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2
votes
Lukas Vacha, Jozef Barunik
posted by LKristoufek (31 January 2012)
In this paper, we contribute to the literature on energy market co-movement
by studying its dynamics in the time-frequency domain. The novelty of our
approach lies in the application of wavelet tools to commodity market data. A
major part of economic time series analysis is done in the time or frequency
domain separately. Wavelet analysis combines these two fundamental approaches
allowing study of the time series in the time- frequency domain. Using this
framework, we propose a new, model-free way of estimating time-varying cor-
relations. In the empirical analysis, we connect our approach to the dynamic
conditional correlation approach of Engle (2002) on the main components of the
energy sector. Namely, we use crude oil, gasoline, heating oil, and natural gas
on a nearest-future basis over a period of approximately 16 and 1/2 years
beginning on November 1, 1993 and ending on July 21, 2010. Using wavelet
coherence, we uncover interesting dynamics of correlations between energy
commodities in the time-frequency space.
2
votes
Jozef Barunik, Ladislav Kristoufek
posted by LKristoufek (31 January 2012)
In this paper, we show how the sampling properties of the Hurst exponent
methods of estimation change with the presence of heavy tails. We run extensive
Monte Carlo simulations to find out how rescaled range analysis (R/S),
multifractal detrended fluctuation analysis (MF-DFA), detrending moving average
(DMA) and generalized Hurst exponent approach (GHE) estimate Hurst exponent on
independent series with different heavy tails. For this purpose, we generate
independent random series from stable distribution with stability exponent
{\alpha} changing from 1.1 (heaviest tails) to 2 (Gaussian normal distribution)
and we estimate the Hurst exponent using the different methods. R/S and GHE
prove to be robust to heavy tails in the underlying process. GHE provides the
lowest variance and bias in comparison to the other methods regardless the
presence of heavy tails in data and sample size. Utilizing this result, we
apply a novel approach of the intraday time-dependent Hurst exponent and we
estimate the Hurst exponent on high frequency data for each trading day
separately. We obtain Hurst exponents for S&P500 index for the period beginning
with year 1983 and ending by November 2009 and we discuss the surprising result
which uncovers how the market's behavior changed over this long period.
2
votes
Jozef Barunik, Lukas Vacha
posted by LKristoufek (31 January 2012)
In this paper we propose a new approach to estimation of the tail exponent in
financial stock markets. We begin the study with the finite sample behavior of
the Hill estimator under {\alpha}-stable distributions. Using large Monte Carlo
simulations, we show that the Hill estimator overestimates the true tail
exponent and can hardly be used on samples with small length. Utilizing our
results, we introduce a Monte Carlo-based method of estimation for the tail
exponent. Our proposed method is not sensitive to the choice of tail size and
works well also on small data samples. The new estimator also gives unbiased
results with symmetrical confidence intervals. Finally, we demonstrate the
power of our estimator on the international world stock market indices. On the
two separate periods of 2002-2005 and 2006-2009, we estimate the tail exponent.
1
vote
Jongwook Kim, Gabjin Oh
posted by Matúš Medo (31 January 2012)
We propose a stochastic process driven by memory effect with novel
distributions including both exponential and leptokurtic heavy-tailed
distributions. A class of distribution is analytically derived from the
continuum limit of the discrete binary process with the renormalized
auto-correlation and the closed form moment generating function is obtained,
thus the cumulants are calculated and shown to be convergent. The other class
of distributions are numerically investigated. The concoction of the two
stochastic processes of the different signs of memory under regime switching
mechanism does incarnate power-law decay behavior, which strongly implies that
memory is the alternative origin of heavy-tail.
