Stelios Bekiros - Academia.edu (original) (raw)

Papers by Stelios Bekiros

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mathematics

Due to the vital role of financial systems in today’s sophisticated world, applying intelligent c... more Due to the vital role of financial systems in today’s sophisticated world, applying intelligent controllers through management strategies is of crucial importance. We propose to formulate the control problem of the macroeconomic system as an optimization problem and find optimal actions using a reinforcement learning algorithm. Using the Q-learning algorithm, the best optimal action for the system is obtained, and the behavior of the system is controlled. We illustrate that it is possible to control the nonlinear dynamics of the macroeconomic systems using restricted actuation. The highly effective performance of the proposed controller for uncertain systems is demonstrated. The simulation results evidently confirm that the proposed controller satisfies the expected performance. In addition, the numerical simulations clearly confirm that even when we confined the control actions, the proposed controller effectively finds optimal actions for the nonlinear macroeconomic system.

Chaos, Solitons & Fractals

This paper incorporates anticipated and unexpected shocks to bank capital into a DSGE model with ... more This paper incorporates anticipated and unexpected shocks to bank capital into a DSGE model with a banking sector. We apply this model to study Basel III countercyclical capital requirements and their implications for banking stability and household welfare. We introduce three different countercyclical capital rules. The first countercyclical capital rule responds to credit to output ratio. The second countercyclical rule reacts to deviations of credit to its steady state, and the third rule reacts to credit growth. The second rule proves to be the most effective tool in dampening credit supply, housing demand, household debt and output fluctuations as well as in enhancing the banking stability by ensuring that banks have higher bank capital and capital to asset ratio. After conducting a welfare analysis we find that the second rule outranks the other ones followed by the first rule, the baseline and the third rule respectively in terms of welfare accumulation.

Soft Computing, 2021

A correction to this paper has been published: https://doi.org/10.1007/s00500-021-05882-3

This paper explores a real-world fundamental theme under a data science perspective. It specifica... more This paper explores a real-world fundamental theme under a data science perspective. It specifically discusses whether fraud or manipulation can be observed in and from municipality income tax size distributions, through their aggregation from citizen fiscal reports. The study case pertains to official data obtained from the Italian Ministry of Economics and Finance over the period 2007–2011. All Italian (20) regions are considered. The considered data science approach concretizes in the adoption of the Benford first digit law as quantitative tool. Marked disparities are found, for several regions, leading to unexpected “conclusions”. The most eye browsing regions are not the expected ones according to classical imagination about Italy financial shadow matters. © 2017 Elsevier Ltd. All rights reserved.

We assess the effectiveness of the forward guidance undertaken by European Central Bank using a s... more We assess the effectiveness of the forward guidance undertaken by European Central Bank using a standard medium-scale DSGE model a la Smets and Wouters (2007). Exploiting data on expectations from surveys, we show that incorporating expectations should be crucial in performance evaluation of models for the forward guidance. We conduct an exhaustive empirical exercise to compare the pseudo out-of-sample predictive performance of the estimated DSGE model with a Bayesian VAR and a DSGE-VAR models. DSGE model with expectations outperforms others for inflation; while for output and short term-interest rate the DSGE-VAR with expectations reports the best prediction.

Although policymakers and practitioners are particularly interested in DSGE models, these are typ... more Although policymakers and practitioners are particularly interested in DSGE models, these are typically too stylized to be applied directly to the data and often yield weak prediction re- sults. Very recently, hybrid DSGE model

Annals of Operations Research

It is well documented that the biopharmaceutical sector has exhibited weak financial returns, con... more It is well documented that the biopharmaceutical sector has exhibited weak financial returns, contributing to underinvestment. Innovations in the industry carry high risks; however, an analysis of systematic risk and return compared to other asset classes is missing. This paper investigates the time–frequency interconnectedness between stocks in the biotech sector and ten asset classes using daily cross-country data from 1995 to 2019. We capture investors' heterogeneous investment horizons by decomposing time series according to frequencies. Using a maximal overlap discrete wavelet transform (MODWT) and a dynamic conditional correlation (DCC)-Student-t copula, diversification potentials are revealed, helping investors to reap the benefits of investing in biotech. Our findings indicate that the underlying assets exhibit nonlinear asymmetric behavior that strengthens during periods of turmoil.

