Forecasting in a risky situation is a very important function for managers to assist in decision making. One of the fluctuated markets in stock exchange market is chemical market. In this research the target item for prediction is PET (Poly Ethylene Terephthalate) which is the raw material for...

Juris-Data is one of the largest case-study base in France. The case studies are indexed by legal classification elaborated by the Juris-Data Group. Knowledge engineering was used to design an intelligent interface for information retrieval based on this classification. The aim of the system is...

In time series analysis, most estimation of relationships and tests are typically based on linear estimators and most classical co-integration methods and causality tests are based on OLS regresses. However the linear functional specification is not necessarily the most appropriate form. This...

Nowadays, forecasting what will happen in economic environments plays a crucial role. We showed that in PET market how a neuro-fuzzy hybrid model can assist the managers in decision-making. In this research, the target is to forecast the same item through another intelligent tool which obeys the...

Using methods from machine learning - adaptive sequential ridge regression with discount factors - that prevent overfitting in-sample for better and more stable forecasting performance out-of-sample we show that fundamentals from the PPP, UIRP and monetary models consistently improve the...

This work deals with strategies of risk management techniques in projects and portfolios in the situation of radical innovation. Existing literature suggests different methods of risk management at the level of 1) projects (S1) (unknown reduction by selecting a priori the less uncertain...

We propose new scoring rules based on conditional and censored likelihood for assessing the predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management. These scoring rules can be interpreted in terms of...

The proposed paper deals with platform emergence in double unknown situations when technology and markets are highly uncertain. The interest in technological platform development to enable creation of products and processes that support present and future development of multiple options is...

Expected Shortfall (ES) has been widely accepted as a risk measure that is conceptually superior to Value-at-Risk (VaR). At the same time, however, it has been criticized for issues relating to backtesting. In particular, ES has been found not to be elicitable which means that backtesting for ES...

Using non-parametric and parametric models, we show that the bivariate distribution of an Asian portfolio is not stable along all the period under study. We suggest several dynamic models to compute two market risk measures, the Value at Risk and the Expected Shortfall: the RiskMetrics...