1
vote
Peter Kratz, Torsten Schöneborn
posted by Matúš Medo (31 January 2012)
We consider an illiquid financial market where a risk averse investor has to
liquidate a portfolio within a finite time horizon [0,T] and can trade
continuously at a traditional exchange (the "primary venue") and in a dark
pool. At the primary venue, trading yields a linear price impact. In the dark
pool, no price impact costs arise but order execution is uncertain, modeled by
a multi-dimensional Poisson process. We characterize the costs of trading by a
linear-quadratic functional which incorporates both the price impact costs of
trading at the primary exchange and the market risk of the position. The
liquidation constraint implies a singularity of the value function of the
resulting minimization problem at the terminal time T. Via the HJB equation and
a quadratic ansatz, we obtain a candidate for the value function which is the
limit of a sequence of solutions of initial value problems for a matrix
differential equation. We show that this limit exists by using an appropriate
matrix inequality and a comparison result for Riccati matrix equations.
Additionally, we obtain upper and lower bounds of the solutions of the initial
value problems, which allow us to prove a verification theorem. If a single
asset position is to be liquidated, the investor slowly trades out of her
position at the primary venue, with the remainder being placed in the dark pool
at any point in time. For multi-asset liquidations this is generally not the
case; it can, e.g., be optimal to oversize orders in the dark pool in order to
turn a poorly balanced portfolio into a portfolio bearing less risk.
2
votes
Anne-Ly Do, Lars Rudolf, Thilo Gross
posted by Matúš Medo (31 January 2012)
In a recent paper, we analyzed the self-assembly of a complex cooperation
network. The network was shown to approach a state where every agent invests
the same amount of resources. Nevertheless, highly-connected agents arise that
extract extraordinarily high payoffs while contributing comparably little to
any of their cooperations. Here, we investigate a variant of the model, in
which highly-connected agents have access to additional resources. We study
analytically and numerically whether these resources are invested in existing
collaborations, leading to a fairer load distribution, or in establishing new
collaborations, leading to an even less fair distribution of loads and payoffs.
2
votes
B. Berche, C. von Ferber, T. Holovatch, Yu. Holovatch
posted by Matúš Medo (31 January 2012)
The goals of this paper are to present criteria, that allow to a priori
quantify the attack stability of real world correlated networks of finite size
and to check how these criteria correspond to analytic results available for
infinite uncorrelated networks. As a case study, we consider public
transportation networks (PTN) of several major cities of the world. To analyze
their resilience against attacks either the network nodes or edges are removed
in specific sequences (attack scenarios). During each scenario the size S(c) of
the largest remaining network component is observed as function of the removed
share c of nodes or edges. To quantify the PTN stability with respect to
different attack scenarios we use the area below the curve described by S(c)
for c \in [0,1] recently introduced (Schneider, C. M, et al., PNAS 108 (2011)
3838) as a numerical measure of network robustness. This measure captures the
network reaction over the whole attack sequence. We present results of the
analysis of PTN stability against node and link-targeted attacks.
3
votes
M. Dickison, S. Havlin, H. E. Stanley
posted by Matúš Medo (31 January 2012)
Populations are seldom completely isolated from their environment.
Individuals in a particular geographic or social region may be considered a
distinct network due to strong local ties, but will also interact with
individuals in other networks. We study the susceptible-infected-recovered
(SIR) process on interconnected network systems, and find two distinct regimes.
In strongly-coupled network systems, epidemics occur simultaneously across the
entire system at a critical infection strength $\beta_c$, below which the
disease does not spread. In contrast, in weakly-coupled network systems, a
mixed phase exists below $\beta_c$ of the coupled network system, where an
epidemic occurs in one network but does not spread to the coupled network. We
derive an expression for the network and disease parameters that allow this
mixed phase and verify it numerically. Public health implications of
communities comprising these two classes of network systems are also mentioned.
3
votes
Vladimir Filimonov, Didier Sornette
posted by Matúš Medo (23 January 2012)
We introduce a new measure of activity of financial markets that provides a
direct access to their level of endogeneity. This measure quantifies how much
of price changes are due to endogenous feedback processes, as opposed to
exogenous news. For this, we calibrate the self-excited conditional Poisson
Hawkes model, which combines in a natural and parsimonious way exogenous
influences with self-excited dynamics, to the E-mini S&P 500 futures contracts
traded in the Chicago Mercantile Exchange from 1998 to 2010. We find that the
level of endogeneity has increased significantly from 1998 to 2010, with only
70% in 1998 to less than 30% since 2007 of the price changes resulting from
some revealed exogenous information. Analogous to nuclear plant safety
concerned with avoiding "criticality", our measure provides a direct
quantification of the distance of the financial market to a critical state
defined precisely as the limit of diverging trading activity in absence of any
external driving.
