114 research outputs found
Complexity in financial market. Modeling psychological behavior in agent-based models and order book models
No full textThe fundamental idea developed throughout this work is the introduction of new
metrics in Social Sciences (Economics, Finance, opinion dynamics, etc). The concept
of metric, that is the concept of measure, is usually neglected by mainstream
theories of Economics and Finance. Financial Markets are the natural starting
point of such an approach to Social Sciences because a systematic approach can
be undertaken and the methods of Physics has shown to be very effective. In fact
since a decade there exists a very huge amount of high frequency data from stock
exchanges which permit to perform experimental procedures as in Natural Sciences.
Financial markets appear as a perfect playground where models can be tested and
where repeatability of empirical evidences are well-established features differently
from, for instance, Macro-Economy and Micro-Economy. Thus Finance has been
the first point of contact for the interdisciplinary application of methods and tools
deriving from Physics and it has been also the starting point of this work.
We investigated the origin of the so-called Stylized Facts of financial markets (i.e.
the statistical properties of financial time series) in the framework of agent-based
models. We found that Stylized Facts can be interpreted as a finite size effect in
terms of the number of effectively independent agents (i.e. strategy) which results
to be a key variable to understand the self-organization of financial markets.
As a second issue we focused our attention on the order book dynamics both
from a theoretical and a data oriented point of view. We developed a zero intelligence
model in order to investigate the role of vanishing liquidity in the price
response to incoming orders. Within the framework of this model we have analyzed
the effect of the introduction of strategies pointing out that simple strategic
behaviors can explain bursts of intermittency and long memory effects. On the
other hand we quantitatively showed that there exists a feedback effect in markets
called self-fulfilling prophecy which is the mechanism through which technical trading
can exist and work. This feature is a very interesting quantitative evidence
of a self-reinforcement of agents’ belief. Last but not least nowadays we live in
a computerized and networked society where many of our actions leave a digital
trace and affect other people’s actions. This has lead to the emergence of a new
data-driven research field. In this work we highlighted how non financial data can
be used to track financial activity, in detail we investigate query log volumes, i.e.
the volumes of searches for a specific query done by users in a search engine, as a
proxy for trading volumes and we find that users’ activity on Yahoo! search engine
anticipates trading volume by one-two days.
Differently from Finance, Economics is far from being an ideal candidate to
export the methodology of Natural Sciences because of the lack of empirical data
since controlled (and repeatable) experiments are totally artificial while real experiments
are almost incontrollable and non repeatable due to a high degree of non
stationarity of economical systems. However, the application of method deriving
from complexity to the Economics of Growth is one of the more important achievement
of the work here developed. The basic idea is to study the network defined
by international trade flows and introduce a (non-monetary) metric to measure the
complexity and the competitiveness of countries’ productive system. In addition
we are able to define a metric for products’ quality which overcomes traditional
economic measure for the quality of products given in terms of hours of qualified
labour needed to produce a good. The method developed provides some impressive
results in predicting economical growth of countries and offers many opportunities
of improvements and generalizations
The heterogeneous dynamics of economic complexity
No full textWhat will be the growth of the Gross Domestic Product (GDP) or the competitiveness of China, United States, and Vietnam in the next 3, 5 or 10 years? Despite this kind of questions has a large societal impact and an extreme value for economic policy making, providing a scientific basis for economic predictability is still a very challenging problem. Recent results of a new branch—Economic Complexity—have set the basis for a framework to approach such a challenge and to provide new perspectives to cast economic prediction into the conceptual scheme of forecasting the evolution of a dynamical system as in the case of weather dynamics. We argue that a recently introduced non-monetary metrics for country competitiveness (fitness) allows for quantifying the hidden growth potential of countries by the means of the comparison of this measure for intangible assets with monetary figures, such as GDP per capita. This comparison defines the fitness-income plane where we observe that country dynamics presents strongly heterogeneous patterns of evolution. The flow in some zones is found to be laminar while in others a chaotic behavior is instead observed. These two regimes correspond to very different predictability features for the evolution of countries: in the former regime, we find strong predictable pattern while the latter scenario exhibits a very low predictability. In such a framework, regressions, the usual tool used in economics, are no more the appropriate strategy to deal with such a heterogeneous scenario and new concepts, borrowed from dynamical systems theory, are mandatory. We therefore propose a data-driven method—the selective predictability scheme—in which we adopt a strategy similar to the methods of analogues, firstly introduced by Lorenz, to assess future evolution of countries
Critical overview of agent-based models for economics
No full textWe present an overview of some representative Agent-Based Models in Economics. We discuss why and how Agent-Based Models represent an important step in order to explain the dynamics and the statistical properties of financial markets beyond the Classical Theory of Economics. We perform a schematic analysis of several models with respect to some specific key categories such as agents' strategies, price evolution, number of agents, etc. In the conclusive part of this review we address some open questions and future perspectives and highlight the conceptual importance of some usually neglected topics, such as non-stationarity and the self-organization of financial markets. ©2012 by Società Italiana di Fisica
There is More than a Power Law in Zipf
No full textThe largest cities, the most frequently used words, the income of the richest countries, and the most wealthy billionaires, can be all described in terms of Zipf's Law, a rank-size rule capturing the relation between the frequency of a set of objects or events and their size. It is assumed to be one of many manifestations of an underlying power law like Pareto's or Benford's, but contrary to popular belief, from a distribution of, say, city sizes and a simple random sampling, one does not obtain Zipf's law for the largest cities. This pathology is reflected in the fact that Zipf's Law has a functional form depending on the number of events N. This requires a fundamental property of the sample distribution which we call 'coherence' and it corresponds to a 'screening' between various elements of the set. We show how it should be accounted for when fitting Zipf's Law
Correction: The complex dynamics of products and its asymptotic properties.
