| « 2012 | Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec |
1
vote
Dirk Helbing
posted by Matúš Medo (21 May 2013)
Despite all our great advances in science, technology and financial
innovations, many societies today are struggling with a financial, economic and
public spending crisis, over-regulation, and mass unemployment, as well as lack
of sustainability and innovation. Can we still rely on conventional economic
thinking or do we need a new approach?
<br />I argue that, as the complexity of socio-economic systems increases,
networked decision-making and bottom-up self-regulation will be more and more
important features. It will be explained why, besides the "homo economicus"
with strictly self-regarding preferences, natural selection has also created a
"homo socialis" with other-regarding preferences. While the "homo economicus"
optimizes the own prospects in separation, the decisions of the "homo socialis"
are self-determined, but interconnected, a fact that may be characterized by
the term "networked minds". Notably, the "homo socialis" manages to earn higher
payoffs than the "homo socialis".
<br />I show that the "homo economicus" and the "homo socialis" imply a different
kind of dynamics and distinct aggregate outcomes. Therefore, next to the
traditional economics for the "homo economicus" ("economics 1.0"), a
complementary theory must be developed for the "homo socialis". This economic
theory might be called "economics 2.0" or "socionomics". The names are
justified, because the Web 2.0 is currently promoting a transition to a new
market organization, which benefits from social media platforms and could be
characterized as "participatory market society". To thrive, the "homo socialis"
requires suitable institutional settings such a particular kinds of reputation
systems, which will be sketched in this paper. I also propose a new kind of
money, so-called "qualified money", which may overcome some of the problems of
our current financial system.
1
vote
Walter Quattrociocchi, Guido Caldarelli, Antonio Scala
posted by Matúš Medo (21 May 2013)
We introduce the concept of self-healing in the field of complex networks.
Obvious applications range from infrastructural to technological networks. By
exploiting the presence of redundant links in recovering the connectivity of
the system, we introduce self-healing capabilities through the application of
distributed communication protocols granting the "smartness" of the system. We
analyze the interplay between redundancies and smart reconfiguration protocols
in improving the resilience of networked infrastructures to multiple failures;
in particular, we measure the fraction of nodes still served for increasing
levels of network damages. We study the effects of different connectivity
patterns (planar square-grids, small-world, scale-free networks) on the healing
performances. The study of small-world topologies shows us that the
introduction of some long-range connections in the planar grids greatly
enhances the resilience to multiple failures giving results comparable to the
most resilient (but less realistic) scale-free structures.
1
vote
Giovanni Luca Ciampaglia
posted by Matúš Medo (21 May 2013)
Simulation with agent-based models is increasingly used in the study of
complex socio-technical systems and in social simulation in general. This
paradigm offers a number of attractive features, namely the possibility of
modeling emergent phenomena within large populations. As a consequence, often
the quantity in need of calibration may be a distribution over the population
whose relation with the parameters of the model is analytically intractable.
Nevertheless, we can simulate. In this paper we present a simulation-based
framework for the calibration of agent-based models with distributional output
based on indirect inference. We illustrate our method step by step on a model
of norm emergence in an online community of peer production, using data from
three large Wikipedia communities. Model fit and diagnostics are discussed.
1
vote
Pablo Piedrahíta, Javier Borge-Holthoefer, Yamir Moreno, Alex Arenas
posted by Matúš Medo (21 May 2013)
The ability to understand and eventually predict the emergence of information
and activation cascades in social networks is core to complex socio-technical
systems research. However, the complexity of social interactions makes this a
challenging enterprise. Previous works on cascade models assume that the
emergence of this collective phenomenon is related to the activity observed in
the local neighborhood of individuals, but do not consider what determines the
willingness to spread information in a time-varying process. Here we present a
mechanistic model that accounts for the temporal evolution of the individual
state in a simplified setup. We model the activity of the individuals as a
complex network of interacting integrate-and-fire oscillators. The model
reproduces the statistical characteristics of the cascades in real systems, and
provides a framework to study time-evolution of cascades in a state-dependent
activity scenario.
1
vote
James P. Gleeson, Jonathan A. Ward, Kevin P. O'Sullivan, William T. Lee
posted by Matúš Medo (21 May 2013)
Heavy-tailed distributions of meme popularity occur naturally in a model of
meme diffusion on social networks. Competition between multiple memes for the
limited resource of user attention is identified as the mechanism that poises
the system at criticality. The popularity growth of each meme is described by a
critical branching process, and asymptotic analysis predicts power-law
distributions of popularity with very heavy tails (exponent $\alpha<2$, unlike
preferential-attachment models), similar to those seen in empirical data.
1
vote
Egmont Kakarot-Handtke
posted by Egmont Kakarot-Handtke (21 May 2013)
This paper provides a substantial reconceptualization of the serial clearing of the product market on the basis of structural axioms. The change of premises is required simply because from the accustomed premises only the accustomed conclusions can be derived and these are known to be inapplicable in the real world. This holds in particular for the still popular idea that the working of a market can be described in terms of the triad demand function–supply function–equilibrium. Structural axiomatization provides the complete and consistent picture of interrelated product market events.
1
vote
Tijana Radivojević, Jonatha Anselmi, Enrico Scalas
posted by Matúš Medo (16 May 2013)
We study a phenomenological model for the continuous double auction,
equivalent to two independent $M/M/1$ queues. The continuous double auction
defines a continuous-time random walk for trade prices. The conditions for
ergodicity of the auction are derived and, as a consequence, three possible
regimes in the behavior of prices and logarithmic returns are observed. In the
ergodic regime, prices are unstable and one can observe an intermittent
behavior in the logarithmic returns. On the contrary, non-ergodicity triggers
stability of prices, even if two different regimes can be seen.
