets, Forecasting in Financial and Sports Gambling Markets details the dynamic process of constructing effective forecasting rules based on both graphical patterns and adaptive drift modeling (ADM) of cointegrated time series. The book uniquely identifies periods of inefficiency that these markets oscillate through and develops profitable forecasting models that capitalize on irrational behavior exhibited during these periods. Providing valuable insights based on the author's firsthand experience, this book utilizes simple, yet unique, candlestick charts to identify optimal time periods in financial markets and optimal games in sports gambling markets for which forecasting models are likely to provide profitable trading and wagering outcomes. Featuring detailed examples that utilize actual data, the book addresses various topics that promote financial and mathematical literacy, including: Higher order ARMA processes in financial markets The effects of gambling shocks in sports gambling markets Cointegrated time series with model drift Modeling volatility Throughout the book, interesting real-world applications are presented, and numerous graphical procedures illustrate favorable trading and betting opportunities, which are accompanied by mathematical developments in adaptive model forecasting and risk assessment. A related web site features updated reviews in sports and financial forecasting and various links on the topic. Forecasting in Financial and Sports Gambling Markets is an excellent book for courses on financial economics and time series analysis at the upper-undergraduate and graduate levels. The book is also a valuable reference for researchers and practitioners working in the areas of retail markets, quant funds, hedge funds, and time series. Also, anyone with a general interest in learning about how to profit from the financial and sports gambling markets will find this book to be a valuable resource.

9186.94 RUR

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Michael Gilliland The Business Forecasting Deal. Exposing Myths, Eliminating Bad Practices, Providing Practical Solutions


Practical-nontechnical-solutions to the problems of business forecasting Written in a nontechnical style, this book provides practical solutions to common business forecasting problems, showing you how to think about business forecasting in the context of uncertainty, randomness and process performance. Addresses the philosophical foundations of forecasting Raises awareness of fundamental issues usually overlooked in pursuit of the perfect forecast Introduces a new way to think about business forecasting, focusing on process efficiency and the elimination of worst practices Provides practical approaches for the non-statistical problems forecasters face Illustrates Forecast Value Added (FVA) Analysis for identifying waste in the forecasting process Couched in the context of uncertainty, randomness, and process performance, this book offers new, innovative ideas for resolving your business forecasting problems.

3299.34 RUR

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Pekka Tiusanen Real Estate Price Forecasting in Finland


Master's Thesis from the year 2017 in the subject Business economics - Miscellaneous, , language: English, abstract: There is an abundance of existing literature regarding time series forecasting and the housing market. This thesis evaluates the performance and statistical adequacy of several time series models in the context of real estate price forecasting in Finland. Each statistical model is applied so that forecasts are generated over the seven quarters following the training sample. The resulting forecasts are compared against realized price development. Model evaluation is carried out from the viewpoint of forecasting errors in the validation period, statistical fit, modelling constraints and success in the light of the theoretical framework. It was concluded that scarce ARIMA-based models are suitable for short-term real estate price forecasting in the concerned setting. The models were built on logarithmic I(1) nominal data and augmented with seasonal dummy variables. The Chen & Liu (1993) structural anomaly detection method enhanced statistical fit in the training period and forecasting accuracy in the validation period. The inclusion of a drift parameter generally led to inflated forecasting results in the validation period. The RMSE and MAE error statistics produced by the best ARIMA-based models remained well below 0.5 % in the validation period. The Holt & Winters and I(1) OLS models were also outperformed by the most adept ARIMA-based models. The in...

6277 RUR

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Peter Hirschbichler Order Quantity Forecasting for the Fashion Industry


Master's Thesis from the year 2010 in the subject Computer Science - Applied, grade: 1, Fachhochschule Salzburg (Information Technology und Systems Management), language: English, abstract: Precise order quantity forecasting for fashion retailers is difficult, because of the specific nature of fashion products namely long lead times, seasonality, and product attributes suchas sizes, colours, and cuts. This thesis contributes to order quantity forecasting for fashion products by the use of regression analysis. For this purpose, forecasting techniques in general, and parametric as well as nonparametric regression analysis in articular are presented. This is followed by fundamentals of data mining, specifically data preprocessing and data warehousing, in order to be able to apply regression analysis on historical sales data. Furthermore, to examine the quality of forecasts a method forevaluating the economical benefit of order quantity forecasting was developed.As a next step, the presented methods for forecasting were applied to historical sales data. Therefore, sales data was analysed, regression models were applied and forecasts werecalculated and evaluated finally. This thesis is concluded by suggesting a forecasting implementation and by discussing the contributions to order quantity forecasting.

