452 research outputs found
Random Matrix Theory Analysis of Cross Correlations in Financial Markets
We confirm universal behaviors such as eigenvalue distribution and spacings
predicted by Random Matrix Theory (RMT) for the cross correlation matrix of the
daily stock prices of Tokyo Stock Exchange from 1993 to 2001, which have been
reported for New York Stock Exchange in previous studies. It is shown that the
random part of the eigenvalue distribution of the cross correlation matrix is
stable even when deterministic correlations are present. Some deviations in the
small eigenvalue statistics outside the bounds of the universality class of RMT
are not completely explained with the deterministic correlations as proposed in
previous studies. We study the effect of randomness on deterministic
correlations and find that randomness causes a repulsion between deterministic
eigenvalues and the random eigenvalues. This is interpreted as a reminiscent of
``level repulsion'' in RMT and explains some deviations from the previous
studies observed in the market data. We also study correlated groups of issues
in these markets and propose a refined method to identify correlated groups
based on RMT. Some characteristic differences between properties of Tokyo Stock
Exchange and New York Stock Exchange are found.Comment: RevTex, 17 pages, 8 figure
Cost functions for pairwise data clustering
Cost functions for non-hierarchical pairwise clustering are introduced, in
the probabilistic autoencoder framework, by the request of maximal average
similarity between the input and the output of the autoencoder. The partition
provided by these cost functions identifies clusters with dense connected
regions in data space; differences and similarities with respect to a well
known cost function for pairwise clustering are outlined.Comment: 5 pages, 4 figure
Drag-out effect of piezomagnetic signals due to a borehole: the Mogi source as an example
We show that using borehole measurements in tectonomagnetic experiments allows enhancement of the observed
signals. New magnetic dipoles, which vary with stress changes from mechanical sources, are produced
on the walls of the borehole. We evaluate such an effect quantitatively. First we formulate a general expression
for the borehole effect due to any arbitrary source models. This is valid everywhere above the ground surface as
well as within the cylindrical hole. A first-order approximate solution is given by a line of horizontal dipoles and
vertical quadrupoles along the central axis of the borehole, which is valid above the ground surface and a slightly
away (several tens of cm) from the top of the borehole. Selecting the Mogi model as an example, we numerically
evaluated the borehole effect. It turned out that the vertical quadrupoles produce two orders of magnitude
more intense magnetic field than the horizontal dipoles. The borehole effect is very local, i.e. detectable only
within a few m from its outlet, since it is of the same order or more than the case without a borehole. However,
magnetic lines of force cannot reach the ground surface from a deeper portion (>10 m) of a borehole
Distinct requirements for the Rad32(Mre¹¹) nuclease and Ctp1(CtIP) in the removal of covalently bound topoisomerase I and II from DNA
For a cancer cell to resist treatment with drugs that trap topoisomerases covalently on the DNA, the topoisomerase must be removed. In this study, we provide evidence that the Schizosaccharomyces pombe Rad32Mre11 nuclease activity is involved in the removal of both Top2 from 5′ DNA ends as well as Top1 from 3′ ends in vivo. A ctp1CtIP deletion is defective for Top2 removal but overproficient for Top1 removal, suggesting that Ctp1CtIP plays distinct roles in removing topoisomerases from 5′ and 3′ DNA ends. Analysis of separation of function mutants suggests that MRN-dependent topoisomerase removal contributes significantly to resistance against topoisomerase-trapping drugs. This study has important implications for our understanding of the role of the MRN complex and CtIP in resistance of cells to a clinically important group of anticancer drugs
Uncovering the Internal Structure of the Indian Financial Market: Cross-correlation behavior in the NSE
The cross-correlations between price fluctuations of 201 frequently traded
stocks in the National Stock Exchange (NSE) of India are analyzed in this
paper. We use daily closing prices for the period 1996-2006, which coincides
with the period of rapid transformation of the market following liberalization.