1
vote
Yuichi Ikeda, Hideaki Aoyama, Hiroshi Iyetomi, Hiroshi Yoshikawa
posted by Matúš Medo (16 May 2013)
We have analyzed the Indices of Industrial Production (Seasonal Adjustment
Index) for a long period of 240 months (January 1988 to December 2007) to
develop a deeper understanding of the economic shocks. The angular frequencies
estimated using the Hilbert transformation, are almost identical for the 16
industrial sectors. Moreover, the partial phase locking was observed for the 16
sectors. These are the direct evidence of the synchronization in the Japanese
business cycle. We also showed that the information of the economic shock is
carried by the phase time-series. The common shock and individual shocks are
separated using phase time-series. The former dominates the economic shock in
all of 1992, 1998 and 2001. The obtained results suggest that the business
cycle may be described as a dynamics of the coupled limit-cycle oscillators
exposed to the common shocks and random individual shocks.
2
votes
Marco Zamparo, Fulvio Baldovin, Michele Caraglio, Attilio L. Stella
posted by Matúš Medo (16 May 2013)
We present and discuss a stochastic model of financial assets dynamics based
on the idea of an inverse renormalization group strategy. With this strategy we
construct the multivariate distributions of elementary returns based on the
scaling with time of the probability density of their aggregates. In its
simplest version the model is the product of an endogenous auto-regressive
component and a random rescaling factor embodying exogenous influences.
Mathematical properties like increments' stationarity and ergodicity can be
proven. Thanks to the relatively low number of parameters, model calibration
can be conveniently based on a method of moments, as exemplified in the case of
historical data of the S&P500 index. The calibrated model accounts very well
for many stylized facts, like volatility clustering, power law decay of the
volatility autocorrelation function, and multiscaling with time of the
aggregated return distribution. In agreement with empirical evidence in
finance, the dynamics is not invariant under time reversal and, with suitable
generalizations, skewness of the return distribution and leverage effects can
be included. The analytical tractability of the model opens interesting
perspectives for applications, for instance in terms of obtaining closed
formulas for derivative pricing. Further important features are: The
possibility of making contact, in certain limits, with auto-regressive models
widely used in finance; The possibility of partially resolving the endogenous
and exogenous components of the volatility, with consistent results when
applied to historical series.
1
vote
L C G Rogers, Pawel Zaczkowski
posted by Matúš Medo (16 May 2013)
This paper sets up a methodology for approximately solving optimal investment
problems using duality methods combined with Monte Carlo simulations. In
particular, we show how to tackle high dimensional problems in incomplete
markets, where traditional methods fail due to the curse of dimensionality.
1
vote
Rémi Louf, Pablo Jensen, Marc Barthelemy
posted by Matúš Medo (16 May 2013)
One of the most important features of spatial networks such as transportation
networks, power grids, Internet, neural networks, is the existence of a cost
associated with the length of links. Such a cost has a profound influence on
the global structure of these networks which usually display a hierarchical
spatial organization. The link between local constraints and large-scale
structure is however not elucidated and we introduce here a generic model for
the growth of spatial networks based on the general concept of cost benefit
analysis. This model depends essentially on one single scale and produces a
family of networks which range from the star-graph to the minimum spanning tree
and which are characterised by a continuously varying exponent. We show that
spatial hierarchy emerges naturally, with structures composed of various hubs
controlling geographically separated service areas, and appears as a
large-scale consequence of local cost-benefit considerations. Our model thus
provides the first building blocks for a better understanding of the evolution
of spatial networks and their properties. We also find that, surprisingly, the
average detour is minimal in the intermediate regime, as a result of a large
diversity in link lengths. Finally, we estimate the important parameters for
various world railway networks and find that --remarkably-- they all fall in
this intermediate regime, suggesting that spatial hierarchy is a crucial
feature for these systems and probably possesses an important evolutionary
advantage.
1
vote
Tetsuya Takaishi, Ting Ting Chen, Zeyu Zheng
posted by Matúš Medo (16 May 2013)
We analyze realized volatilities constructed using high-frequency stock data
on the Tokyo Stock Exchange. In order to avoid non-trading hours issue in
volatility calculations we define two realized volatilities calculated
separately in the two trading sessions of the Tokyo Stock Exchange, i.e.
morning and afternoon sessions. After calculating the realized volatilities at
various sampling frequencies we evaluate the bias from the microstructure noise
as a function of sampling frequency. Taking into account of the bias to
realized volatility we examine returns standardized by realized volatilities
and confirm that price returns on the Tokyo Stock Exchange are described
approximately by Gaussian time series with time-varying volatility, i.e.
consistent with a mixture of distributions hypothesis.
1
vote
Tetsuya Takaishi
posted by Matúš Medo (16 May 2013)
The stochastic volatility model is one of volatility models which infer
latent volatility of asset returns. The Bayesian inference of the stochastic
volatility (SV) model is performed by the hybrid Monte Carlo (HMC) algorithm
which is superior to other Markov Chain Monte Carlo methods in sampling
volatility variables. We perform the HMC simulations of the SV model for two
liquid stock returns traded on the Tokyo Stock Exchange and measure the
volatilities of those stock returns. Then we calculate the accuracy of the
volatility measurement using the realized volatility as a proxy of the true
volatility and compare the SV model with the GARCH model which is one of other
volatility models. Using the accuracy calculated with the realized volatility
we find that empirically the SV model performs better than the GARCH model.
