MEAN-VARIANCE CAPITAL BUDGETING MODEL FOR R & D PROJECT SELECTION

A Comprehensive Model for R and D Project Portfolio Selection with Zero-One Linear Goal-Programming (RESEARCH NOTE)

Technology centered organizations must be able to identify promising new products or process improvements at an early stage so that the necessary resources can be allocated to those activities. It is essential to invest in targeted research and development (R and D) projects as opposed to a wide range of ideas so that resources can be focused on successful outcomes. The selection of the most ap...

Long-term R&d Project Selection

Neural network-based mean-variance-skewness model for portfolio selection

In this study, a novel neural network-based mean–variance–skewness model for optimal portfolio selection is proposed integrating different forecasts and trading strategies, as well as investors’ risk preference. Based on the Lagrange multiplier theory in optimization and the radial basis function (RBF) neural network, the model seeks to provide solutions satisfying the trade-off conditions of m...

Mean-variance-skewness model for portfolio selection with fuzzy returns

Article history: Received 21 August 2008 Accepted 4 May 2009 Available online 15 May 2009

Optimal Capital Allocation: Mean-Variance Models

This paper studies capital allocation problem based on minimizing loss functions. Two capital allocation models based on the Mean-Variance principle are proposed. General formulas for optimal capital allocations for both models are derived according to quadratic distance measure. In particular, we discuss centrally symmetric distributions and gamma distributions. Some numerical examples are giv...