arXiv subjects

Andrea Rapisarda

Publications and source records attributed to Andrea Rapisarda.

At least 19 recordsLinked to original sources

arXiv2024

Early Career Wins and Tournament Prestige Characterize Tennis Players' Trajectories

Success in sports is a complex phenomenon that has only garnered limited research attention. In particular, we lack a deep scientific understanding of success in sports like tennis and the factors that contribute to it. Here, we study the unfolding of tennis players' careers to understand the role of early career stages and the impact of specific tournaments on players' trajectories. We employ a comprehensive approach combining network science and analysis of ATP tournament data and introduce a novel method to quantify tournament prestige based on the eigenvector centrality of the co-attendance network of tournaments. Focusing on the interplay between participation in central tournaments and players' performance, we find that the level of the tournament where players achieve their first win is associated with becoming a top player. This work sheds light on the critical role of the initial stages in the progression of players' careers, offering valuable insights into the dynamics of success in tennis.

physics.soc-ph↗

arXiv2023

The Paradox of Talent: how Chance affects Success in Tennis Tournaments

Individual sports competitions provide a natural setting for examining the relative importance of talent and luck/chance in achieving success. The belief that success is primarily due to individual abilities and hard work rather than external factors is particularly strong in this context. In this study, we test this belief using tennis as a case study, due to its popularity and competition structure in direct-elimination tournaments. Our dataset covers the decade 2010-2019 of main events in the ATP circuit and consists of tourney results and annual rankings for professional male players. After a preliminary data analysis, we introduce an agent-based model able to accurately simulate the tennis players' dynamics along several seasons. We show that, once calibrated on the dataset, the model is able to reproduce the main stylized facts observed in real data, including the results of single tournaments and the development of players' careers in the ATP community. The strength of our approach lies in its simplicity: it requires only one free parameter a to determine the importance of talent in scoring every single point: a = 1, if only talent matters; a = 0, if the outcome of each point is entirely due to chance. We find the best agreement between real data and simulation results when talent weights substantially less than luck, i.e. when a is between 0.20 and 0.30. A further comparison between data and simulations, based on the analysis of the direct networks of all the matches, confirms the previous finding. A posteriori, we notice that this surprisingly important role of chance in tennis tournaments is not an exception. On the contrary, it can be explained by a more general paradoxical effect that characterizes highly competitive environments, particularly in individual sports. In other words, when the difference in talent between top players is minimal, chance becomes determinant.

physics.soc-ph↗

arXiv2022

Pairwise and high-order dependencies in the cryptocurrency trading network

In this paper we analyse the effects of information flows in cryptocurrency markets. We first define a cryptocurrency trading network, i.e. the network made using cryptocurrencies as nodes and the Granger causality among their weekly log returns as links, later we analyse its evolution over time. In particular, with reference to years 2020 and 2021, we study the logarithmic US dollar price returns of the cryptocurrency trading network using both pairwise and high-order statistical dependencies, quantified by Granger causality and O-information, respectively. With reference to the former, we find that it shows peaks in correspondence of important events, like e.g., Covid-19 pandemic turbulence or occasional sudden prices rise. The corresponding network structure is rather stable, across weekly time windows in the period considered and the coins are the most influential nodes in the network. In the pairwise description of the network, stable coins seem to play a marginal role whereas, turning high-order dependencies, they appear in the highest number of synergistic information circuits, thus proving that they play a major role for high order effects. With reference to redundancy and synergy with the time evolution of the total transactions in US dollars, we find that their large volume in the first semester of 2021 seems to have triggered a transition in the cryptocurrency network toward a more complex dynamical landscape. Our results show that pairwise and high-order descriptions of complex financial systems provide complementary information for cryptocurrency analysis.