No full text[This corrects the article DOI: 10.1371/journal.pone.0177360.]
A Network Analysis of Countries’ Export Flows: Firm Grounds for the Building Blocks of the Economy
No full textIn this paper we analyze the bipartite network of countries and products from UN data on country production. We define the country-country and product-product projected networks and introduce a novel method of filtering information based on elements’ similarity. As a result we find that country clustering reveals unexpected socio-geographic links among the most competing countries. On the same footings the products clustering can be efficiently used for a bottom-up classification of produced goods. Furthermore we mathematically reformulate the “reflections method” introduced by Hidalgo and Hausmann as a fixpoint problem; such formulation highlights some conceptual weaknesses of the approach. To overcome such an issue, we introduce an alternative methodology (based on biased Markov chains) that allows to rank countries in a conceptually consistent way. Our analysis uncovers a strong non-linear interaction between the diversification of a country and the ubiquity of its products, thus suggesting the possible need of moving towards more efficient and direct non-linear fixpoint algorithms to rank countries and products in the global market.</p
Minimal agent based model for financial markets I
No full text89.65.Gh Economics; econophysics, financial markets, business and management, 89.75.-k Complex systems,
How the Taxonomy of Products Drives the Economic Development of Countries
No full textWe introduce an algorithm able to reconstruct the relevant network structure on which the time evolution of country-product bipartite networks takes place. The significant links are obtained by selecting the largest values of the projected matrix. We first perform a number of tests of this filtering procedure on synthetic cases and a toy model. Then we analyze the bipartite network constituted by countries and exported products, using two databases for a total of almost 50 years. It is then possible to build a hierarchically directed network, in which the taxonomy of products emerges in a natural way. We study the influence of the structure of this taxonomy network on countries' development; in particular, guided by an example taken from the industrialization of South Korea, we link the structure of the taxonomy network to the empirical temporal connections between product activations, finding that the most relevant edges for countries' development are the ones suggested by our network. These results suggest paths in the product space which are easier to achieve, and so can drive countries' policies in the industrialization process
Universal relation between skewness and kurtosis in complex dynamics
No full textWe identify an important correlation between skewness and kurtosis for a broad class of complex dynamic systems and present a specific analysis of earthquake and financial time series. Two regimes of non-Gaussianity can be identified: a parabolic one, which is common in various fields of physics, and a power law one, with exponent 4/3, which at the moment appears to be specific of earthquakes and financial markets. For this property we propose a model and an interpretation in terms of very rare events dominating the statistics independently on the nature of the events considered. The predicted scaling relation between skewness and kurtosis matches very well the experimental pattern of the second regime. Regarding price fluctuations, this situation characterizes a universal stylize
Reaction to extreme events in a minimal agent based model
No full textWe consider the issue of the overreaction of financial markets to a sudden price change. In particular, we focus on the price and the population dynamics which follows a large fluctuation. In order to investigate these aspects from different perspectives we discuss the known results for empirical data, the Lux-Marchesi model and a minimal agent based model which we have recently proposed. We show that, in this framework, the presence of a overreaction is deeply linked to the population dynamics. In particular, the presence of a destabilizing strategy in the market is a necessary condition to have an overshoot with respect to the exogenously induced price fluctuation. Finally, we analyze how the memory of the agents can quantitatively affect this behavi
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