1
vote
Ovidiu Racorean
posted by Ovidiu Racorean (16 May 2013)
The question on the title came through my mind one day as I keep in one hand a paper in nuclear physics and in the other hand a paper in finance and surprisingly conclude that the same formula appear in both articles*. Phenomena from apparently completely different field of research were solved with the help of same equation. Things are getting even weirder saying that the formula I was talking about is the time-independent Schrodinger equation.
1
vote
Anirban Chakraborti, Damien Challet, Arnab Chatterjee, Matteo Marsili, Yi-Cheng Zhang, Bikas K. Chak
posted by Matúš Medo (10 May 2013)
Demand outstrips available resources in most situations, which gives rise to
competition, interaction and learning. In this article, we review a broad
spectrum of multi-agent models of competition and the methods used to
understand them analytically. We emphasize the power of concepts and tools from
statistical mechanics to understand and explain fully collective phenomena such
as phase transitions and long memory, and the mapping between agent
heterogeneity and physical disorder. As these methods can be applied to any
large-scale model made up of heterogeneous adaptive agent with non-linear
interaction, they provide a prospective unifying paradigm for many scientific
disciplines.
1
vote
Jiri Kukacka, Jozef Barunik
posted by Matúš Medo (10 May 2013)
The main aim of this work is to incorporate selected findings from
behavioural finance into a Heterogeneous Agent Model using the Brock and Hommes
(1998) framework. Behavioural patterns are injected into an asset pricing
framework through the so-called `Break Point Date', which allows us to examine
their direct impact. In particular, we analyse the dynamics of the model around
the behavioural break. Price behaviour of 30 Dow Jones Industrial Average
constituents covering five particularly turbulent U.S. stock market periods
reveals interesting pattern in this aspect. To replicate it, we apply numerical
analysis using the Heterogeneous Agent Model extended with the selected
findings from behavioural finance: herding, overconfidence, and market
sentiment. We show that these behavioural breaks can be well modelled via the
Heterogeneous Agent Model framework and they extend the original model
considerably. Various modifications lead to significantly different results and
model with behavioural breaks is also able to partially replicate price
behaviour found in the data during turbulent stock market periods.
1
vote
Kang Liu, N. Lubbers, W. Klein, J. Tobochnik, B. Boghosian, Harvey Gould
posted by Matúš Medo (10 May 2013)
We investigate the relation between economic growth and equality in a
modified version of the agent-based asset exchange model (AEM). The modified
model is a driven system that for a range of parameter space is effectively
ergodic in the limit of an infinite system. We find that the belief that "a
rising tide lifts all boats" does not always apply, but the effect of growth on
the wealth distribution depends on the nature of the growth. In particular, we
find that the rate of growth, the way the growth is distributed, and the
percentage of wealth exchange determine the degree of equality. We find strong
numerical evidence that there is a phase transition in the modified model, and
for a part of parameter space the modified AEM acts like a geometric random
walk.
1
vote
Coco Krumme, Alejandro Llorente, Manuel Cebrián, Alex, Pentland, Esteban Moro
posted by Matúš Medo (10 May 2013)
We consider hundreds of thousands of individual economic transactions to ask:
how predictable are consumers in their merchant visitation patterns? Our
results suggest that, in the long-run, much of our seemingly elective activity
is actually highly predictable. Notwithstanding a wide range of individual
preferences, shoppers share regularities in how they visit merchant locations
over time. Yet while aggregate behavior is largely predictable, the
interleaving of shopping events introduces important stochastic elements at
short time scales. These short- and long-scale patterns suggest a theoretical
upper bound on predictability, and describe the accuracy of a Markov model in
predicting a person's next location. We incorporate population-level transition
probabilities in the predictive models, and find that in many cases these
improve accuracy. While our results point to the elusiveness of precise
predictions about where a person will go next, they suggest the existence, at
large time-scales, of regularities across the population.
1
vote
Lazaros K. Gallos, Fabricio Q. Potiguar, José S. Andrade Jr., Hernan A. Makse
posted by Matúš Medo (10 May 2013)
We study a subset of the movie collaboration network, imdb.com, where only
adult movies are included. We show that there are many benefits in using such a
network, which can serve as a prototype for studying social interactions. We
find that the strength of links, i.e., how many times two actors have
collaborated with each other, is an important factor that can significantly
influence the network topology. We see that when we link all actors in the same
movie with each other, the network becomes small-world, lacking a proper
modular structure. On the other hand, by imposing a threshold on the minimum
number of links two actors should have to be in our studied subset, the network
topology becomes naturally fractal. This occurs due to a large number of
meaningless links, namely, links connecting actors that did not actually
interact. We focus our analysis on the fractal and modular properties of this
resulting network, and show that the renormalization group analysis can
characterize the self-similar structure of these networks.
1
vote
Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G. Tartakovsky
posted by Matúš Medo (10 May 2013)
The focus of this work is on developing probabilistic models for user
activity in social networks by incorporating the social network influence as
perceived by the user. For this, we propose a coupled Hidden Markov Model,
where each user's activity evolves according to a Markov chain with a hidden
state that is influenced by the collective activity of the friends of the user.
We develop generalized Baum-Welch and Viterbi algorithms for model parameter
learning and state estimation for the proposed framework. We then validate the
proposed model using a significant corpus of user activity on Twitter. Our
numerical studies show that with sufficient observations to ensure accurate
model learning, the proposed framework explains the observed data better than
either a renewal process-based model or a conventional uncoupled Hidden Markov
Model. We also demonstrate the utility of the proposed approach in predicting
the time to the next tweet. Finally, clustering in the model parameter space is
shown to result in distinct natural clusters of users characterized by the
interaction dynamic between a user and his network.
