In this paper we propose a new indicator of monthly global real economic activity, named world steel production. We use world steel production, OECD industrial production index and Kilian's rea index to forecast world real GDP, and key commodity prices. We find that world steel production...

Recent advances in machine learning are finding commercial applications across many industries, not least the finance industry. This paper focuses on applications in one of the core functions of finance, the investment process. This includes return forecasting, risk modelling and portfolio...

In modelling macroeconomic time series, often a monthly indicator of global real economic activity is used. We propose a new indicator, named World steel production, and compare it to other existing indicators, precisely the Kilian's index of global real economic activity and the index of OECD...

This paper focuses on forecasting quarterly energy prices of commodities, such as oil, gas and coal, using the Global VAR dataset proposed by Mohaddes and Raissi (2018). This dataset includes a number of potentially informative quarterly macroeconomic variables for the 33 largest economies,...

This paper establishes the consequences of a wrong specification on the quality of the data envelopment analysis. Specifically, the case of omitting a relevant variable in the input oriented problem is analyzed when there are different correlation structures between the inputs. It is established...

In modelling macroeconomic time series, often a monthly indicator of global real economic activity is used. We propose a new indicator, named World steel production, and compare it to other existing indicators, precisely the Kilian's index of global real economic activity and the index of OECD...

In modelling macroeconomic time series, often a monthly indicator of global real economic activity is used. We propose a new indicator, named World steel production, and compare it to other existing indicators, precisely the Kilian's index of global real economic activity and the index of OECD...

The technologically intensive nature of the predictive maintenance (PdM) method restricts its use to companies with higher turnover. This research is aimed to propose a PdM model for an N-component repairable system by integrating non-homogeneous Poisson process (NHPP) models and a system...

Every machine degrades with time and requires maintenance. Among all types of maintenance policies, predictive maintenance is established as the best form of maintenance policy as numerous benefits are associated with it. Despite all the benefits, it finds restrictive usage in manufacturing...

This paper proposes a predictive maintenance policy using modified failure mode effect and criticality analysis (Mod-FMECA) technique. FMECA is used to identify failure modes, reasons, effects and criticality of the system (machine/plant) but in Mod-FMECA in addition to the analysis carried for...