2
votes
Eytan Bakshy, Itamar Rosenn, Cameron Marlow, Lada Adamic
posted by Matúš Medo (23 January 2012)
Online social networking technologies enable individuals to simultaneously
share information with any number of peers. Quantifying the causal effect of
these technologies on the dissemination of information requires not only
identification of who influences whom, but also of whether individuals would
still propagate information in the absence of social signals about that
information. We examine the role of social networks in online information
diffusion with a large-scale field experiment that randomizes exposure to
signals about friends' information sharing among 253 million subjects in situ.
Those who are exposed are significantly more likely to spread information, and
do so sooner than those who are not exposed. We further examine the relative
role of strong and weak ties in information propagation. We show that, although
stronger ties are individually more influential, it is the more abundant weak
ties who are responsible for the propagation of novel information. This
suggests that weak ties may play a more dominant role in the dissemination of
information online than currently believed.
2
votes
Reginald D. Smith
posted by Rsmith (23 January 2012)
In this paper we analyze Gresham's Law, in particular, how the rate of inflow
or outflow of currencies is affected by the demand elasticity of arbitrage and
the difference in face value ratios inside and outside of a country under a
bimetallic system. We find that these equations are very similar to those used
to describe drift in systems of free charged particles. In addition, we look at
how Gresham's Law would play out with multiple currencies and multiple
countries under a variety of connecting topologies.
2
votes
Franck Jovanovic and Christophe Schinckus
posted by gocadog (21 January 2012)
This paper deals with the disciplinary dimensions of a very new field called econphysics and shows that despite the fact that econophysics is regularly described as an interdisciplinary approach, it is in fact a multidisciplinary field. Beyond this observation, we note that recent developments suggests that econophysics could evolve into a more integrated field. We have therefore taken a prospective approach by analyzing how this field could become more transdisciplinary. We show that a common echeme is attainable and we investigate the possibilities of transdisciplinary econophysics.
2
votes
Ladislav Kristoufek
posted by LKristoufek (18 January 2012)
We introduce a new method for detection of long-range cross-correlations and
multifractality - multifractal height cross-correlation analysis (MF-HXA) -
based on scaling of qth order covariances. MF-HXA is a bivariate generalization
of the height-height correlation analysis of Barabasi & Vicsek [Barabasi, A.L.,
Vicsek, T.: Multifractality of self-affine fractals, Physical Review A 44(4),
1991]. The method can be used to analyze long-range cross-correlations and
multifractality between two simultaneously recorded series. We illustrate a
power of the method on both simulated and real-world time series.
1
vote
Ladislav Kristoufek
posted by LKristoufek (18 January 2012)
In this paper, we present the results of Monte Carlo simulations for two
popular techniques of long-range correlations detection - classical and
modified rescaled range analyses. A focus is put on an effect of different
distributional properties on an ability of the methods to efficiently
distinguish between short and long-term memory. To do so, we analyze the
behavior of the estimators for independent, short-range dependent, and
long-range dependent processes with innovations from 8 different distributions.
We find that apart from a combination of very high levels of kurtosis and
skewness, both estimators are quite robust to distributional properties.
Importantly, we show that R/S is biased upwards (yet not strongly) for
short-range dependent processes, while M-R/S is strongly biased downwards for
long-range dependent processes regardless of the distribution of innovations.
1
vote
Pau Erola, Albert Diaz-Guilera, Sergio Gomez, Alex Arenas
posted by Matúš Medo (17 January 2012)
Trade is a fundamental pillar of economy and a form of social organization.
