The entropy as a tool for analysing statistical dependences in financial time series

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Efficient factor GARCH models and factor-DCC models (2009, methodology): “financial time series (Dion´ isio et al., 2003; Darbellay & Wuertz, 2000; Maasoumi & Racine,”
Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency (2010, background): “The concept of entropy can be of great help when analyzing stock market data since it captures the uncertainty and disorder of the time series without imposing any limitations on the theoretical probability distribution [30,31].”
Forbidden patterns, permutation entropy and stock market inefficiency (2009, background): “Furthermore, the concept of entropy can be of great help when analyzing stockmarket data since it captures the uncertainty and disorder of the time series without imposing any constraints on the theoretical probability distribution [23,24].”
Characterizing the spatial variability of groundwater quality using the entropy theory: I. Synthetic data (2004, methodology): “The entropy (or information) theory, developed by Shannon (1948), recently has been applied in many different fields, such as ecology, biology, data mining and financial time-series analysis (e.g. Darbellay and Wuertz, 2000; Rojdestvenski and Cottam, 2000; Sy, 2001; Ulanowicz, 2001).”