We use methods of non-extensive statistical physics to describe quantitatively the memory effect involved in returns of companies from WIG 30 index on the Warsaw Stock Exchange. The entropic approach based on the generalization of the Boltzmann-Gibbs entropy to non-additive Tsallis q-entropy is applied to fit fat tailed distribution of returns to q-normal (Tsallis) distribution. The existence of long term memory effects in price returns generated by two-point autocorrelations are checked via calculation of the Hurst exponent within detrended fluctuation analysis approach. The results are collected for diversified frequency of data sampling. We confirm the perfect inverse cubic power law for low time-lags (≈1 min) of returns for the main WIG 30 index as well as for the most of separate stocks, however this relationship does not hold for longer time-lags. The particular emphasis is given to a study of an independent fit of probability distribution of positive and negative returns to qnormal distribution. We discuss in this context the asymmetry between tails in terms of the Tsallis parameters q ± . A qualitative and quantitative relationship between the frequency of data sampling, the parameters q and q ± , and the corresponding main Hurst exponent H is provided to analyze the effect of memory in data caused by linear and nonlinear autocorrelations. A new quantifier based on asymmetry of the Tsallis index instead of skewness of distribution is proposed which we believe is able to describe the stage of market development and its robustness to speculation.

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One of the essential factors influencing the overall urban experience is the presence of biologically active surfaces. Despite widespread awareness of the beneficial effects of such spaces, the natural tissue in cities is still being significantly limited by the priority given to functionality and the economy. The aim of this article is to assess the potential of using a hybrid infrastructure in the grey–green–blue system (GGB) on a public site. In order to assess the efficiency of the implemented solutions, a multi-criteria method was developed, thereby recognising this research aspect as necessary in the process of designing urban built-up spaces. The assessment compared indicators of biological activity in the area using the biotope area factor and green space factor scales. The rainwater retention potential was estimated using a quantitative method. The change in the site’s thermal conditions was analysed by conducting numerous experiments with the use of micrometeorogical computational fluid dynamics models ENVI-met. The demonstrated improvement in the proportion of the biologically active area, water retention, and thermal conditions, ranging from a few to a dozen percent compared to the initial state, confirms the legitimacy of using grey–green–blue infrastructure systems as a method of shaping a sustainable and climate-responsive urban design.

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