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ADAPTIVE DRIFT MODELING OF DYNAMIC COINTEGRATED TIME SERIES: APPLICATIONS IN FINANCIAL AND SPORTS GAMBLING MARKETS

William Mallios

Abstract


Cointegrated time processes are viewed graphically in terms of candlestick charts in finance and sports and modeled dynamically in terms of adaptive drift procedures. Forecasts focus on active equity trading, betting against the bookmakers’ lines in sports and assessing trading/betting risks. Modeling premises are that (1) markets fluctuate between periods of efficiency and inefficiency and that (2) during inefficient periods, present and past disequilibria (shocks) have dynamic effects on subsequent price changes/game outcomes. Sports forecasting incorporates the added effects of the lines and lagged gambling shocks. Forecasts are in terms of reduced, higher order, ARMA-type processes that drift to accommodate evolving market conditions. Risk assessment is in terms of adaptive GARCH modeling. Modeling applications are with reference to the Great Depression and NFL playoff games.


Keywords


Rational/irrational market behavior, gambling/statistical shocks, higher order ARMA systems

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References


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DOI: http://dx.doi.org/10.5750/jpm.v4i3.480

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