190 research outputs found
A model for correlations in stock markets
We propose a group model for correlations in stock markets. In the group
model the markets are composed of several groups, within which the stock price
fluctuations are correlated. The spectral properties of empirical correlation
matrices reported in [Phys. Rev. Lett. {\bf 83}, 1467 (1999); Phys. Rev. Lett.
{\bf 83}, 1471 (1999.)] are well understood from the model. It provides the
connection between the spectral properties of the empirical correlation matrix
and the structure of correlations in stock markets.Comment: two pages including one EPS file for a figur
Inverse Cubic Law for the Probability Distribution of Stock Price Variations
The probability distribution of stock price changes is studied by analyzing a
database (the Trades and Quotes Database) documenting every trade for all
stocks in three major US stock markets, for the two year period Jan 1994 -- Dec
1995. A sample of 40 million data points is extracted, which is substantially
larger than studied hitherto. We find an asymptotic power-law behavior for the
cumulative distribution with an exponent alpha approximately 3, well outside
the Levy regime 0< alpha <2.Comment: 5 pages, 4 figures, RevTex 2 figures adde
Quantifying Stock Price Response to Demand Fluctuations
We address the question of how stock prices respond to changes in demand. We
quantify the relations between price change over a time interval
and two different measures of demand fluctuations: (a) , defined as the
difference between the number of buyer-initiated and seller-initiated trades,
and (b) , defined as the difference in number of shares traded in buyer
and seller initiated trades. We find that the conditional expectations and of price change for a given or
are both concave. We find that large price fluctuations occur when demand is
very small --- a fact which is reminiscent of large fluctuations that occur at
critical points in spin systems, where the divergent nature of the response
function leads to large fluctuations.Comment: 4 pages (multicol fomat, revtex
Bioactive potential of actinobacteria isolated from the gut of marine fishes
1280-1285The study was undertaken to explore the gut-associated actinobacteria from two marine fish with special reference to antimicrobial and anti-quorum sensing activity. A total of 40 actinobacterial strains were isolated from fish gut samples using starch casein agar and Kusterâs agar medium. About 14 morphologically different strains recovered from Rastrelliger kanagurta (Indian mackerel) and Panna microdon (Panna croaker) were screened for the antimicrobial activity against Staphylococcus aureus MTCC96, Escherichia coli MTCC739, Salmonella enterica, Candida albicans, and quorum sensing inhibition (QSI) against Chromobacterium violaceum and Serratia marcescens. The actinobacterial strain IM20 from R. kanagurta showed both antimicrobial and QSI activity, whereas the strains PCA1 and PCA4 from P. microdon showed only antimicrobial activity. Strain IM20, which showed wide range of activity, was selected as the potential strain for further studies. Thus, the findings suggested that the fish-associated actinobacteria is a promising source for antimicrobial compounds for developing novel therapeutic drugs
The Grounds For Time Dependent Market Potentials From Dealers' Dynamics
We apply the potential force estimation method to artificial time series of
market price produced by a deterministic dealer model. We find that dealers'
feedback of linear prediction of market price based on the latest mean price
changes plays the central role in the market's potential force. When markets
are dominated by dealers with positive feedback the resulting potential force
is repulsive, while the effect of negative feedback enhances the attractive
potential force.Comment: 9 pages, 3 figures, proceedings of APFA
Exponential distribution of financial returns at mesoscopic time lags: a new stylized fact
We study the probability distribution of stock returns at mesoscopic time
lags (return horizons) ranging from about an hour to about a month. While at
shorter microscopic time lags the distribution has power-law tails, for
mesoscopic times the bulk of the distribution (more than 99% of the
probability) follows an exponential law. The slope of the exponential function
is determined by the variance of returns, which increases proportionally to the
time lag. At longer times, the exponential law continuously evolves into
Gaussian distribution. The exponential-to-Gaussian crossover is well described
by the analytical solution of the Heston model with stochastic volatility.Comment: 7 pages, 12 plots, elsart.cls, submitted to the Proceedings of
APFA-4. V.2: updated reference
Statistical properties of short term price trends in high frequency stock market data
We investigated distributions of short term price trends for high frequency
stock market data. A number of trends as a function of their lengths was
measured. We found that such a distribution does not fit to results following
from an uncorrelated stochastic process. We proposed a simple model with a
memory that gives a qualitative agreement with real data.Comment: 10 pages, 9 figures, in ver. 2 one chapter adde
Scaling of the distribution of price fluctuations of individual companies
We present a phenomenological study of stock price fluctuations of individual
companies. We systematically analyze two different databases covering
securities from the three major US stock markets: (a) the New York Stock
Exchange, (b) the American Stock Exchange, and (c) the National Association of
Securities Dealers Automated Quotation stock market. Specifically, we consider
(i) the trades and quotes database, for which we analyze 40 million records for
1000 US companies for the 2-year period 1994--95, and (ii) the Center for
Research and Security Prices database, for which we analyze 35 million daily
records for approximately 16,000 companies in the 35-year period 1962--96. We
study the probability distribution of returns over varying time scales , where varies by a factor of ---from 5 min up to
4 years. For time scales from 5~min up to approximately 16~days, we
find that the tails of the distributions can be well described by a power-law
decay, characterized by an exponent ---well outside the
stable L\'evy regime . For time scales days, we observe results consistent with a slow
convergence to Gaussian behavior. We also analyze the role of cross
correlations between the returns of different companies and relate these
correlations to the distribution of returns for market indices.Comment: 10pages 2 column format with 11 eps figures. LaTeX file requiring
epsf, multicol,revtex. Submitted to PR
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