impact of the Global Financial Crisis. We apply a series of non-parametric based tests utilizing entropy based metrics. These … suggest that the PDFs and CDFs of these two return distributions change shape in various subsample periods. The entropy and MI … relative maximum in the most recent period from 2011 to 2012. The entropy based non-parametric tests of the equivalence of the …

framework forms the basis for an entropy-based stacking model to address issues of inconsistency and bias in classification … individual base models, the proposed entropy-based stacking model provides more consistent performance across multiple data …

Rényi entropy criterion, which summarizes the uncertainty in portfolio returns. Assuming asset returns are projected by a … regime-switching regression model on the two market risk factors, we develop an entropy-based dynamic portfolio selection … empirical Sharpe and return to entropy ratios, the dynamic portfolio under the proposed strategy is much improved in contrast …

quantile (QU) function, moment (MOs), incomplete MOs, conditional MOs, MO-generating function, and entropy. Based on simple …

absolute percentage error (MAPE), symmetric mean absolute percentage error (sMAPE), and Shannon entropy (SE), clearly …

Entropy to quantify the indirect influence that indices have on one another. We find that Transfer Entropy is an effective way …

The present study used transfer entropy and effective transfer entropy to examine the asymmetric information flow … variables is asymmetric. The highest transfer entropy was observed for Gold→EUR/USD among all the pairs under consideration. …

performance over time. Using data on CESEE stock market indices, we model the dynamics of entropy transfers from one return series … previous results. Here, the main results indicate that using entropy transfers in portfolio construction and rebalancing has …

In this paper, we estimate the Shannon entropy S(f)=-E[log(f(x))] of a one-sided linear process with probability …