q-fin.TR↗

arXiv2022

Objective and perceived risk in seismic vulnerability assessment at urban scale

The assessment of seismic risk in urban areas with high seismicity is certainly one of the most important problems that territorial managers have to face. A reliable evaluation of this risk is the basis for the design of both specific seismic improvement interventions and emergency management plans. Unappropriate seismic risk assessments may provide misleading results and induce bad decisions with relevant economic and social impact. The seismic risk in urban areas is mainly linked to three factors, namely, "hazard", "exposure" and "vulnerability". Hazard measures the potential of an earthquake to produce harm; exposure evaluates the amount of population exposed to harm; vulnerability represents the proneness of considered buildings to suffer damages in case of an earthquake. Estimates of such factors may not always coincide with the perceived risk of the resident population. The propensity to implement structural seismic improvement interventions aimed at reducing the vulnerability of buildings depends significantly on the perceived risk. This paper investigates on the difference between objective and perceived risk and highlights some critical issues. The aim of this study is to calibrate opportune policies, which allow addressing the most appropriate seismic risk mitigation options with reference to current levels of perceived risk. We propose the introduction of a Seismic Policy Prevention index (SPPi). This methodology is applied to a case-study focused on a densely populated district of the city of Catania (Italy).

physics.soc-ph↗

arXiv2020

On the origins of extreme wealth inequality in the Talent vs Luck Model

While wealth distribution in the world is highly skewed and heavy-tailed, human talent - as the majority of individual features - is normally distributed. In a recent computational study by Pluchino et al [Talent vs luck: The role of randomness in success and failure, Adv. Complex Syst. 21 (03-04) (2018) 1850014], it has been shown that the combined effects of both random external factors (lucky and unlucky events) and multiplicative dynamics in capital accumulation are able to clarify this apparent contradiction. We introduce here a simplified version (STvL) of the original Talent versus Luck (TvL) model, where only lucky events are present, and verify that its dynamical rules lead to the same very large wealth inequality as the original model. We also derive some analytical approximations aimed to capture the mechanism responsible for the creation of such wealth inequality from a Gaussian-distributed talent. Under these approximations, our analysis is able to reproduce quite well the results of the numerical simulations of the simplified model in special cases. On the other hand, it also shows that the complexity of the model lies in the fact that lucky events are transformed into an increase of capital with heterogeneous rates, which yields a non-trivial generalization of the role of multiplicative processes in generating wealth inequality, whose fully generic case is still not amenable to analytical computations.

physics.soc-ph↗

arXiv2019

A generalised model for asymptotically-scale-free geographical networks

We consider a generalised d-dimensional model for asymptotically-scale-free geographical networks. Central to many networks of this kind, when considering their growth in time, is the attachment rule, i.e. the probability that a new node is attached to one (or more) preexistent nodes. In order to be more realistic, a fitness parameter $η_i \in [0,1]$ for each node $i$ of the network is also taken into account to reflect the ability of the nodes to attract new ones. Our d-dimensional model takes into account the geographical distances between nodes, with different probability distribution for $η$ which sensibly modifies the growth dynamics. The preferential attachment rule is assumed to be $Π_i\propto k_i η_i r_{ij}^{-α_A} $ where $k_i$ is the connectivity of the $i$th pre-existing site and $α_A$ characterizes the importance of the euclidean distance r for the network growth. For special values of the parameters, this model recovers respectively the Bianconi-Barabási and the Barabási-Albert ones. The present generalised model is asymptotically scale-free in all cases, and its degree distribution is very well fitted with q-exponential distributions, which optimise the nonadditive entropy $S_q$, given by $p(k) \propto e_q^{-k/κ} \equiv 1/[1+(q-1)k/κ]^{1/(q-1)}$, with $(q,κ)$ depending uniquely only on the ratio $α_A/d$ and the fitness distribution. Hence this model constitutes a realization of asymptotically-scale-free geographical networks within nonextensive statistical mechanics, where $k$ plays the role of energy and $κ$ plays the role of temperature. General scaling laws are also found for q as a function of the parameters of the model.

physics.soc-ph↗

arXiv2019

Inequalities, chance and success in sport competitions: simulations vs empirical data

