257 research outputs found
The fine structure of spectral properties for random correlation matrices: an application to financial markets
We study some properties of eigenvalue spectra of financial correlation
matrices. In particular, we investigate the nature of the large eigenvalue
bulks which are observed empirically, and which have often been regarded as a
consequence of the supposedly large amount of noise contained in financial
data. We challenge this common knowledge by acting on the empirical correlation
matrices of two data sets with a filtering procedure which highlights some of
the cluster structure they contain, and we analyze the consequences of such
filtering on eigenvalue spectra. We show that empirically observed eigenvalue
bulks emerge as superpositions of smaller structures, which in turn emerge as a
consequence of cross-correlations between stocks. We interpret and corroborate
these findings in terms of factor models, and and we compare empirical spectra
to those predicted by Random Matrix Theory for such models.Comment: 21 pages, 10 figure
News and price returns from threshold behaviour and vice-versa: exact solution of a simple agent-based market model
Starting from an exact relationship between news, threshold and price return
distributions in the stationary state, I discuss the ability of the
Ghoulmie-Cont-Nadal model of traders to produce fat-tailed price returns. Under
normal conditions, this model is not able to transform Gaussian news into
fat-tailed price returns. When the variance of the news so small that only the
players with zero threshold can possibly react to news, this model produces
Levy-distributed price returns with a -1 exponent. In the special case of
super-linear price impact functions, fat-tailed returns are obtained from
well-behaved news.Comment: 4 pages, 3 figures. This is quite possibly the final version. To
appear in J. Phys
Mechanisms of Self-Organization and Finite Size Effects in a Minimal Agent Based Model
We 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 to enter or leave 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 time scales. 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.Comment: 14 pages, 7 figure
Comprehensive Analysis of Market Conditions in the Foreign Exchange Market: Fluctuation Scaling and Variance-Covariance Matrix
We investigate quotation and transaction activities in the foreign exchange
market for every week during the period of June 2007 to December 2010. A
scaling relationship between the mean values of number of quotations (or number
of transactions) for various currency pairs and the corresponding standard
deviations holds for a majority of the weeks. However, the scaling breaks in
some time intervals, which is related to the emergence of market shocks. There
is a monotonous relationship between values of scaling indices and global
averages of currency pair cross-correlations when both quantities are observed
for various window lengths .Comment: 13 pages, 10 figure
Advances in the Agent-based Modeling of Economic and Social Behavior
In this review we discuss advances in the agent-based modeling of economic and social systems. We show the state of the art of the heuristic design of agents and how behavioral economics and laboratory experiments have improved the modeling of agent behavior. We further discuss how economic networks and social systems can be modeled and we discuss novel methodology and data sources. Lastly, we present an overview of estimation techniques to calibrate and validate agent-based models and show avenues for future research
Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior
Despite the availability of very detailed data on financial market,
agent-based modeling is hindered by the lack of information about real trader
behavior. This makes it impossible to validate agent-based models, which are
thus reverse-engineering attempts. This work is a contribution to the building
of a set of stylized facts about the traders themselves. Using the client
database of Swissquote Bank SA, the largest on-line Swiss broker, we find
empirical relationships between turnover, account values and the number of
assets in which a trader is invested. A theory based on simple mean-variance
portfolio optimization that crucially includes variable transaction costs is
able to reproduce faithfully the observed behaviors. We finally argue that our
results bring into light the collective ability of a population to construct a
mean-variance portfolio that takes into account the structure of transaction
costsComment: 26 pages, 9 figures, Fig. 8 fixe
Human immunodeficiency virus type 1, human protein interaction database at NCBI
The ‘Human Immunodeficiency Virus Type 1 (HIV-1), Human Protein Interaction Database’, available through the National Library of Medicine at www.ncbi.nlm.nih.gov/RefSeq/HIVInteractions, was created to catalog all interactions between HIV-1 and human proteins published in the peer-reviewed literature. The database serves the scientific community exploring the discovery of novel HIV vaccine candidates and therapeutic targets. To facilitate this discovery approach, the following information for each HIV-1 human protein interaction is provided and can be retrieved without restriction by web-based downloads and ftp protocols: Reference Sequence (RefSeq) protein accession numbers, Entrez Gene identification numbers, brief descriptions of the interactions, searchable keywords for interactions and PubMed identification numbers (PMIDs) of journal articles describing the interactions. Currently, 2589 unique HIV-1 to human protein interactions and 5135 brief descriptions of the interactions, with a total of 14 312 PMID references to the original articles reporting the interactions, are stored in this growing database. In addition, all protein–protein interactions documented in the database are integrated into Entrez Gene records and listed in the ‘HIV-1 protein interactions’ section of Entrez Gene reports. The database is also tightly linked to other databases through Entrez Gene, enabling users to search for an abundance of information related to HIV pathogenesis and replication
iRefR: an R package to manipulate the iRefIndex consolidated protein interaction database
<p>Abstract</p> <p>Background</p> <p>The iRefIndex addresses the need to consolidate protein interaction data into a single uniform data resource. iRefR provides the user with access to this data source from an R environment.</p> <p>Results</p> <p>The iRefR package includes tools for selecting specific subsets of interest from the iRefIndex by criteria such as organism, source database, experimental method, protein accessions and publication identifier. Data may be converted between three representations (MITAB, edgeList and graph) for use with other R packages such as igraph, graph and RBGL.</p> <p>The user may choose between different methods for resolving redundancies in interaction data and how n-ary data is represented. In addition, we describe a function to identify binary interaction records that possibly represent protein complexes. We show that the user choice of data selection, redundancy resolution and n-ary data representation all have an impact on graphical analysis.</p> <p>Conclusions</p> <p>The package allows the user to control how these issues are dealt with and communicate them via an R-script written using the iRefR package - this will facilitate communication of methods, reproducibility of network analyses and further modification and comparison of methods by researchers.</p
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