Catherine Kyrtsou's research while affiliated with University of Macedonia and other places

... The interactions between stocks and contagion risks are essential to understand the stock market fluctuations and global financial crisis [16][17][18]. The classical econometric methods rely on pairwise measurements including Pearson's correlation to describe the relationships within the network system [19][20][21][22]. ...

... Although previous empirical researches have provided an important reference for comprehending the information transmission between markets of carbon emissions and clean energies, the dynamic causality between the price of EUA and the index of clean energy stocks remains elusive and has rarely been investigated using information flow analysis, a natural tool for understanding information transmission. Information flow (or information transfer as it may appear in the literature) is a fundamental physics concept which is logically associated with causality: while a causal relation entails a flow of information, the latter provides a measure of the strength of entailing causality (Liang and Kleeman 2005;Pereda et al 2005) and has been successful in many applications and generalized to multivariate data and nonlinear time series causal analysis (Kyrtsou et al 2019;Li and Liu 2019;Liang 2019;Zhang et al 2022). Recently, causality in terms of information flow has been realized as a real physical notion that can be rigorously formulated from first principles (Liang 2008(Liang , 2016. ...

... The theory of chaos can be represented in the form of an appropriate section of knowledge suitable for searching order in disorder. Initially, this theory was used to develop tools for trading stocks [7], but now the scope of its application in finance has expanded [5]. The main arguments are: (1) chaos theory is competitive and may well become a "convenient" theory of the financial market, (2) traditional finance does not take into account dynamics, while chaos theory is built on the dynamics of the system, which allows the theory to be brought closer to reality, and (3) Instability is associated not only with the crisis, to which the theory of chaos in the financial market is applied, but also from the hypothesis of Minsk's financial instability, which assumes instability of the financial market as such and in many respects links it to its innovativeness. ...

... Transfer entropy has also been extended in the multivariate case, namely the partial transfer entropy (PTE), while different estimators of PTE have been proposed, e.g. based on binning [Verdes, 2005], correlation sums [Vakorin et al., 2009] and k-nearest neighbors [Papana et al., 2012]. The PTE though seems to be only effective for low dimensional systems [Vakorin et al., 2009;Kugiumtzis, 2013b;Papana et al., 2012;Papana et al., 2017]. Spurious causal effects by transfer entropy are discussed in [Smirnov, 2013]. ...

... This means that it measures the number of insertion point it has. While out-degree is the sum of outward connections which means that it measures the number of origins (Papana, Kyrtsou, Kugiumtzis, & Diks, 2017). Directed networks are constructed to reveal casual relationships (Tang, Xiong, Luo, & Zhang, 2019). ...

... Matilla-García (2007) studies the butterfly effect nature of three energy futures series -natural gas, unleaded gasoline and light crude oil -finding its "evidence in futures returns". Kyrtsou et al. (2009), analyze five energy products (crude oil, gasoline, heating oil, propane, and natural gas) over the period from 1994 to mid-January 2008. They reject the null hypothesis of butterfly effect behavior. ...

... Understanding the determinants of the crude oil future market is of great interest. Previous research mainly examines the contributions of supply and demand fundamentals (Pan et al., 2017;Meng and Liu, 2019), macroeconomic factors (Aloui et al., 2016;Meng and Liu, 2019), financial factors (Kyrtsou et al., 2016;Lu et al., 2020) and political factors (Chen et al., 2016; ...

... To estimate only the information transferred directly between the two time series, we need to take into account the influence of the third time series. Partial transfer entropy (PTE) is the extension of TE designed for measuring the influence of X on Y conditioned on Z [67]. In other words, TE has been extended to include the effect of the past of Z on the current state of the response Y and the past of X . ...

... The empirical distribution of PTE, as well as the size and power of the significance test, for the seven resampling methods are assessed in a simulation study. Some first results on the aforementioned resampling methods have been already presented in[46]and[47]. Here, we extend the study of the examined resampling methods in order to establish their performance. ...

... and that the VAR model is stable: the roots of (1 À a 11 L)(1 À a 22 L) À a 12 a 21 L 2 lie outside the unit circle, where L is the lag operator (see, Enders, 2010, Chapter 5). 3 This test has been also discussed by Kyrtsou and Labys (2006, 2007) and by Kyrtsou (2008). 4 The Mackey-Glass equation is a non-linear time delay differential equation of the form dX=dt ¼ Xτ=1 þ X n τ À γX, where β, γ, τ and n are positive real numbers, and X τ represents the value of X at time (t À τ). ...