Its empirical characterization at the worldwide scale is represented by the
World Trade Web (WTW), the network built upon the trade relationships between
the different countries. Several scientific studies have focused on the
structural characterization of this network, as well as its dynamical
properties, since we have registry of the structure of the network at different
times in history. In this paper we study an abstract scenario for the
development of global crises on top of the structure of connections of the WTW.
Assuming a cyclic dynamics of national economies and the interaction of
different countries according to the import-export balances, we are able to
investigate, using a simple model of pulse-coupled oscillators, the
synchronization phenomenon of crises at the worldwide scale. We focus on the
level of synchronization measured by an order parameter at two different
scales, one for the global system and another one for the mesoscales defined
through the topology. We use the WTW network structure to simulate a network of
Integrate-and-Fire oscillators for six different snapshots between years 1950
and 2000. The results reinforce the idea that globalization accelerates the
global synchronization process, and the analysis at a mesoscopic level shows
that this synchronization is different before and after globalization periods:
after globalization, the effect of communities is almost inexistent.
1
vote
Matteo Marsili
posted by Matúš Medo (17 January 2012)
For fat tailed distributions (i.e. those that decay slower than an
exponential), large deviations not only become relatively likely, but the way
in which they are realized changes dramatically: A finite fraction of the whole
sample deviation is concentrated on a single variable: large deviations are not
the accumulation of many small deviations, but rather they are dominated to a
single large fluctuation. The regime of large deviations is separated from the
regime of typical fluctuations by a phase transition where the symmetry between
the points in the sample is {\em spontaneously broken}. This phenomenon has
been discussed in the context of mass transport models in physics, where it
takes the form of a condensation phase transition. Yet, the phenomenon is way
more general. For example, in risk management of large portfolios, it suggests
that one should expect losses to concentrate on a single asset: when extremely
bad things happen, it is likely that there is a single factor on which bad luck
concentrates. Along similar lines, one should expect that bubbles in financial
markets do not gradually deflate, but rather burst abruptly and that in the
most rainy day of a year, precipitation concentrate on a given spot.
Analogously, when applied to biological evolution, we're lead to infer that, if
fitness changes for individual mutations have a broad distribution, those large
deviations that lead to better fit species are not likely to result from the
accumulation of small positive mutations. Rather they are likely to arise from
large rare jumps.
1
vote
Hao Meng, Fei Ren, Gao-Feng Gu, Xiong Xiong, Yong-Jie Zhang, Wei-Xing Zhou, Wei Zhang
posted by Matúš Medo (17 January 2012)
Understanding the statistical properties of recurrence intervals of extreme
events is crucial to risk assessment and management of complex systems. The
probability distributions and correlations of recurrence intervals for many
systems have been extensively investigated. However, the impacts of microscopic
rules of a complex system on the macroscopic properties of its recurrence
intervals are less studied. In this Letter, we adopt an order-driven stock
market model to address this issue for stock returns. We find that the
distributions of the scaled recurrence intervals of simulated returns have a
power law scaling with stretched exponential cutoff and the intervals possess
multifractal nature, which are consistent with empirical results. We further
investigate the effects of long memory in the directions (or signs) and
relative prices of the order flow on the characteristic quantities of these
properties. It is found that the long memory in the order directions (Hurst
index $H_s$) has a negligible effect on the interval distributions and the
multifractal nature. In contrast, the power-law exponent of the interval
distribution increases linearly with respect to the Hurst index $H_x$ of the
relative prices, and the singularity width of the multifractal nature
fluctuates around a constant value when $H_x<0.7$ and then increases with
$H_x$. No evident effects of $H_s$ and $H_x$ are found on the long memory of
the recurrence intervals. Our results indicate that the nontrivial properties
of the recurrence intervals of returns are mainly caused by traders' behaviors
of persistently placing new orders around the best bid and ask prices.
