Publikační činnost Katedry financí / Publications of Department of Finance (154)

Permanent URI for this collectionhttp://hdl.handle.net/10084/64733

Kolekce obsahuje bibliografické záznamy publikační činnosti (článků) akademických pracovníků Katedry financí (154) v časopisech registrovaných ve Web of Science od roku 2003 po současnost.
Do kolekce jsou zařazeny:
a) publikace, u nichž je v originálních dokumentech jako působiště autora (adresa) uvedena Vysoká škola báňská-Technická univerzita Ostrava (VŠB-TUO),
b) publikace, u nichž v originálních dokumentech není v adrese VŠB-TUO uvedena, ale autoři prokazatelně v době jejich zpracování a uveřejnění působili na VŠB-TUO.

Bibliografické záznamy byly původně vytvořeny v kolekci Publikační činnost akademických pracovníků VŠB-TUO, která sleduje publikování akademických pracovníků od roku 1990.

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Now showing 1 - 20 out of 165 results

Systemic risk detection using an entropy approach in portfolio selection strategy
(Springer Nature, 2024) Neděla, David; Tichý, Tomáš; Torri, Gabriele
This paper focuses on the investigation and detection of systemic risk. Such risk significantly affects the financial markets and the banking sector, and is fundamental for macro-prudential regulation. To address this issue, we propose an early warning system to anticipate periods of distress. In particular, we consider systemic risk from the investors' perspective, developing optimal portfolio strategies that incorporate such an early warning system based on different entropy measures to predict and hedge the occurrence of systemic risk. On top of this, we introduce a rule that, in periods of crisis, triggers a switch to a risk-free portfolio. In order to determine the optimal composition of a portfolio, we use a new double-optimization strategy, which consists of the maximization of selected performance ratios in the first step and the minimization of selected systemic risk indicators (CoVaR, Marginal expected shortfall) for a given expected return in the second step. An empirical analysis shows that the proposed strategy allows reducing the total risk of the portfolio and generally improves its profitability. We finally discuss how the introduction of these investment strategies may affect the overall stability of the financial system.
Nonlinear dynamics in an environmental overlapping generations model with technology choice
(Cambridge University Press, 2026) Gori, Luca; Purificato, Francesco; Sodini, Mauro
This paper introduces an overlapping generations model to explore the interplay between economic growth, the environment, and endogenous technology adoption. Considering an economy with physical capital and publicly funded human capital, the analytical framework extends Prieur and Br & eacute;chet (2013, Macroeconomic Dynamics 17, 1135-1157) by incorporating the endogenous technology choice mechanism from Umezuki and Yokoo (2019, Journal of Economic Dynamics & Control 100, 164-175). The analysis focuses on how the choice of capital-intensive technologies impacts environmental dynamics. The model reveals complex equilibrium dynamics, driven by a core trade-off between individuals' resource allocation on consumption versus environmental protection and firms' technology decisions.
Data analysis in demand forecasting: a case study of poetry book sales in the european area
(Vysoká škola ekonomická v Praze, Fakulta podnikohospodářská, 2024) Kolková, Andrea
Logistics concepts are becoming less functional nowadays. The successful concept of just- in-time manufacturing seems untenable for 21st-century Europe. New ideas and new practices are emerging. One of the major trends in contemporary logistics is the demand- driven enterprise. Managing supply, fields and other processes in a company based on demand requires accurate demand forecasting at the relevant time. Relevant data are necessary for this forecasting. In the time of big data, the problem is not collecting data but evaluating them correctly. Data analytics is of great interest in business. The aim of the paper is to verify the possibilities of demand forecasting using traditional statistical methods (exponential smoothing, ARIMA), more advanced statistical methods (TBATS, etc.), methods based on artificial neural networks and a hybrid method. This is in conjunction with thorough data preparation, especially data normality testing. My research question is to provide, on data that contain a number of outliers, the results and the accuracy of the models when the data are or are not normalized. Demand forecasting for poetry books was chosen for the case study. The data were obtained from Google Trends data, i.e., searches for the topic of poetry for the period from 1 September 2013 to 31 September 2023. The results showed that the selected data contain a number of outliers that recur at regular intervals and are the result of a logical order of demand. The expected result was that data normalization increases the accuracy of the model. A method based on artificial neural networks provided significantly more accurate results. However, the resulting estimated underlying trend remained very similar. The article thus opens a discussion about the necessity of excluding outlying observations in time series where outliers exist at regular intervals. Implications for Central European audience: The article poses fundamental scientific questions for Central Europe. Logistics concepts are developing rapidly in this area and Europe is the creator of significant innovations. Europe is currently facing great competition from foreign companies and new logistics concepts are becoming a necessity. Therefore, many European companies now feel the need to change their logistics processes. One of them may be to switch to an adaptive enterprise based on demand. The practical implications are also based on data from Europe.
