Modeling Market Shake Ups Using Time Series Data
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Modeling Market Shake Ups Using Time Series Data
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Author : Marcel Kornelis
language : en
Publisher:
Release Date : 2002
Modeling Market Shake Ups Using Time Series Data written by Marcel Kornelis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Advertising categories.
Time Series Models For Business And Economic Forecasting
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Author : Philip Hans Franses
language : en
Publisher: Cambridge University Press
Release Date : 1998-10-15
Time Series Models For Business And Economic Forecasting written by Philip Hans Franses and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-10-15 with Business & Economics categories.
An introduction to time series models for business and economic forecasting.
Prediction Of International Stock Market Movements Using A Statistical Time Series Analysis Method
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Author : Jehan Shareef
language : en
Publisher:
Release Date : 2015-07-24
Prediction Of International Stock Market Movements Using A Statistical Time Series Analysis Method written by Jehan Shareef and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-24 with categories.
Modeling Market Shake Ups Using Time Series Data
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Author : Marcel Kornelis
language : en
Publisher:
Release Date : 2002
Modeling Market Shake Ups Using Time Series Data written by Marcel Kornelis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
Forecasting And Timing Markets A Quantitative Approach
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Author : Henry Liu
language : en
Publisher:
Release Date : 2021-04-15
Forecasting And Timing Markets A Quantitative Approach written by Henry Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-15 with categories.
Financial markets are essentially time-series data driven events consisting of valleys, peaks, and in-betweens of ups and downs. For more than a century, many pioneers had attempted to come up with various theoretical models to facilitate forecasting and timing market moves. For example, as early as in 1902, or 119 years ago, S. A. Nelson, a friend of Charles H. Dow, attempted to explain Dow's methods in his book titled The A B C of Stock Speculation, which became later known as "the Dow Theory." 20 years later in 1922, William Peter Hamilton carried on and wrote the book The Stock Market Barometer, which explained the Dow Theory in more detail. More recently in the last few decades, the advent of advanced computing technologies helped create numerous technical indicators, such as Relative Strength Index (RSI) by J. Welles Wilder (1978), Moving Average Convergence Divergence (MACD) by Gerald Appel (2005), Stochastic Oscillator (SO) by George Lane (2007), and Bollinger Bands (BB) by John Bollinger (2002), etc. Those powerful theories and indicators have been heavily studied and well-known in the financial circle. However, they are empirical and lack quantitative verifications out of solid backtest results. This book helps fill these vacancies. This text attempts to help explore how one can forecast and time markets more quantitatively. For this purpose, the author developed a model-based system, named AlphaCovaria, to help demonstrate how to use various simplest, readily available technical indicators to forecast and time markets approximately while eliminating subjective speculations at the same time. Centered on various math models, the author's AlphaCovaria system has three main components: an AlphaCurve program for charting, a BTDriver program for running all backtests, and an AlphaCovaria driver for generating buy/sell signals based on symbol profiles learned through backtests. This kind of formula-driven approach is more promising for building more high-performance strategies. The text is made concise and precise of about 100 pages only, as a working method does not need to be wordy. Math models, data and charts can help explain more effectively and convincingly. Also, inspired by those classical models, the author came up with a new indicator named simple cascading indicator (sci), which beat all those classical models in most cases, based on the backtest results with 29 carefully selected symbols and past 15 years' price data. This 2nd edition of the book also shared my live trading experience using real money in my Fidelity and eTrade accounts with my AlphaCovaria system. Such data can be found nowhere else.
Market Response Models Econometric And Time Series Analysis
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Author : Dominique M. Hanssens
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Market Response Models Econometric And Time Series Analysis written by Dominique M. Hanssens 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 Business & Economics categories.
This book reports over a decade's worth of research on the development of empirical response models that have important uses for generating marketing knowledge and improving marketing decisions. Some of its contributions to marketing are the following: 1. It integrates state-of-the art technical material with discussions of its relevance to management. 2. It provides continuity to a research stream over 20 years old. 3. It illustrates how marketing generalizations are the basis of marketing theory and marketing knowledge. 4. It shows how the research can be applied to marketing planning and forecasting. 5. It presents original research in marketing. The book addresses both marketing researchers and marketing managers. This can be done because empirical decision models are helpful in practice and are also based on theories of response. Econometric and time series analysis (ETS) is one of the few areas in marketing where there is little, if any, conflict between the academic sphere and the world of professional practice. Market Response Models is a sequel to Marketing Models and Econometric Research, published in 1976. It is rare for a research-oriented book in market ing to be updated or to have a sequel. Unlike many other methodologies, ETS research in marketing has stood the test of time. It remains the main method for discovering relations among marketing variables.