1
vote
Vygintas Gontis, Aleksejus Kononovicius, Stefan Reimann
posted by Matúš Medo (17 January 2012)
We investigate large changes, bursts, of the continuous stochastic signals,
when the exponent of multiplicativity is higher than one. Earlier we have
proposed a general nonlinear stochastic model which can be transformed into
Bessel process with known first hitting (first passage) time statistics. Using
these results we derive PDF of burst duration for the proposed model. We
confirm analytical expressions by numerical evaluation and discuss bursty
behavior of return in financial markets in the framework of modeling by
nonlinear SDE.
1
vote
Kun Zhao, Márton Karsai, Ginestra Bianconi
posted by Matúš Medo (17 January 2012)
Human dynamical social networks encode information and are highly adaptive.
To characterize the information encoded in the fast dynamics of social
interactions, here we introduce the entropy of dynamical social networks. By
analysing a large dataset of phone-call interactions we show evidence that the
dynamical social network has an entropy that depends on the time of the day in
a typical week-day. Moreover we show evidence for adaptability of human social
behavior showing data on duration of phone-call interactions that significantly
deviates from the statistics of duration of face-to-face interactions. This
adaptability of behavior corresponds to a different information content of the
dynamics of social human interactions. We quantify this information by the use
of the entropy of dynamical networks on realistic models of social
interactions.
1
vote
Daniel Kapp, Marco Vega
posted by Matúš Medo (10 January 2012)
We study cross-country GDP losses due to financial crises in terms of
frequency (number of loss events per period) and severity (loss per
occurrence). We perform the Loss Distribution Approach (LDA) to estimate a
multi-country aggregate GDP loss probability density function and the
percentiles associated to extreme events due to financial crises.
<br />We find that output losses arising from financial crises are strongly
heterogeneous and that currency crises lead to smaller output losses than debt
and banking crises.
<br />Extreme global financial crises episodes, occurring with a one percent
probability every five years, lead to losses between 2.95% and 4.54% of world
GDP.
2
votes
Leonidas Sandoval Junior, Adriana Bruscato, Maria Kelly Venezuela
posted by Matúš Medo (10 January 2012)
By using Random Matrix Theory, we build covariance matrices between stocks of
the BM&F-Bovespa (Bolsa de Valores, Mercadorias e Futuros de S\~ao Paulo) which
are cleaned of some of the noise due to the complex interactions between the
many stocks and the finiteness of available data. We also use a regression
model in order to remove the market effect due to the common movement of all
stocks. These two procedures are then used to build stock portfolios based on
Markowitz's theory, trying to obtain better predictions of future risk based on
past data. This is done for years of both low and high volatility of the
Brazilian stock market, from 2004 to 2010. The results show that the use of
regression to subtract the market effect on returns greatly increases the
accuracy of the prediction of risk, and that, although the cleaning of the
correlation matrix often leads to portfolios that better predict risks, in
periods of high volatility of the market this procedure may fail to do so.
1
vote
Jozef Barunik, Tomaso Aste, Tiziana Di Matteo, Ruipeng Liu
posted by Matúš Medo (10 January 2012)
In this paper, we use the generalized Hurst exponent approach to study the
multi- scaling behavior of different financial time series. We show that this
approach is robust and powerful in detecting different types of multiscaling.
We observe a puzzling phenomenon where an apparent increase in multifractality
is measured in time series generated from shuffled returns, where all
time-correlations are destroyed, while the return distributions are conserved.
This effect is robust and it is reproduced in several real financial data
including stock market indices, exchange rates and interest rates. In order to
understand the origin of this effect we investigate different simulated time
series by means of the Markov switching multifractal (MSM) model,
autoregressive fractionally integrated moving average (ARFIMA) processes with
stable innovations, fractional Brownian motion and Levy flights. Overall we
conclude that the multifractality observed in financial time series is mainly a
consequence of the characteristic fat-tailed distribution of the returns and
time-correlations have the effect to decrease the measured multifractality.
