In this paper we investigate a multi-objective portfolio selection model with three criteria: risk, return and liquidity for investors. Non-probabilistic uncertainty factors in the market, such as imprecision and vagueness of investors’ preference and judgement are simulated in the portfolio selection process. The liquidity of portfolio cannot be accurately predicted in the market, and thus is ...

This paper considers the problem of modelling and forecasting for multivariate financial time series. The use of Dynamic Linear State Space models and Stochastic Volatility models with Kalman filtering techniques to address this problem is considered in the context of providing a modular software implementation. The combination of these two approaches is presented with an illustrative example. ...

Floating, Production, Storage and Offloading “FPSO” have become a popular choice since 1980s for marginal and fast-track developments where subsea pipeline is not an economic or feasible solution for export. Field development usually starts with a concept selection procedure which is constituted from a sequence of multi-disciplinary decision making tasks. As limited data is availabl...

Methods for the selection of a research and development (R&D) project portfolio have attracted considerable interest among practitioners and academics. However, these methods have found limited use in practice, partly because they have encountered difficulties in capturing uncertainties and interdependencies related to R&D projects. Motivated by these difficulties, we develop Contingent Portfol...

Investing in financial market require the reliable predicting of expecting returns, assessment of risk and reliability. Principle of portfolio orthogonality was using to reduce the risk of the investment. An artificial intelligence system may reveal new opportunities for using this principle. Prediction of recurrent neural networks ensemble is stochastically informative distribution, which is h...