We present a new way of estimation of the role of chance in achieving success, by comparing the empirical data from 100-meter dash competitions (one of the sports disciplines with the most stringent controls of external randomness), with the results of an agent-based computer model, which assumes that success depends jointly on the intrinsic talent of the agent and on unpredictable luck. We find a small, but non-zero contribution of random luck to the performance of the best sprinters, which may serve as a lower bound for the randomness role in other, less stringently controlled competitive domains. Additionally we discuss the perception of the payoff differences among the top participants, and the role of random luck in the resulting inequality.

physics.soc-ph↗

arXiv2019

Quantum statistics in Network Geometry with Fractional Flavor

Growing network models have been shown to display emergent quantum statistics when nodes are associated to a fitness value describing the intrinsic ability of a node to acquire new links. Recently it has been shown that quantum statistics emerge also in a growing simplicial complex model called Network Geometry with Flavor which allow for the description of many-body interaction between the nodes. This model depend on an external parameter called flavor that is responsible for the underlying topology of the simplicial complex. When the flavor takes the value $s=-1$ the $d$-dimensional simplicial complex is a manifold in which every $(d-1)$-dimensional face can only have an incidence number $n_α\in\{0,1\}$. In this case the faces of the simplicial complex are naturally described by the Bose-Einstein, Boltzmann and Fermi-Dirac distribution depending on their dimension. In this paper we extent the study of Network Geometry with Flavor to fractional values of the flavor $s=-1/m$ in which every $(d-1)$-dimensional face can only have incidence number $n_α\in\{0,1,2,\dots, m\}$. We show that in this case the statistical properties of the faces of the simplicial complex are described by the Bose-Einstein or the Fermi-Dirac distribution only. Finally we comment on the spectral properties of the networks constituting the underlying structure of the considered simplicial complexes.

cond-mat.dis-nn↗

arXiv2019

Why lot: How sortition came to help representative democracy

In this paper we discuss the problems of modern representative democracy and we look at the selection of legislators by lot as a way to tame some of the drawbacks of that system. It is recalled at the beginning that resorting to sortition for the selection of public officers used to be a popular way of taming factionalism in public affairs. Factionalism is assumed to be detrimental to public affairs as public officers may favour their own faction (a tribe or a party) instead of pursuing the general interest. Moreover they tend to overinvest in strengthening their power, thus engaging in power struggles with opposing factions, unlikely to benefit society. In this respect we present a new mathematical model aiming at describing a more efficient parliament where sortition is brought to bear. It will be shown that starting from a parliament working with two parties (or coalitions), where the costs of representative democracy are quite apparent through the detrimental effects of party discipline, one can beneficially move towards a parliament where independent legislators, randomly selected from the population of constituents, sit alongside elected members who belong to a party and are subjected to party discipline. The paper shows that increasing the number of independent legislators up to a point enhances the efficiency of the parliament and puts into check the factionalism likely to arise from party discipline.

physics.soc-ph↗

arXiv2019

Exploring the Role of Interdisciplinarity in Physics: Success, Talent and Luck

Although interdisciplinarity is often touted as a necessity for modern research, the evidence on the relative impact of sectorial versus to interdisciplinary science is qualitative at best. In this paper we leverage the bibliographic data set of the American Physical Society to quantify the role of interdisciplinarity in physics, and that of talent and luck in achieving success in scientific careers. We analyze a period of 30 years (1980-2009) tagging papers and their authors by means of the Physics and Astronomy Classification Scheme (PACS), to show that some degree of interdisciplinarity is quite helpful to reach success, measured as a proxy of either the number of articles or the citations score. We also propose an agent-based model of the publication-reputation-citation dynamics reproduces the trends observed in the APS data set. On the one hand, the results highlight the crucial role of randomness and serendipity in real scientific research; on the other, they shed light on a counter-intuitive effect indicating that the most talented authors are not necessarily the most successful ones.

physics.soc-ph↗

arXiv2018

Exploring the role of talent and luck in getting success

We review recent numerical results on the role of talent and luck in getting success by means of a schematic agent-based model. In general the role of luck is found to be very relevant in order to get success, while talent is necessary but not sufficient. Funding strategies to improve the success of the most talented people are also discussed.