1
vote
Yuri Biondi
posted by Yuri Biondi (9 May 2013)
This paper develops an agent-based model to examine the emergent dynamic properties of share market price formation over time, with a view on financial market stability under alternative accounting regimes. In the model, individual heterogeneous investors interact with each other and with institutional devices which are an accounting system (related to the business firm) and a price system (related to the Share Exchange). These interactions provide mechanisms for transmission through which firm-specific (accounting signal) and market-driven (aggregate price) drivers can act. A baseline simulation analysis assesses the financial market stability under three alternative accounting designs, namely two kinds of historical cost accounting regime and one kind of fair value (mark-to-market) accounting regime. The former prove to better stabilize the financial system for market volatility and exuberance in perfectly balanced conditions between speculative and fundamentalist beliefs and intentions. An evolutionary analysis is then developed by varying the relative degree of speculative attitudes. Historical cost accounting regimes further prove to make the financial system more resilient to speculative waves occurring at inter-individual level. Baseline findings are further corroborated through experimental analysis in ten artificial financial systems. This mathematical institutional economic analysis has general implications for both designing accounting systems aimed at enhancing financial market stability and preventing pro-cyclicality, and the study of accounting information process in the formation of share market prices over time.
1
vote
Dirk Helbing
posted by Matúš Medo (2 May 2013)
The increasing interdependencies between the world’s technological, socio-economic, and environmental systems have the potential to create global catastrophic risks. We may have to re-design many global networks, otherwise they could turn into "global time bombs".
2
votes
Dirk Helbing, Alan Kirman
posted by Matúš Medo (2 May 2013)
In this paper we argue that if we want to find a more satisfactory approach to tackling the major socio-economic problems we are facing, we need to thoroughly rethink the basic assumptions of macroeconomics and financial theory. Making minor modifications to the standard models to remove "imperfections" is not enough, the whole framework needs to be revisited.
2
votes
Egmont Kakarot-Handtke
posted by Egmont Kakarot-Handtke (1 May 2013)
Economists are fond of the physicists’ powerful tools. As a popular mindset
Toolism is as old as economics but the transplants failed to produce the same
successes as in their aboriginal environment. Economists therefore looked
more and more to the math department for inspiration. Now the tide turns
again. The ongoing crisis discredits standard economics and offers the chance
for a comeback. Modern econophysics commands the most powerful tools
and argues that there are many occasions for their application. The present
paper argues that it is not a change of tools that is most urgently needed but a
paradigm change.
1
vote
A. Gareche, G. Disdier, J. Kockelkoren, J.-P. Bouchaud
posted by Matúš Medo (1 May 2013)
Motivated by empirical data, we develop a statistical description of the
queue dynamics for large tick assets based on a two-dimensional Fokker-Planck
(diffusion) equation, that explicitly includes state dependence, i.e. the fact
that the drift and diffusion depends on the volume present on both sides of the
spread. "Jump" events, corresponding to sudden changes of the best limit price,
must also be included as birth-death terms in the Fokker-Planck equation. All
quantities involved in the equation can be calibrated using high-frequency data
on best quotes. One of our central finding is the the dynamical process is
approximately scale invariant, i.e., the only relevant variable is the ratio of
the current volume in the queue to its average value. While the latter shows
intraday seasonalities and strong variability across stocks and time periods,
the dynamics of the rescaled volumes is universal. In terms of rescaled
volumes, we found that the drift has a complex two-dimensional structure, which
is a sum of a gradient contribution and a rotational contribution, both stable
across stocks and time. This drift term is entirely responsible for the
dynamical correlations between the ask queue and the bid queue.
1
vote
Karim Azizi, Nicolas Canry, Jean-Bernard Chatelain, Bruno Tinel
posted by Matúš Medo (1 May 2013)
This paper investigates the relevance of the No-Ponzi game condition for
public debt (i.e. the public debt growth rate has to be lower than the real
interest rate, a necessary assumption for Ricardian equivalence) and of the
transversality condition for the GDP growth rate (i.e. the GDP growth rate has
to be lower than the real interest rate). First, on the unbalanced panel of 21
countries from 1961 to 2010 available in OECD database, those two conditions
were simultaneously validated only for 29% of the cases under examination.
Second, those two conditions were more frequent in the 1980s and the 1990s when
monetary policies were more restrictive. Third, in tune with the Keynesian
view, when the real interest rate is higher than the GDP growth, it corresponds
to 75% of the cases of the increases of the debt/GDP ratio but to only 43% of
the cases of the decreases of the debt/GDP ratio (fiscal consolidations).
1
vote
David Kempe, Jon Kleinberg, Sigal Oren, Aleksandrs Slivkins
posted by Matúš Medo (1 May 2013)
One of the fundamental principles driving diversity or homogeneity in domains
such as cultural differentiation, political affiliation, and product adoption
is the tension between two forces: influence (the tendency of people to become
similar to others they interact with) and selection (the tendency to be
affected most by the behavior of others who are already similar). Influence
tends to promote homogeneity within a society, while selection frequently
causes fragmentation. When both forces are in effect simultaneously, it becomes
an interesting question to analyze which societal outcomes should be expected.
<br />In order to study the joint effects of these forces more formally, we analyze
a natural model built upon active lines of work in political opinion formation,
cultural diversity, and language evolution. Our model posits an arbitrary graph
structure describing which "types" of people can influence one another: this
captures effects based on the fact that people are only influenced by
sufficiently similar interaction partners. In a generalization of the model, we
introduce another graph structure describing which types of people even so much
as come in contact with each other. These restrictions on interaction patterns
can significantly alter the dynamics of the process at the population level.