Do pension funds beat inflation? Assessing trend-dependent risk and dominance techniques
(Springer Nature, 2026) Neděla, David; Kabašinskas, Audrius; Kopa, Miloš
In this paper, we address whether pension fund investments are losing value over time. We propose a new methodology for pension fund risk and performance evaluation based on the trend-risk measurement concept. We analyze the two-sided and downside deviations from a given trend. In the long term, inflation and consumer price changes significantly affect an investor's wealth. For this reason, we consider these macroeconomic indicators to represent a time-dependent trend, which pension funds should outperform. Furthermore, we propose the concept of Time-Cumulative Dominance. This methodology serves as a valuable tool for both portfolio managers and regulators. In the empirical part, we study this new methodology across various pension funds in Lithuania while reflecting on various market conditions and regimes detected by Hidden Markov Models. The results highlight the impact of portfolio composition on the ability to outperform inflation and consumer price changes in the long-term period. We also observe a negative effect during market anomalies.
Mean–trend risk portfolio selection with non-dominated sorting asset preselection
(Palgrave Macmillan, 2026) Neděla, David; Ortobelli, Sergio; Tichý, Tomáš
In the vast landscape of financial markets, identifying potential investment assets such as stocks can be overwhelming and time-consuming. For portfolio managers, focusing on a specific selection of stocks through an effective filtering process can streamline this task. This paper introduces an efficient stock preselection method using multidimensional non-dominated sorting of selected return statistics. Unlike previous research, our approach leverages statistics derived from approximated return series through nonparametric regression and principal component analysis (PCA). We further explore the impact of this preselection on mean-variance and the newly proposed mean-trend risk large-scale portfolio selection strategies. By examining the efficient frontier of portfolios from various return and risk perspectives, our empirical analysis on US stock market data provides both ex-post and ex-ante results for 40 portfolio strategies. The findings suggest that for most risk-averse investors, mean-trend risk strategies with preselection significantly outperform both the same strategies without preselection and traditional mean-variance strategies.
Nonlinear dynamics in a public good game
(Springer Nature, 2024) Gori, Luca; Sodini, Mauro
The present work aims to study the problem of individual voluntary anonymous contributions to the financing of public goods in a dynamic setting. To do this, the article departs from a textbook model & agrave; la Naimzada and Tramontana (2010) augmented with public goods. The article studies how bounded rationality and dependence on agents' past decisions combine with the problem of voluntary contributions. This favours the emergence of nonlinear dynamics in individual behaviour as well as in the aggregate contribution to the financing of a public good project. The Nash equilibrium can be destabilised through a flip bifurcation when the agent reactivity increases. In addition, some Neimark-Sacker bifurcations can also occur although not around the steady-state equilibrium. A sufficiently high agent reactivity level can also lead to chaotic dynamics with possible multiple attractors. When the chaotic regime prevails, synchronisation phenomena in agent behaviour may occur but are rare. Thus, usually, even if agents are homogeneous, they behave as if they were heterogeneous by making non-synchronised decisions. The work also explicitly deepens the case of a heterogeneous economy in terms of both consumer preferences and income.
