Forecasting in financial and sports gambling markets

adaptive drift modeling

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Last edited by MARC Bot
August 21, 2024 | History

Forecasting in financial and sports gambling markets

adaptive drift modeling

  • 1 Want to read

"This book discusses cointegrated time series associated with financial and sports gambling markets are analyzed in terms of time-varying parameter models. Modeling premises are that present and past disequilibria--shocks both within and between time series--may affect subsequent changes and rates of these changes within individual series and sufficiently large shocks may disrupt/alter model structure such that resulting forecasts may be temporarily unreliable. Reduced forecasting equations are in terms of higher order ARMA models that are not limited to bilinear processes. Sports forecasting models based on public information are usually more effective--in terms of profitable trading/wagering strategies--than those for the financial sector for two reasons: insider information is less prevalent, and modeling is simplified since lagged shocks associated with the gambling lines/spreads are known--in contrast with financial modeling where there are no comparable gambling shocks, only unknown, lagged statistical shocks in terms of MA variables. Forecasting is illustrated for NFL and NBA playoff games. In financial markets, cointegration is discussed in terms of candlestick chart variants with modeling illustrations given in terms of recent Google price changes. Chapter coverage includes candlestick charts, higher order ARMA processes in financial markets, the effects of gambling shocks in sports gambling markets, cointegrated time series with model drift, modeling volatility, and the promotion of financial and mathematical literacy"--Provided by publisher.

"This book discusses cointegrated time series associated with financial and sports gambling markets are analyzed in terms of time-varying parameter models. Modeling premises are that present and past disequilibria--shocks both within and between time series--may affect subsequent changes and rates of these changes within individual series and sufficiently large shocks may disrupt/alter model structure such that resulting forecasts may be temporarily unreliable"--Provided by publisher.

Publish Date
Publisher
Wiley
Language
English
Pages
264

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Previews available in: English

Book Details


Edition Notes

Includes bibliographical references and index.

Published in
Hoboken, N.J

Classifications

Dewey Decimal Class
332.63/2220112
Library of Congress
HG6015 .M23 2011, HG6015.M23 2011

The Physical Object

Pagination
xiii, 264 p. :
Number of pages
264

Edition Identifiers

Open Library
OL24893007M
Internet Archive
forecastingfinan00mall
ISBN 13
9780470484524
LCCN
2010036845
OCLC/WorldCat
617637860

Work Identifiers

Work ID
OL15988370W

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History

Download catalog record: RDF / JSON / OPDS | Wikipedia citation
August 21, 2024 Edited by MARC Bot import existing book
December 24, 2022 Edited by MARC Bot import existing book
November 13, 2020 Edited by MARC Bot import existing book
October 9, 2020 Edited by ImportBot import existing book
July 29, 2011 Created by LC Bot Imported from Library of Congress MARC record