<br />For the basic version of the model, in which all individuals come in contact
with all others, we achieve an essentially complete characterization of
(stable) equilibrium outcomes and prove convergence from all starting states.
For the other extreme case, in which individuals only come in contact with
others who have the potential to influence them, the underlying process is
significantly more complicated; nevertheless we present an analysis for certain
graph structures.
1
vote
T. Hartonen, M. J. Alava
posted by Matúš Medo (25 April 2013)
The advancement of various fields of science depends on the actions of
individual scientists via the peer review process. The referees' work patterns
and stochastic nature of decision making both relate to the particular features
of refereeing and to the universal aspects of human behavior. Here, we show
that the time a referee takes to write a report on a scientific manuscript
depends on the final verdict. The data is compared to a model, where the review
takes place in an ongoing competition of completing an important composite task
with a large number of concurrent ones - a Deadline -effect. In peer review
human decision making and task completion combine both long-range
predictability and stochastic variation due to a large degree of ever-changing
external "friction".
1
vote
Young-Ho Eom, Klaus M. Frahm, András Benczúr, Dima L. Shepelyansky
posted by Matúš Medo (25 April 2013)
We study the time evolution of ranking and spectral properties of the Google
matrix of English Wikipedia hyperlink network during years 2003 - 2011. The
statistical properties of ranking of Wikipedia articles via PageRank and
CheiRank probabilities, as well as the matrix spectrum, are shown to be
stabilized for 2007 - 2011. A special emphasis is done on ranking of Wikipedia
personalities and universities. We show that PageRank selection is dominated by
politicians while 2DRank, which combines PageRank and CheiRank, gives more
accent on personalities of arts. The Wikipedia PageRank of universities
recovers 80 percents of top universities of Shanghai ranking during the
considered time period.
1
vote
Gabriel Frahm
posted by Matúš Medo (19 April 2013)
The following fundamental properties are proved to be true if a financial
market is exhaustive: (i) Every event which is measurable by the price history
at time T is independent of G_t conditional on the current price history H_t,
where G_t is a superset of H_t, (ii) every event which is measurable by G_t is
independent of H_T conditional on H_t. These properties are especially useful
for asset valuation, portfolio optimization and risk management. An exhaustive
market with respect to {F_t} is free of dominance and there are no free lunches
with vanishing risk under {F_t}. Moreover, it is complete with respect to every
information flow which is contained in {F_t} and the growth-optimal portfolio
at time t is only determined by the past asset prices. This means any other
information which is contained in F_t and available to the investor at time t
is irrelevant.
1
vote
Cornelia Metzig, Mirta B. Gordon
posted by Matúš Medo (19 April 2013)
We introduce a simple agent-based model which allows us to analyze three
stylized facts: a fat-tailed size distribution of companies, a `tent-shaped'
growth rate distribution, the scaling relation of the growth rate variance with
firm size, and the causality between them. This is achieved under the simple
hypothesis that firms compete for a scarce quantity (either aggregate demand or
workforce) which is allocated probabilistically. The model allows us to relate
size and growth rate distributions. We compare the results of our model to
simulations with other scaling relationships, and to similar models and relate
it to existing theory.
1
vote
Thilo A. Schmitt, Desislava Chetalova, Rudi Schäfer, Thomas Guhr
posted by Matúš Medo (19 April 2013)
Financial markets are prominent examples for highly non-stationary systems.
Sample averaged observables such as variances and correlation coefficients
strongly depend on the time window in which they are evaluated. This implies
severe limitations for approaches in the spirit of standard equilibrium
statistical mechanics and thermodynamics. Nevertheless, we show that there are
similar generic features which we uncover in the empirical return distributions
for whole markets. We explain our findings by setting up a random matrix model.
1
vote
Lev Muchnik, Sen Pei, Lucas C. Parra, Saulo D.S. Reis, Jose S. Andrade, Jr., Shlomo Havlin, Hernan A
posted by Matúš Medo (19 April 2013)
The probability distribution of number of ties of an individual in a social
network follows a scale-free power-law. However, how this distribution arises
has not been conclusively demonstrated in direct analyses of people's actions
in social networks. Here, we perform a causal inference analysis and find an
underlying cause for this phenomenon. Our analysis indicates that heavy-tailed
degree distribution is causally determined by similarly skewed distribution of
human activity. Specifically, the degree of an individual is entirely random -
following a "maximum entropy attachment" model - except for its mean value
which depends deterministically on the volume of the users' activity. This
relation cannot be explained by interactive models, like preferential
attachment, since the observed actions are not likely to be caused by
interactions with other people.
1
vote
Danai Koutra, Joshua T. Vogelstein, Christos Faloutsos
posted by Matúš Medo (19 April 2013)
How much did a network change since yesterday? How different is the wiring
between Bob's brain (a left-handed male) and Alice's brain (a right-handed
female)? Graph similarity with known node correspondence, i.e. the detection of
changes in the connectivity of graphs, arises in numerous settings. In this
work, we formally state the axioms and desired properties of the graph
similarity functions, and evaluate when state-of-the-art methods fail to detect
crucial connectivity changes in graphs. We propose DeltaCon, a principled,
intuitive, and scalable algorithm that assesses the similarity between two
graphs on the same nodes (e.g. employees of a company, customers of a mobile
carrier). Experiments on various synthetic and real graphs showcase the
advantages of our method over existing similarity measures. Finally, we employ
DeltaCon to real applications: (a) we classify people to groups of high and low
creativity based on their brain connectivity graphs, and (b) do temporal
anomaly detection in the who-emails-whom Enron graph.