Green subsidies as strategic trade policy tools
(Springer Nature, 2024) Buccella, Domenico; Fanti, Luciano; Gori, Luca; Sodini, Mauro
In a third-country market model in which two export countries adopt environmental policies (taxes and subsidies), this article analyses how an abatement ("green") subsidy can become a potential strategic trade policy tool. When governments set the optimal policy considering their local environmental damages, a rich set of equilibria arises. In contrast to the standard result, it is shown that subsidising pollution abatement can 1) emerge as the unique Pareto-efficient Nash equilibrium of the policy game, 2) be the only feasible environmental policy when environmental awareness is low, irrespective of the efficiency of the cleaning technology, and 3) emerge as the unique Pareto-inefficient Nash equilibrium of the policy game at the end of the ecological transition. The article also tackles some dynamic issues that the policy game implies.
3D desktop virtual reality as a facilitator of the learning quality and of strengthening students’ results
(Taylor & Francis, 2024) Hvorecký, Jozef; Rozehnal, Petr; Funioková, Taťána; Gurný, Petr
Applications of Virtual Reality in education are becoming more and more frequent. A desktop-based 3D virtual reality environment has been piloted at our university. The aim was to analyse the impact of VRE implementation on results of students. Two educational experiments were conducted in order to evaluate its effect on students' outcomes in the university courses of Finance (N = 177; age 20-24) and Marketing (N = 157; age 20-24). In the case of Finance, a positive impact was demonstrated, while in Marketing, the resulting picture was inconsistent. After disclosing this disproportion, the authors discuss which factors could lead to the differences and what and how could be changed in order to increase the impact of virtual reality on students' results.
Bifurcation structures of a two-dimensional piecewise linear discontinuous map: analysis of a cobweb model with regime-switching expectations
(Springer Nature, 2024) Gardini, Laura; Radi, Davide; Schmitt, Noemi; Sushko, Iryna; Westerhoff, Frank
We consider the bifurcations occurring in a two-dimensional piecewise-linear discontinuous map that describes the dynamics of a cobweb model in which firms rely on a regime-switching expectation rule. In three different partitions of the phase plane, separated by two discontinuity lines, the map is defined by linear functions with the same Jacobian matrix, having two real eigenvalues, one of which is negative and one equal to 0. This leads to asymptotic dynamics that can belong to two or three critical lines. We show that when the basic fixed point is attracting, it may coexist with at most three attracting cycles. We have determined their existence regions, in the two-dimensional parameter plane, bounded by border collision bifurcation curves. At parameter values for which the basic fixed point is repelling, chaotic attractors may exist - either one that is symmetric with respect to the basic fixed point, or, if not symmetric, the symmetric one also exists. The homoclinic bifurcations of repelling cycles leading to the merging of chaotic attractors are commented by using the first return map on a suitable line. Moreover, four different kinds of homoclinic bifurcations of a saddle 2-cycle, leading to divergence of the generic trajectory, are determined.
Nonlinear dynamics and game-theoretic modeling in economics and finance
(Springer Nature, 2024) Bischi, Gian Italo; Baiardi, Lorenzo Cerboni; Lamantia, Fabio; Radi, Davide
In this foreword to the Special Issue “Nonlinear dynamics and game-theoretical model ing in economics and finance” we review the contributions in the issue highlighting the economic results and the connections with aspects of dynamic analysis. Indeed, the com mon theme of the contributions is the focus on system dynamics and the latest analyti cal techniques. This issue is devoted to celebrating the 70th birthday of Professor Laura Gardini, who inspired a generation of scholars in the study of discrete-time systems and global methods of analysis.