3752 RUR

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W. D. Gann The Master Commodity Course. Original Market Trading Course


W. D. Gann's Commodities Trading Course is an extensive course. This course gives you a number of different trading techniques and skills. Which include: charting, chart interpretation, using Gann Angles, Squaring Price and Time, using Gann Squares, Square of Nine, Gann Numbers, Gann Calculators and more. This course consists of Gann's original course he sold in the early 1950's for a reported $5,000. Here is a listing of the subjects covered in this Course: Speculation; a Profitable Profession. Mechanical Method and Trend Indicator Rules for Trading in Grains The Basis of My Forecasting Methods for Grains Forecasting by Time Cycles. The Basis of My Forecasting Method for Cotton Mechanical Method and New Trend Indicator for Cotton Cash and May Soybean Futures Master Egg Course Master Charts Supplement Section

8177 RUR

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S. Yadavendra Babu,M. Subbarayudu and Balasiddamuni Pagadala Some Aspects Of Forecasting Techniques In Econometrics


In The present book Chapter - I is an introductory one. It contains the general introduction about the problem of forecasting besides objectives and organization of the research.Chapter - II describes the various basic forecasting models such as Naive, Moving averages, Simple smoothing, Double moving averages and Double smoothing, triple smoothing and adaptive smoothing forecasting models. Chapter - III deals with the Adaptive, Filtering and Combination for forecasting techniques. Chapter - IV gives the need for exponential smoothing forecasting model along with model selection criterion. Chapter - V presents the presents the various autoregressive forecasting models such as ARMA, ARIMA and STARMA models with their link with dynamic linear models .Chapter - VI proposes some new forecasting techniques in econometrics. Chapter - VII epitomizes the conclusions based on the present book..Several relevant articles regarding the forecasting techniques have been presented under a separate title ‘BIBLIOGRAPHY’.

5707 RUR

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Natalia Gotman,Galina Shumilova and Tatiana Starceva Electric load forecasting using an artificial neural networks


Electric load forecasting is an important research field in electric power industry. It plays a crucial role in solving a wide range of tasks of short-term planning and operating control of electric power system operating modes. Load forecasting is carried out in different time spans. Load forecasting within a current day - operating forecasting; one-day-week-month-ahead load forecasting - short-term load forecasting; one-month-quarter-year-ahead load forecasting - long-term load forecasting. So far a great number of both conventional and non-conventional electric load forecasting methods and models have been developed. The work presents research results of electric load forecasting for electrical power systems using artificial neural networks and fuzzy logic as one of the most advanced and perspective directions of solving this task. A theoretical approach to the issues discussed is combined with the data of experimental studies implemented with application of load curves of regional electrical power systems. The book is addressed to specialists and researchers concerned with operational control modes of electric power systems.

2612 RUR

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Kostas Nikolopoulos I. Forecasting With The Theta Method. Theory and Applications


The first book to be published on the Theta method, outlining under what conditions the method outperforms other forecasting methods This book is the first to detail the Theta method of forecasting – one of the most difficult-to-beat forecasting benchmarks, which topped the biggest forecasting competition in the world in 2000: the M3 competition. Written by two of the leading experts in the forecasting field, it illuminates the exact replication of the method and under what conditions the method outperforms other forecasting methods. Recent developments such as multivariate models are also included, as are a series of practical applications in finance, economics, and healthcare. The book also offers practical tools in MS Excel and guidance, as well as provisional access, for the use of R source code and respective packages. Forecasting with the Theta Method: Theory and Applications includes three main parts. The first part, titled Theory, Methods, Models & Applications details the new theory about the method. The second part, Applications & Performance in Forecasting Competitions, describes empirical results and simulations on the method. The last part roadmaps future research and also include contributions from another leading scholar of the method – Dr. Fotios Petropoulos. First ever book to be published on the Theta Method Explores new theory and exact conditions under which methods would outperform most forecasting benchmarks Clearly written with practical applications Employs R – open source code with all included implementations Forecasting with the Theta Method: Theory and Applications is a valuable tool for both academics and practitioners involved in forecasting and respective software development.

8553.35 RUR

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Dr. Mohamed E. El-Hawary Advances in Electric Power and Energy Systems. Load Price Forecasting


A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial arenas. Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every maximization strategy. This book fills a gap in the literature on this increasingly important topic. Following an introductory chapter offering background information necessary for a full understanding of the forecasting issues covered, this book: Introduces advanced methods of time series forecasting, as well as neural networks Provides in-depth coverage of state-of-the-art power system load forecasting and electricity price forecasting Addresses river flow forecasting based on autonomous neural network models Deals with price forecasting in a competitive market Includes estimation of post-storm restoration times for electric power distribution systems Features contributions from world-renowned experts sharing their insights and expertise in a series of self-contained chapters Advances in Electric Power and Energy Systems is a valuable resource for practicing engineers, regulators, planners, and consultants working in or concerned with the electric power industry. It is also a must read for senior undergraduates, graduate students, and researchers involved in power system planning and operation.