1
vote
Luo-Luo Jiang, Matjaz Perc, Attila Szolnoki
posted by Matúš Medo (19 April 2013)
Punishment may deter antisocial behavior. Yet to punish is costly, and the
costs often do not offset the gains that are due to elevated levels of
cooperation. However, the effectiveness of punishment depends not only on how
costly it is, but also on the circumstances defining the social dilemma. Using
the snowdrift game as the basis, we have conducted a series of economic
experiments to determine whether severe punishment is more effective than mild
punishment. We have observed that severe punishment is not necessarily more
effective, even if the cost of punishment is identical in both cases. The
benefits of severe punishment become evident only under extremely adverse
conditions, when to cooperate is highly improbable in the absence of sanctions.
If cooperation is likely, mild punishment is not less effective and leads to
higher average payoffs, and is thus the much preferred alternative. Presented
results suggest that the positive effects of punishment stem not only from
imposed fines, but may also have a psychological background. Small fines can do
wonders in motivating us to chose cooperation over defection, but without the
paralyzing effect that may be brought about by large fines. The later should be
utilized only when absolutely necessary.
2
votes
A. Ferscha, K. Farrahi, J. van denHoven, D. Hales, A. Nowak, P. Lukowicz, D. Helbing
posted by Matúš Medo (11 April 2013)
Modern ICT (Information and Communication Technology) has developed a vision
where the "computer" is no longer associated with the concept of a single
device or a network of devices, but rather the entirety of situated services
originating in a digital world, which are perceived through the physical world.
It is observed that services with explicit user input and output are becoming
to be replaced by a computing landscape sensing the physical world via a huge
variety of sensors, and controlling it via a plethora of actuators. The nature
and appearance of computing devices is changing to be hidden in the fabric of
everyday life, invisibly networked, and omnipresent, with applications greatly
being based on the notions of context and knowledge. Interaction with such
globe spanning, modern ICT systems will presumably be more implicit, at the
periphery of human attention, rather than explicit, i.e. at the focus of human
attention. Socio-inspired ICT assumes that future, globe scale ICT systems
should be viewed as social systems. Such a view challenges research to identify
and formalize the principles of interaction and adaptation in social systems,
so as to be able to ground future ICT systems on those principles. This
position paper therefore is concerned with the intersection of social behaviour
and modern ICT, creating or recreating social conventions and social contexts
through the use of pervasive, globe-spanning, omnipresent and participative
ICT.
1
vote
Christian Doerr, Norbert Blenn, Siyu Tang, Piet Van Mieghem
posted by Matúš Medo (11 April 2013)
The key feature of online social networks (OSN) is the ability of users to
become active, make friends and interact via comments, videos or messages with
those around them. This social interaction is typically perceived as critical
to the proper functioning of these platforms; therefore, a significant share of
OSN research in the recent past has investigated the characteristics and
importance of these social links, studying the networks' friendship relations
through their topological properties, the structure of the resulting
communities and identifying the role and importance of individual members
within these networks.
<br />In this paper, we present results from a multi-year study of the online
social network Digg.com, indicating that the importance of friends and the
friend network in the propagation of information is less than originally
perceived. While we do note that users form and maintain a social structure
along which information is exchanged, the importance of these links and their
contribution is very low: Users with even a nearly identical overlap in
interests react on average only with a probability of 2% to information
propagated and received from friends. Furthermore, in only about 50% of stories
that became popular from the entire body of 10 million news we find evidence
that the social ties among users were a critical ingredient to the successful
spread. Our findings indicate the presence of previously unconsidered factors,
the temporal alignment between user activities and the existence of additional
logical relationships beyond the topology of the social graph, that are able to
drive and steer the dynamics of such OSNs.
2
votes
Anna Carbone, Marco Ajmone-Marsan, Kay W. Axhausen, Michael Batty, Marcelo Masera, Erich Rome
posted by Matúš Medo (11 April 2013)
"In the next century, planet earth will don an electronic skin. It will use
the Internet as a scaffold to support and transmit its sensations. This skin is
already being stitched together. It consists of millions of embedded electronic
measuring devices: thermostats, pressure gauges, pollution detectors, cameras,
microphones, glucose sensors, EKGs, electroencephalographs. These will probe
and monitor cities and endangered species, the atmosphere, our ships, highways
and fleets of trucks, our conversations, our bodies--even our dreams ....What
will the earth's new skin permit us to feel? How will we use its surges of
sensation? For several years--maybe for a decade--there will be no central
nervous system to manage this vast signaling network. Certainly there will be
no central intelligence...some qualities of self-awareness will emerge once the
Net is sensually enhanced. Sensuality is only one force pushing the Net toward
intelligence". These statements are quoted by an interview by Cherry Murray,
Dean of the Harvard School of Engineering and Applied Sciences and Professor of
Physics. It is interesting to outline the timeliness and highly predicting
power of these statements. In particular, we would like to point to the
relevance of the question "What will the earth's new skin permit us to feel?"
to the work we are going to discuss in this paper. There are many additional
compelling questions, as for example: "How can the electronic earth's skin be
made more resilient?"; "How can the earth's electronic skin be improved to
better satisfy the need of our society?";"What can the science of complex
systems contribute to this endeavour?"