Entropy

The Selkov system, which is typically employed to model glycolysis phenomena, unveils some rich d... more The Selkov system, which is typically employed to model glycolysis phenomena, unveils some rich dynamics and some other complex formations in biochemical reactions. In the present work, the synchronization problem of the glycolysis reaction-diffusion model is handled and examined. In addition, a novel convenient control law is designed in a linear form and, on the other hand, the stability of the associated error system is demonstrated through utilizing a suitable Lyapunov function. To illustrate the applicability of the proposed schemes, several numerical simulations are performed in one- and two-spatial dimensions.

Entropy

Although most of the early research studies on fractional-order systems were based on the Caputo ... more Although most of the early research studies on fractional-order systems were based on the Caputo or Riemann–Liouville fractional-order derivatives, it has recently been proven that these methods have some drawbacks. For instance, kernels of these methods have a singularity that occurs at the endpoint of an interval of definition. Thus, to overcome this issue, several new definitions of fractional derivatives have been introduced. The Caputo–Fabrizio fractional order is one of these nonsingular definitions. This paper is concerned with the analyses and design of an optimal control strategy for a Caputo–Fabrizio fractional-order model of the HIV/AIDS epidemic. The Caputo–Fabrizio fractional-order model of HIV/AIDS is considered to prevent the singularity problem, which is a real concern in the modeling of real-world systems and phenomena. Firstly, in order to find out how the population of each compartment can be controlled, sensitivity analyses were conducted. Based on the sensitivit...

Chaos, Solitons & Fractals

Abstract We examine long memory (self-similarity) in digital currencies and international stock e... more Abstract We examine long memory (self-similarity) in digital currencies and international stock exchanges prior and during COVID-19 pandemic. Specifically, ARFIMA and FIGARCH models are respectively employed to evaluate long memory parameter in returns and volatility. The dataset contains 45 cryptocurrency markets and 16 international equity markets. The t-test and F-test are performed to estimated long memory parameters. The empirical findings follow. First, the level of persistence in return series of both markets has increased during the COVID-19 pandemic. Second, during COVID-19 pandemic, variability level in persistence in return series has increased in both digital currencies and stock markets. Third, return series in both markets exhibited comparable level of persistence prior and during the COVID-19 pandemic. Fourth, return series in volatility series of cryptocurrency exhibited high degree of persistence compared to international stock markets during the COVID-19 pandemic. Therefore, it is concluded that COVID-19 pandemic significantly affected long memory in return and volatility of cryptocurrency and international stock markets. In addition, our results suggest that the hybrid long memory model represented by the integration of ARFIMA-FIGARCH is significantly suitable to describe returns and volatility of cryptocurrencies and stocks and to reveal differences before and during COVID-19 pandemic periods.

International Review of Financial Analysis

European Journal of Control

Chaos, Solitons & Fractals

Abstract Due to the importance of consumed control energy in financial systems, employing an opti... more Abstract Due to the importance of consumed control energy in financial systems, employing an optimal controller for these systems could be beneficial. Also, the presence of disturbances is undeniable in most of these systems. Hence, applying optimal mixed H 2 / H ∞ control, which posses the positive features of both H ∞ and H 2 control, could bring up luminous results for these systems. However, in the literature, no attempt has been made to design this type of controller for chaotic financial systems. This issue motivated the current study. In this study, we present a type-2 fuzzy-based optimal mixed H 2 / H ∞ control for a hyperchaotic financial system. In this approach, H ∞ attenuates the effect of uncertainties and through H 2 the consumed control energy is minimized. Also, since the proposed controller is equipped with a type-2 fuzzy observer, it can easily handle uncertainties and unknown functions. Via Lyapunov theorem, it is confirmed that all signals in the system are bounded. In the numerical simulation, firstly, a hyperchaotic financial system with coexisting attractors is investigated. The proposed controller is then applied to the financial system, and the proposed technique's performance is assessed. Numerical simulations clearly confirm the theoretical claims about the effectiveness of the proposed methodology.