Modelling De novo programming within Simon’s satisficing theory: Methods and application in designing an optimal offshore wind farm location system
(Elsevier, 2024) Hocine, Amin; Kouaissah, Noureddine; Lozza, Sergio Ortobelli; Aouam, Tarik
De novo programming (DNP) is an efficient technique for optimal system design. This paper explores the ability to link the DNP technique with Simon's satisficing theory to deal with a system design that is satisfactory rather than optimal. To achieve this aim, the ideal vector is replaced by an aspiration -level vector, and the solutions are determined by minimising the Lp-distance metric between the aspiration level and the feasible objective region. To generate a satisficing solution, we develop two models (weighted DNP (W-DNP) and Chebyshev DNP (C-DNP)) based on goal programming techniques. To achieve equilibrium between the solutions obtained from W-DNP and C-DNP, an extended DNP (E-DNP) model is proposed. Moreover, to deal with uncertainty and give decision makers more flexibility to incorporate their preferences, we consider the concept of penalty function (PF) with DNP and propose DNP type models with penalty functions (DNP-PFs). An illustrative example is adopted to show the usefulness of the proposed approach over the standard DNP. We also conduct a hypothetical application to Italian offshore wind farm locations to assess and validate the proposed formulations for solving real -world problems. To check the stability of the obtained results, the impact of the weights on the obtained solution is detected with a weight-space analysis. The results confirm the proposed methodologies and show that they can assist decision makers in determining the optimal location under uncertain aspiration levels.
Green quality choice in a duopoly
(Wiley, 2024) Gori, Luca; Purificato, Francesco; Sodini, Mauro
This article considers a quantity-setting duopoly (Cournot rivalry) in which firms adopt an abatement technology as a device to improve the quality of products. Consumer preferences capture vertical product differentiation (quality) towards "green" products. This introduces a trade-off on the production side, as firms that do not abate, in turn, do not sustain any abatement cost but the demand for their product is low. On the contrary, firms that choose to abate incur abatement costs, but the demand for their product is high. The article aims to study and understand whether this kind of preference may lead firms to strategically invest in green technology and introduces a new, private-based (that contrasts the well-known public-based) mechanism through which pollution abatement can emerge as a sub-game perfect Nash equilibrium (SPNE) of a non-cooperative abatement decision game with product quality and complete information. The model is developed in a parsimonious way to pinpoint the main determinants of the endogenous market outcomes ranging from an anti-prisoner's dilemma in which self-interest and mutual benefit of non-abatement do not conflict to an anti-prisoner's dilemma in which self-interest and mutual benefit of abatement do not conflict, passing through to an anti-coordination scenario. Additionally, the welfare analysis reveals the existence of a win-win solution from a societal perspective. The article shows that the results obtained in the Cournot setting also hold considering a Bertrand duopoly.
Maladaptation in an unequal world: an evolutionary model with heterogeneous agents
(Springer Nature, 2024) Antoci, Angelo; Borghesi, Simone; Galdi, Giulio; Sodini, Mauro; Ticci, Elisa
Maladaptation is steadily increasing its presence in agenda and debates about climate change and its impacts. The term denotes actions undertaken, at the individual or collective level, to defend against the adverse effects of climate change or environmental degradation, but that ultimately exacerbate the underlying risk factors. In this paper, we investigate the effects of maladaptation in terms of well-being and inequality in a two-population (North-South) evolutionary model. While agents in the South often face higher vulnerability to environmental degradation and limited defense mechanisms compared to their Northern counterparts, the latter stand to endure greater economic losses, in absolute terms. Our model demonstrates that the diffusion of maladaptive choices could result in a Pareto-dominated steady state, influencing inequality levels positively or negatively based on the scale of maladaptation impacts relative to the existing environmental degradation. These findings stress the imperative of integrating environmental risk studies with maladaptive effects and dynamics. Additionally, they advocate for international discourse not only on climate change mitigation but also on adaptive measures among countries.
