The Analysis of Sports Forecasting: Modeling Parallels between Sports Gambling and Financial Markets

Author:   William S. Mallios
Publisher:   Springer
ISBN:  

9780792377139


Pages:   294
Publication Date:   31 December 1999
Format:   Hardback
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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The Analysis of Sports Forecasting: Modeling Parallels between Sports Gambling and Financial Markets


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Full Product Details

Author:   William S. Mallios
Publisher:   Springer
Imprint:   Springer
Dimensions:   Width: 15.50cm , Height: 1.90cm , Length: 23.50cm
Weight:   0.641kg
ISBN:  

9780792377139


ISBN 10:   0792377133
Pages:   294
Publication Date:   31 December 1999
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Introduction: A Variety of Betting Lines.- I Models, Moralities, and Misconceptions.- II Modeling Concepts.- III Football.- IV Basketball.- V Baseball.- VI Selection of Athletes.- VII Financial Markets.- A.1 Time Series Analysis: Overview of Arma, Bilinear, and Higher Order Models.- A.1.1 Preliminary Comments.- A.1.2 Overview of Autoregressive Moving Average (ARMA) Models.- A.1.3 Overview of Bilinear Models.- A.1.4 Approaches to Modeling Heteroskedasticity Through Time Varying Coefficients.- A.1.5 Autoregressive Conditional Heteroskedasticity.- A.1.6 Generalized Autoregressive Conditional Heteroskedasticity.- A.1.7 ARMA Models with GARCH Errors.- A.1.8 Model Misspecification.- A.1.9 Least Squares Estimation for Non-Varying Coefficients.- A.1.10 Empirical Bayes Estimation for Time Varying Coefficients.- A.2 Multiple Time Series Equations.- A.2.1 Models Based on Wold’s Decomposition Theorem.- A.2.2 Multiple, Higher-Order Systems of Time Series Equations.- A.2.3 Extensions to Rational Expectations.- A.2.4 Classification of Events According to Observed Outcomes and States of Nature in Currency Markets.- A.3 Quantification of Structural Effects in Regression Systems.- A.3.1 Preliminary Comments.- A.3.2 Structural and Reduced Systems: Exploratory Models and Assumptions.- A.3.3 Increasing Efficiency Through Restricted Systems: Adjustments for Intra Sample Biases.- A.3.4 Estimation in Structural Systems.- A.3.5 Examples of Model Ambiguity in Structural Systems.- A.3.6 Structural Experimental Design Reconsidered.

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