Elena Fedorova

TL;DR: Different combinations of modern learning algorithms are applied to try to identify the most effective approach to bankruptcy prediction for Russian manufacturing companies to find out whether the financial indicators stipulated by Russian legislation provide an effective set of indicators for bankruptcy prediction.

TL;DR: The genetic algorithm based two-step classification method (TSCM) is suggested that allows both selecting the relevant factors and adapting the model itself to application to improve the advantages and alleviate the weaknesses inherent in ordinary classifiers, enabling the business decisions support with a higher reliability.

TL;DR: In this paper, the authors examined mean-to-mean, volatility to-mean and volatility-tovolatility spillover effects for the stock markets of BRIC countries using a 4-dimensional BEKK-GARCH-in-mean model.

TL;DR: In this article, the impact of outlier filtering on forecasting accuracy based on a recently introduced seasonal component autoregressive model was discussed, and it was shown that such data preprocessing often leads to the forecasting accuracy gain while the error decrease (relative to the approach without filtering) in a number of cases may reach 1.8-1.9% of the average weekly price (in absolute values).

TL;DR: An improved approach to electricity prices trend-cyclical component filtering, which is based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and the combined criterion for determining the modes to be included into the trend component is introduced.