Symmetry

Control of supply chains with chaotic dynamics is an important, yet daunting challenge because of... more Control of supply chains with chaotic dynamics is an important, yet daunting challenge because of the limitations and constraints there are in the amplitude of control efforts. In real-world systems, applying control techniques that need a large amplitude signal is impractical. In the literature, there is no study that considers the control of supply chain systems subject to control input limitations. To this end, in the current study, a new control scheme is proposed to tackle this issue. In the designed control input, limitations in control inputs, as well as robustness against uncertainties, are taken into account. The proposed scheme is equipped with a fixed time disturbance observer to eliminate the destructive effects of uncertainties and disturbances. Additionally, the super-twisting sliding mode technique guarantees the fixed-time convergence of the closed-loop system. After that, a symmetric supply chain system is presented, and its chaotic attractors are demonstrated. Fina...

Physica A: Statistical Mechanics and its Applications

Abstract In this paper, by considering the Caputo-like delta difference definition, a fractional ... more Abstract In this paper, by considering the Caputo-like delta difference definition, a fractional difference order map with chaotic dynamics and with no equilibria is proposed. The complex dynamical behaviors associated with fractional difference order maps are analyzed employing the phase portraits, bifurcations diagrams, and Lyapunov exponents. The complexity of the sequence generated by the chaotic difference map is studied using the permutation entropy approach. Afterwards, projective synchronization of the systems is investigated. Fuzzy logic engines as intelligent schemes are strong tools for control of various systems. However, studies that apply fuzzy logic engines for control of fractional-order discrete-time systems are rare. Hence, in the current study, by taking advantages of fuzzy systems, a new controller is proposed for the fractional-order discrete-time map. The fuzzy logic engine is implemented in order to enhance the performance and agility of the proposed control technique. The stability of the closed-loop systems and asymptotic convergence of the projective synchronization error based on the proposed control scheme are proven. Finally, numerical simulations which clearly confirm that the offered control technique is able to push the states of the fractional-order discrete-time system to the desired value in a short period of time are presented.

Start-Ups and SMEs

New developments in the Information and Communications Technology industry have substantially inc... more New developments in the Information and Communications Technology industry have substantially increased the importance of the internet over the last decade. As a result, the finance sector has developed its technological capability to be able to compete in an online marketplace with other financial services providers and to be able to serve their customer. This chapter examines the use of technology in the financial industry and the various factors associated with it, as well as introducing the reader to the main types of project initiators-contributor business relations in online crowdfunding.

Mem-elements for Neuromorphic Circuits with Artificial Intelligence Applications

Mathematics

Due to the vital role of financial systems in today’s sophisticated world, applying intelligent c... more Due to the vital role of financial systems in today’s sophisticated world, applying intelligent controllers through management strategies is of crucial importance. We propose to formulate the control problem of the macroeconomic system as an optimization problem and find optimal actions using a reinforcement learning algorithm. Using the Q-learning algorithm, the best optimal action for the system is obtained, and the behavior of the system is controlled. We illustrate that it is possible to control the nonlinear dynamics of the macroeconomic systems using restricted actuation. The highly effective performance of the proposed controller for uncertain systems is demonstrated. The simulation results evidently confirm that the proposed controller satisfies the expected performance. In addition, the numerical simulations clearly confirm that even when we confined the control actions, the proposed controller effectively finds optimal actions for the nonlinear macroeconomic system.

Chaos, Solitons & Fractals

This paper incorporates anticipated and unexpected shocks to bank capital into a DSGE model with ... more This paper incorporates anticipated and unexpected shocks to bank capital into a DSGE model with a banking sector. We apply this model to study Basel III countercyclical capital requirements and their implications for banking stability and household welfare. We introduce three different countercyclical capital rules. The first countercyclical capital rule responds to credit to output ratio. The second countercyclical rule reacts to deviations of credit to its steady state, and the third rule reacts to credit growth. The second rule proves to be the most effective tool in dampening credit supply, housing demand, household debt and output fluctuations as well as in enhancing the banking stability by ensuring that banks have higher bank capital and capital to asset ratio. After conducting a welfare analysis we find that the second rule outranks the other ones followed by the first rule, the baseline and the third rule respectively in terms of welfare accumulation.

