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

Publications (63)

Article
Full-text available
In financial markets, information constitutes a crucial factor contributing to the evolution of the system, while the presence of heterogeneous investors ensures its flow among financial products. When nonlinear trading strategies prevail, the diffusion mechanism reacts accordingly. Under these conditions, information englobes behavioral traces of...
Article
In the aim to explore the complex relationships between S&P500, VIX and volume we introduce a Granger causality test using the nonlinear statistic of Asymmetric Partial Transfer Entropy (APTE). Through a simulation exercise, it arises that the APTE offers precise information on the nature of the connectivity. Our empirical findings concretize the i...
Article
In this paper, we further study the dynamics of the Kyrtsou model composed of heterogeneous nonlinear feedback rules. For various levels and types of underlying nonlinearity, we analyze the resulting time series by means of the largest Lyapunov exponent. Our results highlight that the observed interaction among feedback mechanisms cannot lead to a...
Data
Percentage of significant PTE values for system 3 for n = 512/2048, for all resampling methods. A single number is displayed when the same percentage corresponds to both n. The true couplings are highlighted. (DOCX)
Article
Full-text available
Different resampling methods for the null hypothesis of no Granger causality are assessed in the setting of multivariate time series, taking into account that the driving-response coupling is conditioned on the other observed variables. As appropriate test statistic for this setting, the partial transfer entropy (PTE), an information and model-free...
Data
The matlab codes for generating the corresponding simulation time series of the manuscript are provided as a Supplementary File. The financial time series from the real applications can be downloaded from the Federal Reserve Bank of Saint Louis at the following link: https://fred.stlouisfed.org/categories. (ZIP)
Article
Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to specify the direction of the interrelationships among t...
Article
Taking the complex property of nonlinear feedback connectivity into consideration, the goal of this paper is to apprehend the interdependences between the financial and energy sectors. Our contribution is both theoretical and methodological. We conduct a multivariate analysis employing nonlinear tools, namely the Partial Transfer Entropy and the As...
Article
In this paper, a framework is developed for the identification of causal effects from non-stationary time series. Focusing on causality measures that make use of delay vectors from time series, the idea is to account for non-stationarity by considering the ranks of the components of the delay vectors rather than the components themselves. As an exe...
Article
In a recent work we proposed the corrected transfer entropy (CTE), which reduces the bias in the estimation of transfer entropy (TE), a measure of Granger causality for bivariate time series making use of the conditional mutual information. An extension of TE to account for the presence of other time series is the partial TE (PTE). Here, we propose...
Article
Different resampling schemes for the null hypothesis of non-causality are assessed. As test statistic the partial transfer entropy (PTE), an information and model-free measure, is used. Two resampling methods, (1) the time shifted surrogates and (2) the stationary bootstrap, are combined with the following three independence settings (giving in tot...
Article
Measures of the direction and strength of the interdependence among time series from multivariate systems are evaluated based on their statistical significance and discrimination ability. The best-known measures estimating direct causal effects, both linear and nonlinear, are considered, i.e., conditional Granger causality index (CGCI), partial Gra...
Article
IntroductionBackground Hristu-Varsakelis and Kyrtsou Nonlinear Granger Causality Test (2006)Data Description and Empirical ResultsConclusions Appendix: Price Series Used
Article
Full-text available
The volatility clustering frequently observed in financial/economic time series is often ascribed to GARCH and/or stochastic volatility models. This paper demonstrates the usefulness of re-conceptualizing the usual definition of conditional heteroscedasticity as the (h = 1) special case of h-step-ahead conditional heteroscedasticity, where the cond...
Article
A growing body of literature concentrates on the linear dependence between stock returns and inflation. Although the recent empirical evidence suggested the presence of complexities, to our knowledge only a few works have investigated the existence of a potential nonlinear stock returns-inflation relationship. In order to study in more depth the dy...
Article
This paper, investigates the effect war and terrorism, have on the covariance between oil prices and the indices of four major stock markets - the American S&P500 and the European DAX, CAC40 and FTSE100 - using nonlinear BEKK-GARCH type models. Findings reported herein indicate that the covariance between stock and oil returns is affected by war. A...
