Portfolio selection is characterized by the imprecision and/or vagueness inherent to the context where investors have to make decisions. In this work an interactive model is proposed to select a suitable portfolio taking into account the uncertainty related to the market scenarios and the imprecision associated with the model data.

The aim of this paper is to address the optimal timing for accessing to bond market financing and its impact on capital structure choices. The switch from strictly private debt to a mix of public and private debt, due to an increase in firm's debt capacity, modifies the rules for resolving financial distress that rely on different Nash bargaining games. In particular, firms with public debt can hardly renegotiate their claims privately and must undergo a public restructuring procedure (Chapter 11 type). As a consequence, the decision to issue bond affects the cost of debt financing, the probability of default and the Nash bargaining equilibrium. In a rational expectations framework, shareholders internalize the effects of this decision when selecting the ex ante optimal debt level.

A stock market decision making situation makes a very propelling case for the use of context aware systems to optimally 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 involve critical context characteristics of pervasiveness and instability. From the pervasive perspective the paper concentrates on the ability to characterize a context-state trajectory 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 in relation 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 (or any combination) 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 infered actions as an issue compromising instability in context aware pervasive computing. More specifically in portfolio optimal decision making it suggests a limited proactive activity while still maintaining a satisfactory degree of influence (reactivity) over a contextual situation.