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"Mallios, William S. (William Steve), 1935-"
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Forecasting in financial and sports gambling markets : adaptive drift modeling
\"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.
Book
Forecasting in financial and sports gambling markets
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.
eBook