Article
An increasing number of recent articles applying powerful tests for non-linear causality have fuelled interest in discovering complex dynamics in macroeconomic and financial data. This paper is an attempt to add to the set of available tools by proposing a test for determining the source of causal relationships when a certain class of complex dynam...
Article
Modern economies have been subjected to a number of shocks during the past several years such as the burst of the Internet bubble, terrorist attacks, corporate scandals, the war in Iraq, the uncertainty about energy prices, and the recent subprime mortgage crisis. In particular, during the last few years, the energy shock has caused concerns for po...
Article
The main objective of this paper is to employ a new dynamic model that combines the bivariate noisy Mackey–Glass recently proposed by Kyrtsou and Labys [Kyrtsou, C., Labys, W., 2006. Evidence for chaotic dependence between US inflation and commodity prices. Journal of Macroeconomics 28(1), 256–266; Kyrtsou, C., Labys, W., 2007. Detecting positive f...
Article
Several methods have been developed for filtering seasonal influences and extreme returns in financial and economic time series. The theoretical support for these approaches is rather questionable since it focuses on the effects of shocks on prices and not on their sources. Removing such effects modifies the true generating system of market dynamic...
Article
This paper comments on the multivariate GARCH modeling of federal funds and the 3-month
Article
The aim of this article is the study of complex structures which are behind the short-term predictability of stock returns series. In this regard, we employ a seasonal version of the Mackey-Glass-GARCH(p,q) model, initially proposed by Kyrtsou and Terraza (2003) and generalized by Kyrtsou (2005, 2006). It has either negligible or significant autoco...
Article
In this paper, we further analyse the rich dynamic properties of the noisy chaotic model developed by Kyrtsou (International Journal of Bifurcation and Chaos, 2005) considering homoskedastic errors, in the aim to derive information about possible linkages between noisy chaotic dynamics and ARCH effects. With the joint application of the Engle (1982...
Article
Modern economies have been subjected to a number of shocks during the past several years such as the burst of the Internet bubble, terrorist attacks, corporate scandals, the war in Iraq, the uncertainty about energy prices, and the recent subprime mortgage crisis. In particular, during the last few years, the energy shock has caused concerns for po...
Article
Full-text available
The purpose of this paper is to propose a version of causality testing that focuses on how the sign of the returns affects the causality results. We replace the traditional VAR specification used in the Granger causality test by a discrete-time bivariate noisy Mackey glass model. Our test reveals interesting and previously unexplored relationships...
Article
This paper attempts to investigate further the nonlinear feedback relationship found in Kyrtsou and Labys (2006) between US inflation (BLS CPI) and primary commodity price index (the BLS PPI component for all primary commodity series). Our goal is to disaggregate the above index to the individual commodity level for a group of raw materials prices,...
Article
Recent empirical researches have examined the relationship between US short-term interest rates using linear as well nonlinear econometric tools. The main objective of this paper is to employ a new dynamic model that combines the bivariate noisy Mackey-Glass and the BEKK GARCH processes (recently proposed by Kyrtsou and Labys, 2006, 2007), in the a...
Article
The objective of this paper is to examine causality and feedback relationships between primary commodity prices and US inflation. To this end, the bivariate noisy Mackey–Glass process recently developed by Kyrtsou and Labys [Evidence for chaotic dependence between US inflation and commodity prices, J. Macroecon. 28(1) (2006) 256–266] has been appli...
Article
In this paper, we discuss a number of univariate tests for independence and hidden nonlinear deterministic structure, and apply these tests to the Canadian exchange rate, using daily data over a 30-year period from January 2, 1973 to February 14, 2003.
Article
Our objective in this paper is to identify the nature of the dependence or causal relationship that exists between US inflation and commodity prices using recent methods of linear cointegration, and non-linear Granger causality. The main contribution is the construction of a noisy chaotic multivariate model, using the bivariate noisy Mackey–Glass p...
Article
Several recently developed chaotic forecasting methods give better results than the random walk forecasts. However they do not take into account specific regularities of stock returns reported in empirical finance literature, such as the calendar effects. In this paper, we present a method for filtering the day-of-the-week and the holiday effect in...