Soft Computing, 2021

A correction to this paper has been published: https://doi.org/10.1007/s00500-021-05882-3

This paper explores a real-world fundamental theme under a data science perspective. It specifica... more This paper explores a real-world fundamental theme under a data science perspective. It specifically discusses whether fraud or manipulation can be observed in and from municipality income tax size distributions, through their aggregation from citizen fiscal reports. The study case pertains to official data obtained from the Italian Ministry of Economics and Finance over the period 2007–2011. All Italian (20) regions are considered. The considered data science approach concretizes in the adoption of the Benford first digit law as quantitative tool. Marked disparities are found, for several regions, leading to unexpected “conclusions”. The most eye browsing regions are not the expected ones according to classical imagination about Italy financial shadow matters. © 2017 Elsevier Ltd. All rights reserved.

We assess the effectiveness of the forward guidance undertaken by European Central Bank using a s... more We assess the effectiveness of the forward guidance undertaken by European Central Bank using a standard medium-scale DSGE model a la Smets and Wouters (2007). Exploiting data on expectations from surveys, we show that incorporating expectations should be crucial in performance evaluation of models for the forward guidance. We conduct an exhaustive empirical exercise to compare the pseudo out-of-sample predictive performance of the estimated DSGE model with a Bayesian VAR and a DSGE-VAR models. DSGE model with expectations outperforms others for inflation; while for output and short term-interest rate the DSGE-VAR with expectations reports the best prediction.

Although policymakers and practitioners are particularly interested in DSGE models, these are typ... more Although policymakers and practitioners are particularly interested in DSGE models, these are typically too stylized to be applied directly to the data and often yield weak prediction re- sults. Very recently, hybrid DSGE model

Annals of Operations Research

It is well documented that the biopharmaceutical sector has exhibited weak financial returns, con... more It is well documented that the biopharmaceutical sector has exhibited weak financial returns, contributing to underinvestment. Innovations in the industry carry high risks; however, an analysis of systematic risk and return compared to other asset classes is missing. This paper investigates the time–frequency interconnectedness between stocks in the biotech sector and ten asset classes using daily cross-country data from 1995 to 2019. We capture investors' heterogeneous investment horizons by decomposing time series according to frequencies. Using a maximal overlap discrete wavelet transform (MODWT) and a dynamic conditional correlation (DCC)-Student-t copula, diversification potentials are revealed, helping investors to reap the benefits of investing in biotech. Our findings indicate that the underlying assets exhibit nonlinear asymmetric behavior that strengthens during periods of turmoil.

Entropy

The Selkov system, which is typically employed to model glycolysis phenomena, unveils some rich d... more The Selkov system, which is typically employed to model glycolysis phenomena, unveils some rich dynamics and some other complex formations in biochemical reactions. In the present work, the synchronization problem of the glycolysis reaction-diffusion model is handled and examined. In addition, a novel convenient control law is designed in a linear form and, on the other hand, the stability of the associated error system is demonstrated through utilizing a suitable Lyapunov function. To illustrate the applicability of the proposed schemes, several numerical simulations are performed in one- and two-spatial dimensions.

Entropy

Although most of the early research studies on fractional-order systems were based on the Caputo ... more Although most of the early research studies on fractional-order systems were based on the Caputo or Riemann–Liouville fractional-order derivatives, it has recently been proven that these methods have some drawbacks. For instance, kernels of these methods have a singularity that occurs at the endpoint of an interval of definition. Thus, to overcome this issue, several new definitions of fractional derivatives have been introduced. The Caputo–Fabrizio fractional order is one of these nonsingular definitions. This paper is concerned with the analyses and design of an optimal control strategy for a Caputo–Fabrizio fractional-order model of the HIV/AIDS epidemic. The Caputo–Fabrizio fractional-order model of HIV/AIDS is considered to prevent the singularity problem, which is a real concern in the modeling of real-world systems and phenomena. Firstly, in order to find out how the population of each compartment can be controlled, sensitivity analyses were conducted. Based on the sensitivit...

Chaos, Solitons & Fractals

Abstract We examine long memory (self-similarity) in digital currencies and international stock e... more Abstract We examine long memory (self-similarity) in digital currencies and international stock exchanges prior and during COVID-19 pandemic. Specifically, ARFIMA and FIGARCH models are respectively employed to evaluate long memory parameter in returns and volatility. The dataset contains 45 cryptocurrency markets and 16 international equity markets. The t-test and F-test are performed to estimated long memory parameters. The empirical findings follow. First, the level of persistence in return series of both markets has increased during the COVID-19 pandemic. Second, during COVID-19 pandemic, variability level in persistence in return series has increased in both digital currencies and stock markets. Third, return series in both markets exhibited comparable level of persistence prior and during the COVID-19 pandemic. Fourth, return series in volatility series of cryptocurrency exhibited high degree of persistence compared to international stock markets during the COVID-19 pandemic. Therefore, it is concluded that COVID-19 pandemic significantly affected long memory in return and volatility of cryptocurrency and international stock markets. In addition, our results suggest that the hybrid long memory model represented by the integration of ARFIMA-FIGARCH is significantly suitable to describe returns and volatility of cryptocurrencies and stocks and to reveal differences before and during COVID-19 pandemic periods.