1
vote
Dirk Helbing
posted by Matúš Medo (11 April 2013)
The FuturICT project is a response to the European Flagship Call in the Area
of Future and Emerging Technologies, which is planning to spend 1 billion EUR
on each of two flagship projects over a period of 10 years. FuturICT seeks to
create an open, global but decentralized, democratically controlled information
platform that will use online data and real-time measurements together with
novel theoretical models and experimental methods to achieve a paradigm shift
in our understanding of today's strongly interdependent and complex world and
make our techno-socio-economic systems more flexible, adaptive, resilient,
sustainable, and livable through a participatory approach.
1
vote
Thomas Grund, Christian Waloszek, Dirk Helbing
posted by Matúš Medo (11 April 2013)
Biological competition is widely believed to result in the evolution of
selfish preferences. The related concept of the `homo economicus' is at the
core of mainstream economics. However, there is also experimental and empirical
evidence for other-regarding preferences. Here we present a theory that
explains both, self-regarding and other-regarding preferences. Assuming
conditions promoting non-cooperative behaviour, we demonstrate that
intergenerational migration determines whether evolutionary competition results
in a `homo economicus' (showing self-regarding preferences) or a `homo
socialis' (having other-regarding preferences). Our model assumes spatially
interacting agents playing prisoner's dilemmas, who inherit a trait determining
`friendliness', but mutations tend to undermine it. Reproduction is ruled by
fitness-based selection without a cultural modification of reproduction rates.
Our model calls for a complementary economic theory for `networked minds' (the
`homo socialis') and lays the foundations for an evolutionarily grounded theory
of other-regarding agents, explaining individually different utility functions
as well as conditional cooperation.
1
vote
Ivan O. Kitov
posted by Ivan Kitov (9 April 2013)
A microeconomic model is developed, which accurately predicts the shape of
personal income distribution (PID) in the United States and the evolution of
the shape over time. The underlying concept is borrowed from geo-mechanics and
thus can be considered as mechanics of income distribution. The model allows
the resolution of empirical and definitional problems associated with personal
income measurements. It also serves as a firm fundament for definitions of
income inequality as secondary derivatives from personal income distribution.
It is found that in relative terms the PID in the US has not been changing
since 1947. Effectively, the Gini coefficient has been almost constant during
the last 60 years, as reported by the Census Bureau.
1
vote
Ben D. Fulcher, Max A. Little, Nick S. Jones
posted by Matúš Medo (5 April 2013)
The process of collecting and organizing sets of observations represents a
common theme throughout the history of science. However, despite the ubiquity
of scientists measuring, recording, and analyzing the dynamics of different
processes, an extensive organization of scientific time-series data and
analysis methods has never been performed. Addressing this, annotated
collections of over 35 000 real-world and model-generated time series and over
9000 time-series analysis algorithms are analyzed in this work. We introduce
reduced representations of both time series, in terms of their properties
measured by diverse scientific methods, and of time-series analysis methods, in
terms of their behaviour on empirical time series, and use them to organize
these interdisciplinary resources. This new approach to comparing across
diverse scientific data and methods allows us to organize time-series datasets
automatically according to their properties, retrieve alternatives to
particular analysis methods developed in other scientific disciplines, and
automate the selection of useful methods for time-series classification and
regression tasks. The broad scientific utility of these tools is demonstrated
on datasets of electroencephalograms, self-affine time series, heart beat
intervals, speech signals, and others, in each case contributing novel analysis
techniques to the existing literature. Highly comparative techniques that
compare across an interdisciplinary literature can thus be used to guide more
focused research in time-series analysis for applications across the scientific
disciplines.
1
vote
Santo Fortunato, Michael Macy, Sidney Redner
posted by Matúš Medo (5 April 2013)
This editorial opens the special issues that the Journal of Statistical
Physics has dedicated to the growing field of statistical physics modeling of
social dynamics. The issues include contributions from physicists and social
scientists, with the goal of fostering a better communication between these two
communities.
1
vote
Filippo Radicchi, Claudio Castellano
posted by Matúš Medo (5 April 2013)
Citation numbers and other quantities derived from bibliographic databases
are becoming standard tools for the assessment of productivity and impact of
research activities. Though widely used, still their statistical properties
have not been well established so far. This is especially true in the case of
bibliometric indicators aimed at the evaluation of individual scholars, because
large-scale data sets are typically difficult to be retrieved. Here, we take
advantage of a recently introduced large bibliographic data set, Google Scholar
Citations, which collects the entire publication record of individual scholars.
We analyze the scientific profile of more than 30,000 researchers, and study
the relation between the h-index, the number of publications and the number of
citations of individual scientists. While the number of publications of a
scientist has a rather weak relation with his/her h-index, we find that the
h-index of a scientist is strongly correlated with the number of citations that
she/he has received so that the number of citations can be effectively be used
as a proxy of the h-index. Allowing for the h-index to depend on both the
number of citations and the number of publications, we find only a minor
improvement.
1
vote
Morgan R. Frank, Lewis Mitchell, Peter S. Dodds, Christopher M. Danforth
posted by Matúš Medo (5 April 2013)
The patterns of life exhibited by large populations have been described and
modeled both as a basic science exercise and for a range of applied goals such
as reducing automotive congestion, improving disaster response, and even
predicting the location of individuals. However, these studies previously had
limited access to conversation content, rendering changes in expression as a
function of movement invisible. In addition, they typically use the
communication between a mobile phone and its nearest antenna tower to infer
position, limiting the spatial resolution of the data to the geographical
region serviced by each cellphone tower. We use a collection of 37 million
geolocated tweets to characterize the movement patterns of 180,000 individuals,
taking advantage of several orders of magnitude of increased spatial accuracy
relative to previous work. Employing the recently developed sentiment analysis
instrument known as the \textit{hedonometer}, we characterize changes in word
usage as a function of movement, and find that expressed happiness increases
logarithmically with distance from an individual's average location.