Debt stabilisation and dynamic interaction between monetary authority and national fiscal authorities
(Springer Nature, 2024) Gori, Luca; Purificato, Francesco; Sodini, Mauro
The main aim of the present research is to consider a monetary union's economy consisting of N countries, N fiscal authorities (one for each country) and a single monetary authority. The fiscal authorities want to stabilise output and public debt through the primary government balance, and they can exhibit heterogeneous preferences about the trade-off between output and debt stability. Unlike these, the monetary authority has the aim of price and output stability. They play a non-cooperative policy game, in which they independently and simultaneously choose monetary and fiscal instruments to pursue their goals. In a dynamic setting, each authority must choose its policy instrument prevailing in the next period without knowing-at the end of each period-the choice of other authorities. By assuming static expectations, the present work shows the possibility of several dynamic outcomes. First, there exists one Nash equilibrium representing the optimal level for the macro economy; this equilibrium is stable if the average weight that fiscal authorities assign to output stability is not excessively high; therefore, this result holds even if some authorities are less willing to promote debt stabilisation. Second, in addition to this equilibrium, there exist other Nash equilibria representing steady-state values for macroeconomic variables that differ from the targets adopted by the authorities; these equilibria emerge and are stable if the authorities' preference for output stability is even greater and with a higher degree of heterogeneity compared to the previous case. Third, the parameters of the model matter to determine the stability properties of the equilibria, and the analysis shows the possibility of nonlinear dynamics.
Individual evolutionary learning in repeated beauty contest games
(Elsevier, 2024) Anufriev, Mikhail; Duffy, John; Panchenko, Valentyn
The Individual Evolutionary Learning (IEL) algorithm was proposed as a portable learning model for games with large strategy spaces. In principle, IEL benchmark simulations could substitute or supplement expensive experiments with human subjects. We evaluate the ability of the IEL model to replicate experimental findings observed in repeated Keynesian Beauty Contest (KBC) games, which have a large strategy space. The IEL specification with standard parameter values is able to capture major dynamical features and differences between treatments in both one-dimensional (Nagel, 1995; Duffy and Nagel, 1997) and two-dimensional (Anufriev et al., 2022b) versions of KBC games. We compare IEL with some other simple learning models and find that it performs relatively better across multiple treatments. We also use IEL to predict behavior in repeated KBC games that have not yet been conducted experimentally.
Dynamic return scenario generation approach for large-scale portfolio optimisation framework
(Springer Nature, 2024) Neděla, David; Ortobelli Lozza, Sergio; Tichý, Tomáš
In this paper, we propose a complex return scenario generation process that can be incorporated into portfolio selection problems. In particular, we assume that returns follow the ARMA–GARCH model with stable-distributed and skewed t-copula dependent residuals. Since the portfolio selection problem is large-scale, we apply the multifactor model with a parametric regression and a nonparametric regression approaches to reduce the complexity of the problem. To do this, the recently pro posed trend-dependent correlation matrix is used to obtain the main factors of the asset dependency structure by applying principal component analysis (PCA). How ever, when a few main factors are assumed, the obtained residuals of the returns still explain a non-negligible part of the portfolio variability. Therefore, we propose the application of a novel approach involving a second PCA to the Pearson correlation to obtain additional factors of residual components leading to the refinement of the f inal prediction. Future return scenarios are predicted using Monte Carlo simula tions. Finally, the impact of the proposed approaches on the portfolio selection prob lem is evaluated in an empirical analysis of the application of a classical mean–vari ance model to a dynamic dataset of stock returns from the US market. The results show that the proposed scenario generation approach with nonparametric regression outperforms the traditional approach for out-of-sample portfolios.
Two-population evolutionary oligopoly with partial cooperation and partial hostility
(Springer Nature, 2024) Lamantia, Fabio; Radi, Davide; Tichý, Tomáš
In this paper, we reconsider the model in Bischi and Lamantia (J Econ Interact Coord 17:3-27, 2022) and reformulate it in a two-population context. There, the Cournot duopoly market examined is in equilibrium (Cournot-Nash-equilibrium quantities are produced) conditionally to the players' (heterogeneous) attitudes toward cooperation. To accommodate players' attitudes, their objective functions partly include the opponent's profit, resulting in greater (partial) cooperation or hostility toward the opponent than in the standard duopoly setting. An evolutionary selection mechanism determines the survival of cooperative or competitive strategies in the duopoly. The game is symmetric and Bischi and Lamantia (J Econ Interact Coord 17:3-27, 2022) assumes that the two players involved start the game by choosing the same strategic profile. In this way, the full-fledged two-population game simplifies in a one-dimensional map. In this paper, we relax this assumption. On one hand, this approach allows us to investigate entirely the dynamics of the model and the evolutionary stability of the Nash equilibria of the static game that is implicit in the evolutionary setup. In fact, the model with only one population partially represents the system dynamics occurring in an invariant subset of the phase space. As a remarkable result, this extension shows that the steady state of the evolutionary model where all players are cooperative can be an attractor, although only in the weak sense, even when it is not a Nash equilibrium. This occurs when firms have a very high propensity to change strategies to the one that performs better. On the other hand, this approach allows us to accommodate players' heterogeneity (non-symmetric version of the game), whose analysis confirms the main insights attained in the homogeneous setting.