International Review of Financial Analysis

European Journal of Control

Chaos, Solitons & Fractals

Abstract Due to the importance of consumed control energy in financial systems, employing an opti... more Abstract Due to the importance of consumed control energy in financial systems, employing an optimal controller for these systems could be beneficial. Also, the presence of disturbances is undeniable in most of these systems. Hence, applying optimal mixed H 2 / H ∞ control, which posses the positive features of both H ∞ and H 2 control, could bring up luminous results for these systems. However, in the literature, no attempt has been made to design this type of controller for chaotic financial systems. This issue motivated the current study. In this study, we present a type-2 fuzzy-based optimal mixed H 2 / H ∞ control for a hyperchaotic financial system. In this approach, H ∞ attenuates the effect of uncertainties and through H 2 the consumed control energy is minimized. Also, since the proposed controller is equipped with a type-2 fuzzy observer, it can easily handle uncertainties and unknown functions. Via Lyapunov theorem, it is confirmed that all signals in the system are bounded. In the numerical simulation, firstly, a hyperchaotic financial system with coexisting attractors is investigated. The proposed controller is then applied to the financial system, and the proposed technique's performance is assessed. Numerical simulations clearly confirm the theoretical claims about the effectiveness of the proposed methodology.

Symmetry

Control of supply chains with chaotic dynamics is an important, yet daunting challenge because of... more Control of supply chains with chaotic dynamics is an important, yet daunting challenge because of the limitations and constraints there are in the amplitude of control efforts. In real-world systems, applying control techniques that need a large amplitude signal is impractical. In the literature, there is no study that considers the control of supply chain systems subject to control input limitations. To this end, in the current study, a new control scheme is proposed to tackle this issue. In the designed control input, limitations in control inputs, as well as robustness against uncertainties, are taken into account. The proposed scheme is equipped with a fixed time disturbance observer to eliminate the destructive effects of uncertainties and disturbances. Additionally, the super-twisting sliding mode technique guarantees the fixed-time convergence of the closed-loop system. After that, a symmetric supply chain system is presented, and its chaotic attractors are demonstrated. Fina...

Physica A: Statistical Mechanics and its Applications

Abstract In this paper, by considering the Caputo-like delta difference definition, a fractional ... more Abstract In this paper, by considering the Caputo-like delta difference definition, a fractional difference order map with chaotic dynamics and with no equilibria is proposed. The complex dynamical behaviors associated with fractional difference order maps are analyzed employing the phase portraits, bifurcations diagrams, and Lyapunov exponents. The complexity of the sequence generated by the chaotic difference map is studied using the permutation entropy approach. Afterwards, projective synchronization of the systems is investigated. Fuzzy logic engines as intelligent schemes are strong tools for control of various systems. However, studies that apply fuzzy logic engines for control of fractional-order discrete-time systems are rare. Hence, in the current study, by taking advantages of fuzzy systems, a new controller is proposed for the fractional-order discrete-time map. The fuzzy logic engine is implemented in order to enhance the performance and agility of the proposed control technique. The stability of the closed-loop systems and asymptotic convergence of the projective synchronization error based on the proposed control scheme are proven. Finally, numerical simulations which clearly confirm that the offered control technique is able to push the states of the fractional-order discrete-time system to the desired value in a short period of time are presented.

Start-Ups and SMEs

New developments in the Information and Communications Technology industry have substantially inc... more New developments in the Information and Communications Technology industry have substantially increased the importance of the internet over the last decade. As a result, the finance sector has developed its technological capability to be able to compete in an online marketplace with other financial services providers and to be able to serve their customer. This chapter examines the use of technology in the financial industry and the various factors associated with it, as well as introducing the reader to the main types of project initiators-contributor business relations in online crowdfunding.