Assessing Marketing Strategy Performance
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Author : Christine Moorman
language : en
Publisher:
Release Date : 2004
Assessing Marketing Strategy Performance written by Christine Moorman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business & Economics categories.
"Offering a diverse set of approaches, from stock market response modeling to historical analysis, Assessing Marketing Strategy Performance aims to foster new and more effective thinking about the value of marketing and the productivity of marketing investments. It will be a valuable resource to those seeking to better understand marketing's role in the firm"--
Modeling Risk
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Author : Johnathan Mun
language : en
Publisher: John Wiley & Sons
Release Date : 2010-06-15
Modeling Risk written by Johnathan Mun and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-15 with Business & Economics categories.
An updated guide to risk analysis and modeling Although risk was once seen as something that was both unpredictable and uncontrollable, the evolution of risk analysis tools and theories has changed the way we look at this important business element. In the Second Edition of Analyzing and Modeling Risk, expert Dr. Johnathan Mun provides up-to-date coverage of risk analysis as it is applied within the realms of business risk analysis and offers an intuitive feel of what risk looks like, as well as the different ways of quantifying it. This Second Edition provides professionals in all industries a more comprehensive guide on such key concepts as risk and return, the fundamentals of model building, Monte Carlo simulation, forecasting, time-series and regression analysis, optimization, real options, and more. Includes new examples, questions, and exercises as well as updates using Excel 2007 Book supported by author's proprietary risk analysis software found on the companion CD-ROM Offers both a qualitative and quantitative description of risk Filled with in-depth insights and practical advice, this reliable resource covers all of the essential tools and techniques that risk managers need to successfully conduct risk analysis. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Tools And Techniques For Social Science Simulation
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Author : Ramzi Suleiman
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Tools And Techniques For Social Science Simulation written by Ramzi Suleiman 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 Social Science categories.
The use of computer simulations to study social phenomena has grown rapidly during the last few years. Many social scientists from the fields of economics, sociology, psychology and other disciplines now use computer simulations to study a wide range of social phenomena. The availability of powerful personal computers, the development of multidisciplinary approaches and the use of artificial intelligence models have all contributed to this development. The benefits of using computer simulations in the social sciences are obvious. This holds true for the use of simulations as tools for theory building and for its implementation as a tool for sensitivity analysis and parameter optimization in application-oriented models. In both, simulation provides powerful tools for the study of complex social systems, especially for dynamic and multi-agent social systems in which mathematical tractability is often impossible. The graphical display of simulation output renders it user friendly to many social scientists that lack sufficient familiarity with the language of mathematics. The present volume aims to contribute in four directions: (1) To examine theoretical and methodological issues related to the application of simulations in the social sciences. By this we wish to promote the objective of designing a unified, user-friendly, simulation toolkit which could be applied to diverse social problems. While no claim is made that this objective has been met, the theoretical issues treated in Part 1 of this volume are a contribution towards this objective.
Advanced Methods For Modeling Markets
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Author : Peter S. H. Leeflang
language : en
Publisher: Springer
Release Date : 2017-08-29
Advanced Methods For Modeling Markets written by Peter S. H. Leeflang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-29 with Business & Economics categories.
This volume presents advanced techniques to modeling markets, with a wide spectrum of topics, including advanced individual demand models, time series analysis, state space models, spatial models, structural models, mediation, models that specify competition and diffusion models. It is intended as a follow-on and companion to Modeling Markets (2015), in which the authors presented the basics of modeling markets along the classical steps of the model building process: specification, data collection, estimation, validation and implementation. This volume builds on the concepts presented in Modeling Markets with an emphasis on advanced methods that are used to specify, estimate and validate marketing models, including structural equation models, partial least squares, mixture models, and hidden Markov models, as well as generalized methods of moments, Bayesian analysis, non/semi-parametric estimation and endogeneity issues. Specific attention is given to big data. The market environment is changing rapidly and constantly. Models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performance. In today’s environment of information overload, the challenge is to make sense of the data that is being provided globally, in real time, from thousands of sources. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based. This volume provides an authoritative and comprehensive review, with each chapter including: · an introduction to the method/methodology · a numerical example/application in marketing · references to other marketing applications · suggestions about software. Featuring contributions from top authors in the field, this volume will explore current and future aspects of modeling markets, providing relevant and timely research and techniques to scientists, researchers, students, academics and practitioners in marketing, management and economics.