The main objective of this research is to use prediction markets as negotiation agents, for supporting R&D portfolio management. To support this research, we iteratively designed, developed, operated and evaluated several prototypes. We start by presenting the weaknesses of the current techniques for managing R&D portfolio. Then, we intend to demonstrate that prediction markets correct these we...

Many methodologies have been introduced to deal with project portfolio selection problem including some techniques that help to evaluate individual projects, or to select a portfolio among available projects. This paper, however, provides several XML-based schemes for building efficient and flexible project portfolio selection systems based on an integrated portfolio selection model proposed. I...

This paper postulates that management performance evaluation is a source of divergence between institutional investors and households’ optimal portfolio decisions. In a partial equilibrium setting, the objective of a representative household is modeled as the maximization of expected utility (an increasing and concave function, in order to accommodate risk aversion) of final wealth. Yet, the in...

In the science of operation research and decision theory, selection is the most important process. Selection is a process that studies multiple qualitative and quantitative criteria, related to the science of management, which are mostly incompatible with each other. The multi criteria selection of a renewable energy portfolio is one of the main issues considered in multi criteria literatur...

Ever since the inception of Markowitz’s modern portfolio theory, static portfolio optimization techniques were gradually phased out by dynamic portfolio management due to the growth of popularity in automated trading. In view of the intensive computational needs, it is common to use machine learning approaches on Sharpe ratio maximization for implementing dynamic portfolio optimization. In the ...