2
votes
Zhen Wang, Attila Szolnoki, Matjaz Perc
posted by Matúš Medo (10 January 2012)
We study the evolution of public cooperation on two interdependent networks
that are connected by means of a utility function, which determines to what
extent payoffs in one network influence the success of players in the other
network. We find that the stronger the bias in the utility function, the higher
the level of public cooperation. Yet the benefits of enhanced public
cooperation on the two networks are just as biased as the utility functions
themselves. While cooperation may thrive on one network, the other may still be
plagued by defectors. Nevertheless, the aggregate level of cooperation on both
networks is higher than the one attainable on an isolated network. This
positive effect of biased utility functions is due to the suppressed feedback
of individual success, which leads to a spontaneous separation of
characteristic time scales of the evolutionary process on the two
interdependent networks. As a result, cooperation is promoted because the
aggressive invasion of defectors is more sensitive to the slowing down than the
build-up of collective efforts in sizable groups.
1
vote
Giorgio Fagiolo, Tiziano Squartini, Diego Garlaschelli
posted by Matúš Medo (10 January 2012)
In all empirical-network studies, the observed properties of economic
networks are informative only if compared with a well-defined null model that
can quantitatively predict the behavior of such properties in constrained
graphs. However, predictions of the available null-model methods can be derived
analytically only under assumptions (e.g., sparseness of the network) that are
unrealistic for most economic networks like the World Trade Web (WTW). In this
paper we study the evolution of the WTW using a recently-proposed family of
null network models. The method allows to analytically obtain the expected
value of any network statistic across the ensemble of networks that preserve on
average some local properties, and are otherwise fully random. We compare
expected and observed properties of the WTW in the period 1950-2000, when
either the expected number of trade partners or total country trade is kept
fixed and equal to observed quantities. We show that, in the binary WTW,
node-degree sequences are sufficient to explain higher-order network properties
such as disassortativity and clustering-degree correlation, especially in the
last part of the sample. Conversely, in the weighted WTW, the observed sequence
of total country imports and exports are not sufficient to predict higher-order
patterns of the WTW. We discuss some important implications of these findings
for international-trade models.
1
vote
G. Cadogan
posted by gocadog (8 January 2012)
We present conditions under which positive alpha exists in the realm of active portfolio management–
in contrast to the controversial result in (Jarrow, 2010, pg. 20) which implicates delegated portfolio
management by surmising that positive alphas are illusionary. Specifically, we show that the critical
assumption used in (Jarrow, 2010, pg. 20), to derive the illusionary alpha result, is based on
a zero set for CAPM with Lebesgue measure zero. So conclusions based on the assumption may
well have probability measure zero of occurrence. Technically, the existence of [Tanaka] local time
on that set implies existence of positive alphas. In fact, we show that positive alpha exists under
the same scenarios of ”perpetual event swap” and ”market systemic event” Jarrow (2010) used to
formulate the illusionary positive alpha result. First, we prove that as long as asset price volatility
is greater than zero, systemic events like market crash will occur in finite time almost surely. Thus
creating an opportunity to hedge against that event. Second, we find that Jarrow’s ”false positive
alpha” variable constitutes portfolio manager reward for trading strategy. For instance, we show
that positive alpha exists if portfolio managers develop hedging strategies based on either (1) an
exotic [barrier] option on the underlying asset–with barrier hitting time motivated by the ”market
systemic” event, or (2) a swaption strategy for the implied interest rate risk inherent in Jarrow’s
triumvirate of riskless rate of return, factor sensitivity exposure, and constant risk premium for a
perpetual event swap.
1
vote
Christian Borghesi, Jean-Claude Raynal, Jean-Philippe Bouchaud
posted by Matúš Medo (4 January 2012)
We study in details the turnout rate statistics for 77 elections in 11
different countries. We show that the empirical results established in a
previous paper for French elections appear to hold much more generally. We find
in particular that the spatial correlation of turnout rates decay
logarithmically with distance in all cases. This result is quantitatively
reproduced by a decision model that assumes that each voter makes his mind as a
result of three influence terms: one totally idiosyncratic component, one
city-specific term with short-ranged fluctuations in space, and one long-ranged
correlated field which propagates diffusively in space. A detailed analysis
reveals several interesting features: for example, different countries have
different degrees of local heterogeneities and seem to be characterized by a
different propensity for individuals to conform to the cultural norm. We
furthermore find clear signs of herding (i.e. strongly correlated decisions at
the individual level) in some countries, but not in others.