The eigenvalue distribution of the cross-correlation matrix, , of
NSE is found to be similar to that of developed markets, such as the New York
Stock Exchange (NYSE): the majority of eigenvalues fall within the bounds
expected for a random matrix constructed from mutually uncorrelated time
series. Of the few largest eigenvalues that deviate from the bulk, the largest
is identified with market-wide movements. The intermediate eigenvalues that
occur between the largest and the bulk have been associated in NYSE with
specific business sectors with strong intra-group interactions. However, in the
Indian market, these deviating eigenvalues are comparatively very few and lie
much closer to the bulk. We propose that this is because of the relative lack
of distinct sector identity in the market, with the movement of stocks
dominantly influenced by the overall market trend. This is shown by explicit
construction of the interaction network in the market, first by generating the
minimum spanning tree from the unfiltered correlation matrix, and later, using
an improved method of generating the graph after filtering out the market mode
and random effects from the data. Both methods show, compared to developed
markets, the relative absence of clusters of co-moving stocks that belong to
the same business sector. This is consistent with the general belief that
emerging markets tend to be more correlated than developed markets.Comment: 15 pages, 8 figures, to appear in Proceedings of International
Workshop on "Econophysics & Sociophysics of Markets & Networks"
(Econophys-Kolkata III), Mar 12-15, 200
Mice with cleavage-resistant N-cadherin exhibit synapse anomaly in the hippocampus and outperformance in spatial learning tasks
N-cadherin is a homophilic cell adhesion molecule that stabilizes excitatory synapses, by connecting pre- and post-synaptic termini. Upon NMDA receptor (NMDAR) activation by glutamate, membrane-proximal domains of N-cadherin are cleaved serially by a-disintegrin-and-metalloprotease 10 (ADAM10) and then presenilin 1(PS1, catalytic subunit of the γ-secretase complex). To assess the physiological significance of the initial N-cadherin cleavage, we engineer the mouse genome to create a knock-in allele with tandem missense mutations in the mouse N-cadherin/Cadherin-2 gene (Cdh2 R714G, I715D, or GD) that confers resistance on proteolysis by ADAM10 (GD mice). GD mice showed a better performance in the radial maze test, with significantly less revisiting errors after intervals of 30 and 300 s than WT, and a tendency for enhanced freezing in fear conditioning. Interestingly, GD mice reveal higher complexity in the tufts of thorny excrescence in the CA3 region of the hippocampus. Fine morphometry with serial section transmission electron microscopy (ssTEM) and three-dimensional (3D) reconstruction reveals significantly higher synaptic density, significantly smaller PSD area, and normal dendritic spine volume in GD mice. This knock-in mouse has provided in vivo evidence that ADAM10-mediated cleavage is a critical step in N-cadherin shedding and degradation and involved in the structure and function of glutamatergic synapses, which affect the memory function
Primary proton spectrum between 200 TeV and 1000 TeV observed with the Tibet burst detector and air shower array
Since 1996, a hybrid experiment consisting of the emulsion chamber and burst
detector array and the Tibet-II air-shower array has been operated at
Yangbajing (4300 m above sea level, 606 g/cm^2) in Tibet. This experiment can
detect air-shower cores, called as burst events, accompanied by air showers in
excess of about 100 TeV. We observed about 4300 burst events accompanied by air
showers during 690 days of operation and selected 820 proton-induced events
with its primary energy above 200 TeV using a neural network method. Using this
data set, we obtained the energy spectrum of primary protons in the energy
range from 200 to 1000 TeV. The differential energy spectrum obtained in this
energy region can be fitted by a power law with the index of -2.97 0.06,
which is steeper than that obtained by direct measurements at lower energies.
We also obtained the energy spectrum of helium nuclei at particle energies
around 1000 TeV.Comment: 25 pages, 22 figures, Accepted for publication in Phys. Rev.
U.S. stock market interaction network as learned by the Boltzmann Machine
We study historical dynamics of joint equilibrium distribution of stock
returns in the U.S. stock market using the Boltzmann distribution model being
parametrized by external fields and pairwise couplings. Within Boltzmann
learning framework for statistical inference, we analyze historical behavior of
the parameters inferred using exact and approximate learning algorithms. Since
the model and inference methods require use of binary variables, effect of this
mapping of continuous returns to the discrete domain is studied. The presented
analysis shows that binarization preserves market correlation structure.
Properties of distributions of external fields and couplings as well as
industry sector clustering structure are studied for different historical dates
and moving window sizes. We found that a heavy positive tail in the
distribution of couplings is responsible for the sparse market clustering
structure. We also show that discrepancies between the model parameters might
be used as a precursor of financial instabilities.Comment: 15 pages, 17 figures, 1 tabl
Observation of Multi-Tev Gamma Rays from the Crab Nebula Using the Tibet Air Shower Array
The Tibet experiment, operating at Yangbajing (4,300 m above sea level), is
the lowest energy air shower array and the new high density array constructed
in 1996 has sensitivity to -ray air showers at energies as low as 3
TeV. With this new array, the Crab Nebula was observed in multi-TeV
-rays and a signal was detected at the 5.5 level. We also
obtained the energy spectrum of -rays in the energy region above 3 TeV
which partially overlaps those observed with imaging atmospheric Cherenkov
telescopes. This is the first observation of -ray signals from point
sources with a conventional air shower array using scintillation detectors.Comment: 9 pages, 4 figures, Accepted for publication in ApJ Letter
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