9603.03 RUR

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Stephan Kolassa, Enno Siemsen Demand Forecasting for Managers


Most decisions and plans in a firm require a forecast. Not matching supply with demand can make or break any business, and that's why forecasting is so invaluable. Forecasting can appear as a frightening topic with many arcane equations to master. For this reason, the authors start out from the very basics and provide a non-technical overview of common forecasting techniques as well as organizational aspects of creating a robust forecasting process. The book also discusses how to measure forecast accuracy to hold people accountable and guide continuous improvement. This book does not require prior knowledge of higher mathematics, statistics, or operations research. It is designed to serve as a first introduction to the non-expert, such as a manager overseeing a forecasting group, or an MBA student who needs to be familiar with the broad outlines of forecasting without specializing in it.

4502 RUR

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Alexander Harin Hypothesis (principle) of uncertain future. Utility theory. Economics. Forecasting


Premises, formulation, consequences and applications of a hypothesis (principle) of uncertain future are reviewed. The hypothesis can be used in economics, especially in utility theory, and in forecasting.

369 RUR

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Gately Forecasting Profits


Книга "Forecasting Profits".

4339 RUR

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Kaoru Tone Advances in DEA Theory and Applications. With Extensions to Forecasting Models


A key resource and framework for assessing the performance of competing entities, including forecasting models Advances in DEA Theory and Applications provides a much-needed framework for assessing the performance of competing entities with special emphasis on forecasting models. It helps readers to determine the most appropriate methodology in order to make the most accurate decisions for implementation. Written by a noted expert in the field, this text provides a review of the latest advances in DEA theory and applications to the field of forecasting. Designed for use by anyone involved in research in the field of forecasting or in another application area where forecasting drives decision making, this text can be applied to a wide range of contexts, including education, health care, banking, armed forces, auditing, market research, retail outlets, organizational effectiveness, transportation, public housing, and manufacturing. This vital resource: Explores the latest developments in DEA frameworks for the performance evaluation of entities such as public or private organizational branches or departments, economic sectors, technologies, and stocks Presents a novel area of application for DEA; namely, the performance evaluation of forecasting models Promotes the use of DEA to assess the performance of forecasting models in a wide area of applications Provides rich, detailed examples and case studies Advances in DEA Theory and Applications includes information on a balanced benchmarking tool that is designed to help organizations examine their assumptions about their productivity and performance.

8450.67 RUR

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S. Sam Titus,C. Santharam and Syluvai Anthony Bayesian Approach For Forecasting Model


Whenever question arises about uncertainty, it can be tackled by Bayesian tools and methods, with the help of priori probabilities and posterior probabilities. In general classical statistics selects just the “best” model and rejects all the others, even of they are only marginally worse than the best model, perhaps the model is a good fit, but in case of forecasting the future; there it fails. Now, the problem is uncertainty about model, in this book detailed discussion about Bayesian analysis and methods, that in contrast, will combine models of highly comparable for forecasting.

4358 RUR

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Craig Shallahamer Forecasting Oracle Performance


Книга "Forecasting Oracle Performance".

6589 RUR

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Social Forecasting for Company Planning


Книга "Social Forecasting for Company Planning".

7689 RUR

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CLEMENTS HEND, Hendry COMP TO ECON FORECASTING


Книга "COMP TO ECON FORECASTING".

9589 RUR

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Evans Practical Business Forecasting


Книга "Practical Business Forecasting".

9102 RUR

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Craig Shallahamer Forecasting Oracle Performance


Книга "Forecasting Oracle Performance".

6589 RUR

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William S. Plumer Writings of Plumer, Three Books on Faith


Writings of William S. Plumer, Three Books on Faith includes three of Plumer's works:Assurance of Grace and Salvation, Balm for Wounded Spirits, False Doctrines and False Teachers. William Plumer was an American lawyer, Baptist lay preacher and represented New Hampshire as a Federalist in the United States Senate. He later served as a Governor of New Hampshire.

802 RUR

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Afsar Naqvi Ik Tera Sahara (Your One Support). Prayers and Forecasting Poems


Книга "Ik Tera Sahara (Your One Support). Prayers and Forecasting Poems".

1802 RUR

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Murat Kulahci Introduction to Time Series Analysis and Forecasting


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.

10372.01 RUR

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