1
vote
Zalán Forró, Peter Cauwels, Didier Sornette
posted by Matúš Medo (4 January 2012)
On December 16, Zynga, the well-known social game developing company went
public. This event is following other recent IPOs in the world of social
networking companies, such as Groupon, Linkedin or Pandora to cite a few. With
a valuation close to 7 billion USD at the time when it went public, Zynga has
become the biggest web IPO since Google. This recent enthusiasm for social
networking companies, and in particular Zynga, brings up the question whether
or not they are overvalued. The common denominator of all these IPOs is that a
lot of estimates about their valuation have been circulating, without any
specifics given about the methodology or assumptions used to obtain those
numbers. To bring more substance to the debate, we propose a two-tiered
approach. First, we introduce a new model to forecast the global user base of
Zynga, based on the analysis of the individual dynamics of its major games.
Next, we model the revenues per user using a logistic growth function, a
standard model for growth in competition. This leads to bracket the valuation
of Zynga using three different scenarios (base one, optimistic and very
optimistic): 4.17 billion USD in the base case, 5.16 billion in the high growth
and 7.02 billion in the extreme growth scenario respectively. Thus, only the
unlikely extreme growth scenario could potentially justify today's 6.6 billion
USD valuation of Zynga. This suggests that Zynga at its IPO has been
overpriced.
1
vote
Hamed Amini, Rama Cont, Andreea Minca
posted by Matúš Medo (4 January 2012)
Propagation of balance-sheet or cash-flow insolvency across financial
institutions may be modeled as a cascade process on a network representing
their mutual exposures. We derive rigorous asymptotic results for the magnitude
of contagion in a large financial network and give an analytical expression for
the asymptotic fraction of defaults, in terms of network characteristics. Our
results extend previous studies on contagion in random graphs to inhomogeneous
directed graphs with a given degree sequence and arbitrary distribution of
weights. We introduce a criterion for the resilience of a large financial
network to the insolvency of a small group of financial institutions and
quantify how contagion amplifies small shocks to the network. Our results
emphasize the role played by "contagious links" and show that institutions
which contribute most to network instability in case of default have both large
connectivity and a large fraction of contagious links. The asymptotic results
show good agreement with simulations for networks with realistic sizes.
1
vote
Alexandros Gabrielsen, Massimiliano Marzo, Paolo Zagaglia
posted by Matúš Medo (4 January 2012)
Asset liquidity in modern financial markets is a key but elusive concept. A
market is often said to be liquid when the prevailing structure of transactions
provides a prompt and secure link between the demand and supply of assets, thus
delivering low costs of transaction. Providing a rigorous and empirically
relevant definition of market liquidity has, however, provided to be a
difficult task. This paper provides a critical review of the frameworks
currently available for modelling and estimating the market liquidity of
assets. We consider definitions that stress the role of the bid-ask spread and
the estimation of its components that arise from alternative sources of market
friction. In this case, intra-daily measures of liquidity appear relevant for
capturing the core features of a market, and for their ability to describe the
arrival of new information to market participants.