1
vote
Saad Ahmad Khan, Ladislau Boloni
posted by Matúš Medo (3 April 2013)
We describe an agent-based simulation of a fictional (but feasible)
information trading business. The Gas Price Information Trader (GPIT) buys
information about real-time gas prices in a metropolitan area from drivers and
resells the information to drivers who need to refuel their vehicles.
<br />Our simulation uses real world geographic data, lifestyle-dependent driving
patterns and vehicle models to create an agent-based model of the drivers. We
use real world statistics of gas price fluctuation to create scenarios of
temporal and spatial distribution of gas prices. The price of the information
is determined on a case-by-case basis through a simple negotiation model. The
trader and the customers are adapting their negotiation strategies based on
their historical profits.
<br />We are interested in the general properties of the emerging information
market: the amount of realizable profit and its distribution between the trader
and customers, the business strategies necessary to keep the market operational
(such as promotional deals), the price elasticity of demand and the impact of
pricing strategies on the profit.
1
vote
Pietro Fodra, Mauricio Labadie
posted by Matúš Medo (3 April 2013)
In this paper we complete and extend our previous work on stochastic control
applied to high frequency market-making with inventory constraints and
directional bets. Our new model admits several state variables (e.g. market
spread, stochastic volatility and intensities of market orders) provided the
full system is Markov. The solution of the corresponding HJB equation is exact
in the case of zero inventory risk. The inventory risk enters into play in two
ways: a path-dependent penalty based on the volatility and a penalty at expiry
based on the market spread. We perform perturbation methods on the inventory
risk parameter and obtain explicitly the solution and its controls up to first
order. We also include transaction costs; we show that the spread of the
market-maker is widened to compensate the transaction costs, but the expected
gain per traded spread remains constant. We perform several numerical
simulations to assess the effect of the parameters on the PNL, showing in
particular how the directional bet and the inventory risk change the shape of
the PNL density. Finally, we extend our results to the case of multi-aset
market-making strategies; we show that the correct notion of inventory risk is
the L2-norm of the (multi-dimensional) inventory with respect to the inventory
penalties.
1
vote
Michal Brzezinski
posted by Matúš Medo (3 April 2013)
We use data on wealth of the richest persons taken from the "rich lists"
provided by business magazines like Forbes to verify if upper tails of wealth
distributions follow, as often claimed, a power-law behaviour. The data sets
used cover the world's richest persons over 1996-2012, the richest Americans
over 1988-2012, the richest Chinese over 2006-2012 and the richest Russians
over 2004-2011. Using a recently introduced comprehensive empirical methodology
for detecting power laws, which allows for testing goodness of fit as well as
for comparing the power-law model with rival distributions, we find that a
power-law model is consistent with data only in 35% of the analysed data sets.
Moreover, even if wealth data are consistent with the power-law model, usually
they are also consistent with some rivals like the log-normal or stretched
exponential distributions.
1
vote
Galen Sher, Pedro Vitoria
posted by Matúš Medo (3 April 2013)
Information theory provides ideas for conceptualising information and
measuring relationships between objects. It has found wide application in the
sciences, but economics and finance have made surprisingly little use of it. We
show that time series data can usefully be studied as information -- by noting
the relationship between statistical redundancy and dependence, we are able to
use the results of information theory to construct a test for joint dependence
of random variables. The test is in the same spirit of those developed by
Ryabko and Astola (2005, 2006b,a), but differs from these in that we add extra
randomness to the original stochatic process. It uses data compression to
estimate the entropy rate of a stochastic process, which allows it to measure
dependence among sets of random variables, as opposed to the existing
econometric literature that uses entropy and finds itself restricted to
pairwise tests of dependence. We show how serial dependence may be detected in
S&P500 and PSI20 stock returns over different sample periods and frequencies.
We apply the test to synthetic data to judge its ability to recover known
temporal dependence structures.
1
vote
Ben Klemens
posted by Matúš Medo (3 April 2013)
It is well known that the distribution of returns from various financial
instruments are leptokurtic, meaning that the distributions have "fatter tails"
than a Normal distribution, and have skew toward zero. This paper presents a
graceful micro-level explanation for such fat-tailed outcomes, using agents
whose private valuations have Normally-distributed errors, but whose utility
function includes a term for the percentage of others who also buy.
Latest blogs Post a blog
- PhD in Econophysics or Economics
by Maurizio (4:54 20 May 2013) - Econophysics journals
by dijiang (1:03 3 May 2013) - Econophysics journals
by dijiang (1:02 3 May 2013) - Econophysics journals
by dijiang (1:02 3 May 2013) - Econophysics journals
by dijiang (1:02 3 May 2013)
Popular papers 
-
Are financial markets just another aspect of Nature? (32 downloads)
-
Scaling symmetry, renormalization, and time series modeling (19 downloads)
-
Monte Carlo approximation to optimal investment (14 downloads)
-
Rethinking Economics Using Complexity Theory (13 downloads)
Active users
Recent comments
-
Complexity by M.Mitchell Waldrop ...
by dipakhore (15 May) -
Dirk, here are 2 of my issues wit...
by Wlawless (5 May) -
I`m new to the site. I`m working...
by bilburns (5 May) -
- the paradigm of the homo econom...
by Joe McCauley (30 March) -
From: Eduardo Martín Pérez
Subj...
by FuturICT (5 March)
