Modeling and adapting to context changes: The case of stock market decisions making
J. Ajenstat, Amir Padovitz, Arkady Zaslavsky, Seng W. Loke · 2005
A stock market decision making makes a compelling case for the use of context aware systems that can adapt to a context behavior known as ‘random walk'. To defend such a proposition the paper adopts the formulation typically used in sensor driven applications that involves critical context characteristics of pervasiveness and instability. From the pervasive perspective the paper concentrates on the ability to characterize a context-state trajectory behavior in real-time to proactively estimate the trend of context change. From the perspective of instability it discusses context related mechanisms such as hedging with derivative instruments as a way to caliber context aware system sensitivity to contextual changes. To validate the idea the paper introduces a special case of an equity option portfolio that is simultaneously delta, gamma and Vega neutral, to deal with extreme context-state exhibiting unpredictable time-varying behavior. Based on some preliminary results of real life experimentation the paper concludes with a continuing current debate on the distinctive merits of reactive versus proactive context.