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Complexity in financial market. Modeling psychological behavior in agent-based models and order book models
Get PDFThe 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
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
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
Mechanisms of self-organization and finite size effects in a minimal agent based model
No full textWe present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on the behavior of the price, it is possible to show that the system self-organizes in a regime with a finite number of agents which corresponds to the stylized facts. The mechanism for entering or leaving the market is based on the idea that a too stable market is unappealing for traders, while the presence of price movements attracts agents to enter and speculate on the market. We show that this mechanism is also compatible with the idea that agents are scared by a noisy and risky market at shorter timescales. We also show that the mechanism for self-organization is robust with respect to variations of the exit/entry rules and that the attempt to trigger the system to self-organize in a region without stylized facts leads to an unrealistic dynamics. We study the self-organization in a specific agent based model but we believe that the basic ideas should be of general validity
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,
Time evolution of financial cross-correlation coefficients across market crisis
No full textWe investigate the time evolution of financial cross-correlation coefficients during financial crises and compare them to what is observed in periods of stability. We choose three main events, the Dot.Com Bubble, the market crisis which followed the attacks at the Twin Towers in 2001 and the recent subprime crisis. Each of them has a different nature and a different impact on the market, which we analyze by studying separately different economic sectors. As a general trend, we observe an increase of correlation during these high volatility periods and a broadening of the distributions of correlation coefficients. We then compare the spectra of the cross-correlation matrices, calculated in different periods of three years, with the distribution of eigenvalues predicted by the Random Matrix Theory. We find that these spectra are markedly perturbated during crisis periods. Finally we show how a simple stochastic model can produce similar results
Correction: The complex dynamics of products and its asymptotic properties.
No full text[This corrects the article DOI: 10.1371/journal.pone.0177360.]
A New Metrics for Countries' Fitness and Products' Complexity
Get PDFClassical economic theories prescribe specialization of countries industrial production. Inspection of the country databases of exported products shows that this is not the case: successful countries are extremely diversified, in analogy with biosystems evolving in a competitive dynamical environment. The challenge is assessing quantitatively the non-monetary competitive advantage of diversification which represents the hidden potential for development and growth. Here we develop a new statistical approach based on coupled non-linear maps, whose fixed point defines a new metrics for the country Fitness and product Complexity. We show that a non-linear iteration is necessary to bound the complexity of products by the fitness of the less competitive countries exporting them. We show that, given the paradigm of economic complexity, the correct and simplest approach to measure the competitiveness of countries is the one presented in this work. Furthermore our metrics appears to be economically well-grounded
Asymmetric statistics of order books: The role of discreteness and evidence for strategic order placement
No full textWe show that the statistics of spreads in real order books is characterized by an intrinsic asymmetry due to discreteness effects for even or odd values of the spread. An analysis of data from the New York Stock Exchange (NYSE) order book points out that traders' strategies contribute to this asymmetry. We also investigate this phenomenon in the framework of a microscopic model and, by introducing a nonuniform deposition mechanism for limit orders, we are able to quantitatively reproduce the asymmetry found in the experimental data. Simulations of our model also show a realistic dynamics with a sort of intermittent behavior characterized by long periods in which the order book is compact and liquid interrupted by volatile configurations. The order placement strategies produce a nontrivial behavior of the spread relaxation dynamics which is similar to the one observed in real markets
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