This study is the first attempt to investigate both the linear and non-linear Granger causality between wavelet transformed spot and futures oil prices. Our findings consistently indicate bidirectional causality between the spot and futures oil markets at different time scales, under linear and...

This paper examines point and density forecasts from the European Central Bank’s Survey of Professional Forecasters. We derive individual uncertainty measures along with individual point- and density-based measures of disagreement. We also explore the relationship between uncertainty and...

Recent modeling developments have created tradeoffs between attribution-based models, models that rely on causal relationships, and “pure prediction models†such as neural networks. While forecasters have historically favored one technology or the other based on comfort or loyalty to a...

The purpose of this work is to introduce one of the most promising among recently developed statistical techniques – the support vector machine (SVM) – to corporate bankruptcy analysis. An SVM is implemented for analysing such predictors as financial ratios. A method of adapting it to...

In this research note we report on our current efforts on developing a leading indicator of housing prices that could be used to forecast housing prices. Specifically we use Google search index at city level to predict Case-Shiller index. The methodology is based on Granger causality where we...

The forecasting results on Baltic Dry Index of the current scientific approaches are still inferior for decision making to satisfy the ship owners, the charterers, the cargo owners and the economic policy maker. The result of an extensive literature search on forecasting of BDI among the...

It is a common understanding that bankruptcy is not a sudden occurrence for any organizations. Macro and micro economic studies have suggested numerous influential factors, which have substantial evidence toward firm's performance (Bekeris, 2012) and survivability (Nehrebecka & Dzik, 2013). With...

Our paper aims to evaluate two novel methods on selecting the best forecasting model or its combination based on a Machine Learning approach. The methods are based on the selection of the "best" model, or combination of models, by cross-validation technique, from a set of possible models. The...

When borrowers default or fail to repay the lenders (banks), default–linked risks-so called credit risks do emerge. Such risks are critical to several agents like creditors, borrowing firms, and governments alike. As such, financial engineers have been putting in place some scientific...