In this paper, a crisis index for the oil price shock is defined and a neural network model is specified for the prediction of the crisis index. This paper contributes to the literature in three ways. First, we build an early warning system for crude oil price. Although the oil price became one...

We present how to enhance classical generalized linear models by neural network features. On the way there, we highlight the traps and pitfalls that need to be avoided to get good statistical models. This includes the non-uniqueness of sufficiently good regression models, the balance property,...

Bankruptcy is a menacing situation, which the investors, businesses, and the economy are afraid of, due to its adverse effects. Prediction of bankruptcy can help the investors and businesses in formulating their strategies in order to improve their profits or at least avoid losses. Researchers...

Quite a few in-depth articles were found in the above-mentioned domain. Bankruptcy is one of the most critical factors which most of companies don't want to face. To predict the Bankruptcy of Banks, there have been several attempts made, some have been successful and some are coming up with new...

The research focuses on the financial turmoil, pursuing different methods to foretell such turmoil. Besides, the methods are undertaken from (McCulloch and Pitts 1943) and ended till (Hosaka 2019). The evidence from such a comprehensive analysis pointed to the use of various ratios using...

One of the main challenges for life actuaries is modeling and predicting the future mortality evolution. To this end, several stochastic mortality models have been proposed in literature, starting from the pivotal approach of the Lee-Carter model. These models essentially use the ARIMA processes...

In this work we use Recurrent Neural Networks and Multilayer Perceptrons, to predict NYSE, NASDAQ and AMEX stock prices from historical data. We experiment with different architectures and compare data normalization techniques. Then, we leverage those findings to question the efficient-market...

In this work we show a briefly presentation of four approaches to opinion polls. The example we present here, is referred on exit polls which have been realized for the elections of Serres Municipal in Greece on October 22nd of 2006. The methodology can be applied in any opinion poll, not only...

Forecasting plays an essential role in energy economics. With new challenges and use cases in the energy system, forecasts have to meet more complex requirements, such as increasing temporal and spatial resolution of data. The concept of machine learning can meet these requirements by providing...

This paper introduces the OECD Weekly Tracker of economic activity for 46 OECD and G20 countries using Google Trends search data. The Tracker performs well in pseudo-real time simulations including around the COVID-19 crisis. The underlying model adds to the previous Google Trends literature in...