1
vote
W.-X. Zhou, G.-H. Mu, J. Kertész
posted by Matúš Medo (4 January 2012)
We study the cross-correlation matrix $C_{ij}$ of inventory variations of the
most active individual and institutional investors in an emerging market to
understand the dynamics of inventory variations. We find that the distribution
of cross-correlation coefficient $C_{ij}$ has a power-law form in the bulk
followed by exponential tails and there are more positive coefficients than
negative ones. In addition, it is more possible that two individuals or two
institutions have stronger inventory variation correlation than one individual
and one institution. We find that the largest and the second largest
eigenvalues ($\lambda_1$ and $\lambda_2$) of the correlation matrix cannot be
explained by the random matrix theory and the projection of inventory
variations on the first eigenvector $u(\lambda_1)$ are linearly correlated with
stock returns, where individual investors play a dominating role. The investors
are classified into three categories based on the cross-correlation
coefficients $C_{VR}$ between inventory variations and stock returns. Half
individuals are reversing investors who exhibit evident buy and sell herding
behaviors, while 6% individuals are trending investors. For institutions, only
10% and 8% investors are trending and reversing investors. A strong Granger
causality is unveiled from stock returns to inventory variations, which means
that a large proportion of individuals hold the reversing trading strategy and
a small part of individuals hold the trending strategy. Comparing with the case
of Spanish market, Chinese investors exhibit common and market-specific
behaviors. Our empirical findings have scientific significance in the
understanding of investors' trading behaviors and in the construction of
agent-based models for stock markets.
1
vote
Krishanu Roy Chowdhury, Asim Ghosh, Soumyajyoti Biswas, Bikas K. Chakrabarti
posted by Matúš Medo (4 January 2012)
We study a recently proposed kinetic exchange opinion model (Lallouache et.
al., Phys. Rev E 82, 056112 (2010)) in the limit of a single parameter map.
Although it does not include the essentially complex behavior of the multiagent
version, it provides us with the insight regarding the choice of order
parameter for the system as well as some of its other dynamical properties. We
also study the generalized two-parameter version of the model, and provide the
exact phase diagram. The universal behavior along this phase boundary in terms
of the suitably defined order parameter is seen.
1
vote
Nikolay K. Vitanov, Marcel R. Ausloos
posted by Matúš Medo (4 January 2012)
The diffusion of ideas is often closely connected to the creation and
diffusion of knowledge and to the technological evolution of society. Because
of this, knowledge creation, exchange and its subsequent transformation into
innovations for improved welfare and economic growth is briefly described from
a historical point of view. Next, three approaches are discussed for modeling
the diffusion of ideas in the areas of science and technology, through (i)
deterministic, (ii) stochastic, and (iii) statistical approaches. These are
illustrated through their corresponding population dynamics and epidemic models
relative to the spreading of ideas, knowledge and innovations. The
deterministic dynamical models are considered to be appropriate for analyzing
the evolution of large and small societal, scientific and technological systems
when the influence of fluctuations is insignificant. Stochastic models are
appropriate when the system of interest is small but when the fluctuations
become significant for its evolution. Finally statistical approaches and models
based on the laws and distributions of Lotka, Bradford, Yule, Zipf-Mandelbrot,
and others, provide much useful information for the analysis of the evolution
of systems in which development is closely connected to the process of idea
diffusion.
2
votes
G. Cadogan
posted by gocadog (3 January 2012)
In this paper we present a simple closed form stock price formula, which captures empirical regularities of high frequency trading (HFT), based on two factors: (1) exposure to hedge factor; and (2) hedge factor volatility. Thus, the parsimonious formula is not based on fundamental valuation. For instance, it allows us to use exposure to and volatility of E-mini contracts to predict movements in an underlying index. For application, we first show that for given exposure to hedge factor, and suitable specification of hedge factor volatility, HFT stock price has a closed form double exponential representation. There, in periods of uncertainty, if volatility is above historic average, a relatively small short selling trade strategy is magnified exponentially, and the stock price plummets when strategies are phased locked. Second, we demonstrate how asymmetric response to news is incorporated in the stock price by and through an endogenous EGARCH type volatility process; and find that intraday returns have a U-shaped pattern inherited from HFT strategies. Third, we show that the stock price is bounded from below (crash), i.e. flight to quality, but not from above (bubble), i.e. confidence, when phased locked trade strategies violate prerequisites of van der Corput's Lemma. Thus, extant regulatory proposals to control price dynamics of select stocks, i.e., ''limit up/limit down" bands over 5-minute rolling windows, may mitigate but not stop future market crashes or price bubbles from manifesting in underlying indexes that exhibit HFT stock price dynamics.
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