Evaluation of strategy portfolios
(Springer Nature, 2024) Wang, Anlan; Kresta, Aleš; Tichý, Tomáš
People usually create a portfolio in order to diversify the risk coming from individual investments. To get a high yield with a good level of diversification, investors usually seek professional advice from portfolio managers. However, the true performance of an optimized portfolio usually depends on the correctness of the estimates of the distribution of future returns, which is often a matter of luck rather than skill. Thus, the optimization models may not be better than randomly selected portfolios. Our aim is to find how the so-called strategy portfolios, i.e., portfolios obtained by some decision optimized for a long-run horizon, perform compared to a benchmark, namely, a random investment, under specific market conditions. For this purpose, we evaluate several portfolio strategies over two periods of crisis: the subprime mortgage crisis and the Covid-19 pandemic, as well as run a moving window analysis over a longer horizon. In each case, the results are compared with the performance of random-weight portfolios. We find that if the strategy is minimization, the portfolios perform well; however, for the maximization of the objectives, the results are rather mixed.
Insights on the theory of robust games
(Springer Nature, 2023) Crespi, G. P.; Radi, Davide; Rocca, M.
A robust game is a distribution-free model to handle ambiguity generated by a bounded set of possible realizations of the values of players' payoff functions. The players are worst-case optimizers and a solution, called robust-optimization equilibrium, is guaranteed by standard regularity conditions. The paper investigates the sensitivity to the level of uncertainty of this equilibrium focusing on robust games with no private information. Specifically, we prove that a robust-optimization equilibrium is an epsilon-Nash equilibrium of the nominal counterpart game, where epsilon measures the extra profit that a player would obtain by reducing his level of uncertainty. Moreover, given an epsilon-Nash equilibrium of a nominal game, we prove that it is always possible to introduce uncertainty such that the epsilon-Nash equilibrium is a robust-optimization equilibrium. These theoretical insights increase our understanding on how uncertainty impacts on the solutions of a robust game. Solutions that can be extremely sensitive to the level of uncertainty as the worst-case approach introduces non-linearity in the payoff functions. An example shows that a robust Cournot duopoly model can admit multiple and asymmetric robust-optimization equilibria despite only a symmetric Nash equilibrium exists for the nominal counterpart game.
Penalized enhanced portfolio replication with asymmetric deviation measures
(Springer Nature, 2023) Torri, Gabriele; Giacometti, Rosella; Paterlini, Sandra
Passive investment strategies, such as those implemented by Exchange Traded Funds (ETFs), have gained increasing popularity among investors. In this context, smart beta products promise to deliver improved performance or lower risk through the implementation of sys tematic investing strategies, and they are also typically more cost-effective than traditional active management. The majority of research on index replication focuses on minimizing tracking error relative to a benchmark index, implementing constraints to improve perfor mance, or restricting the number of assets included in portfolios. Our focus is on enhancing the benchmark through a limited number of deviations from the benchmark. We propose a range of innovative investment strategies aimed at minimizing asymmetric deviation mea sures related to expectiles and quantiles, while also controlling for the deviation of portfolio weights from the benchmark composition through penalization. This approach, as compared to traditional minimum tracking error volatility strategies, places a greater emphasis on the overall risk of the portfolio, rather than just the risk relative to the benchmark. The use of penalization also helps to mitigate estimation risk and minimize turnover, as compared to strategies without penalization. Through empirical analysis using simulated and real-world data, we critically examine the benefits and drawbacks of the proposed strategies in compar ison to state-of-the-art tracking models.

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