physics.soc-ph↗

arXiv2018

Testing demand responsive shared transport services via agent-based simulations

Demand Responsive Shared Transport DRST services take advantage of Information and Communication Technologies ICT, to provide on demand transport services booking in real time a ride on a shared vehicle. In this paper, an agent-based model ABM is presented to test different the feasibility of different service configurations in a real context. First results show the impact of route choice strategy on the system performance.

cs.MA↗

arXiv2016

Finding shared decisions in stakeholder networks: an agent-based approach

We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations' results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

physics.soc-ph↗

arXiv2016

A multilayer approach for price dynamics in financial markets

We introduce a new Self-Organized Criticality (SOC) model for simulating price evolution in an artificial financial market, based on a multilayer network of traders. The model also implements, in a quite realistic way with respect to previous studies, the order book dy- namics, by considering two assets with variable fundamental prices. Fat tails in the probability distributions of normalized returns are observed, together with other features of real financial markets.

q-fin.TR↗

arXiv2016

Order Book, Financial Markets and Self-Organized Criticality

We present a simple order book mechanism that regulates an artificial financial market with self-organized criticality dynamics and fat tails of returns distribution. The model shows the role played by individual imitation in determining trading decisions, while fruitfully replicates typical aggregate market behavior as the "self-fulfilling prophecy". We also address the role of random traders as a possible decentralized solution to dampen market fluctuations.

q-fin.TR↗

arXiv2014

Micro and Macro Benefits of Random Investments in Financial Markets

In this paper, making use of recent statistical physics techniques and models, we address the specific role of randomness in financial markets, both at the micro and the macro level. In particular, we review some recent results obtained about the effectiveness of random strategies of investment, compared with some of the most used trading strategies for forecasting the behavior of real financial indexes. We also push forward our analysis by means of a Self-Organized Criticality model, able to simulate financial avalanches in trading communities with different network topologies, where a Pareto-like power law behavior of wealth spontaneously emerges. In this context, we present new findings and suggestions for policies based on the effects that random strategies can have in terms of reduction of dangerous financial extreme events, i.e. bubbles and crashes.

q-fin.GN↗

arXiv2014

Selective altruism in collective games

We study the emergence of altruistic behaviour in collective games. In particular, we take into account Toral's version of collective Parrondo's paradoxical games, in which the redistribution of capital between agents, who can play different strategies, creates a positive trend of increasing capital. In this framework, we insert two categories of players, altruistic and selfish ones, and see how they interact and how their capital evolves. More in detail, we analyse the positive effects of altruistic behaviour, but we also point out how selfish players take advantage of that situation. The general result is that altruistic behaviour is discouraged, because selfish players get richer while altruistic ones get poorer. We also consider a smarter way of being altruistic, based on reputation, called "selective altruism", which prevents selfish players from taking advantage of altruistic ones. In this new situation it is altruism, and not selfishness, to be encouraged and stabilized. Finally, we introduce a mechanism of imitation between players and study how it influences the composition of the population of both altruistic and selfish players as a function of time for different initial conditions and network topologies adopted.

physics.soc-ph↗

arXiv2013

Reducing Financial Avalanches By Random Investments

Building on similarities between earthquakes and extreme financial events, we use a self-organized criticality-generating model to study herding and avalanche dynamics in financial markets. We consider a community of interacting investors, distributed on a small-world network, who bet on the bullish (increasing) or bearish (decreasing) behavior of the market which has been specified according to the S&P500 historical time series. Remarkably, we find that the size of herding-related avalanches in the community can be strongly reduced by the presence of a relatively small percentage of traders, randomly distributed inside the network, who adopt a random investment strategy. Our findings suggest a promising strategy to limit the size of financial bubbles and crashes. We also obtain that the resulting wealth distribution of all traders corresponds to the well-known Pareto power law, while the one of random traders is exponential. In other words, for technical traders, the risk of losses is much greater than the probability of gains compared to those of random traders.

q-fin.GN↗