Article
In practice it is very difficult to distinguish between stochastic and chaotic non-linearity. It is also difficult to identify non-linear structures in time series when the hidden dynamics are complex. In this paper we provide evidence that in presence of specific high-dimensional underlying structures the White (1989) and Theiler et al. (1992) tes...
Chapter
Full-text available
In this paper we examine the effect of financial development on economic growth in an additive Instrumental Variable (IV)-augmented Partially Linear Regression (PLR) model using panel data of 66 countries for the period 1961-1995. Three common measures of financial development are used. Our results show that the effect of the exogenous component of...
Article
In this work we employ the Recurrence Quantification Analysis (RQA) framework, effective in discovering evidence of non-linear determinism and complex dynamics in short, noisy and irregular signals. We apply RQA to a set of US macroeconomic time series and simulated sequences in order to provide a classification based on topological aspects of thei...
Book
"This volume does exactly what its title says: it acquaints with 'New Trends in Macroeconomics'. More specifically, it contains eleven chapters covering different aspects of modern macroeconomics: short-run fluctuations, long-run growth, monetary economics, international finance, macroeconometrics and complex dynamics. All chapters break new ground...
Article
Full-text available
We investigate for evidence of complex-deterministic dynamics in financial returns time series. By combining the Surrogate Data Analysis inferential framework with the MG-GARCH (Kyrtsou and Terraza, 2003) modelling approach, we examine whether the sequences are characterized by aperiodic and nonlinear deterministic cycles or pure randomness. Our re...
Article
The nonlinear testing and modeling of economic and financial time series has increased substantially in recent years, enabling us to better understand market and price behavior, risk and the formation of expectations. Such tests have also been applied to commodity market behavior, providing evidence of heteroskedasticity, chaos, long memory, cyclic...
Article
Full-text available
Financial returns series typically exhibit excess kurtosis and volatility clustering. The GARCH often is applied to describe these two stylized facts. Nevertheless, in applications of this model to stock returns series it is usually found that it cannot capture all excess kurtosis and high Jarque-Bera. In presence of such dynamics, a model that it...
Article
Most recent empirical works that apply sophisticated statistical proceduressuch as a correlation-dimension method have shown that stock returns arehighly complex. The estimated correlation dimension is high and there islittle evidence of low-dimensional deterministic chaos. Taking the complexbehaviour in stock markets into account, we think it is m...
Article
Recent empirical studies have shown that the chaotic behaviour and excess volatility of financial series are the result of interactions between heterogeneous investors. In our article, we propose verifying this hypothesis. Thus, we use the Chen, Lux, and Marchesi (2000) model to show that the modification of the agents' homogeneity hypothesis can d...
Article
The nonlinear testing and modeling of economic and financial time series has increased substantially in recent years, enabling us to better understand market and price behavior, risk and the formation of expectations. Such tests have also been applied to commodity market behavior, providing evidence of heteroskedasticity, chaos, long memory, cyclic...
Article
In this paper we study the volatility behaviour, the aggregation effects and we investigate the nature of shocks coming disturb the Greek Market. To do so, we apply the ARCH LM, the fractional integration (Geweke and Porter-Hudak, 1983) and the R/S (Lo, 1991) tests, to daily and intra-daily data. The findings support trading-day effects in intra-da...
Article
The purpose of the study is to investigate whether corporate tax policy announcements affect the systematic risk of bank returns in the Athens Stock Exchange for the period: 2001-2006. The study examines the role of Greek financial market as a transmission mechanism for the tax policy announcements released in a period following major institutional...
Article
This paper is an extension of a previous publica- tion in the journal Historical Social Research (Vol. 26, No. 4, 2001, p. 208-219). Our treatment begins with a simple presentation of the basic notions of chaos, and then de- scribes the related econometric tools.
Article
The aim of this article is the study of complex structures, which are behind the short-term predictability of stock returns series. To avoid the limitations of agent-based modelling, we use a seasonal version of the Mackey-Glass-GARCH(p,q) model, initially proposed by Kyrtsou and Terraza (2003) and generalized by Kyrtsou (2004). It has either negli...

Citations

... 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). ...