66 research outputs found
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
Scaling of the distribution of fluctuations of financial market indices
We study the distribution of fluctuations over a time scale (i.e.,
the returns) of the S&P 500 index by analyzing three distinct databases.
Database (i) contains approximately 1 million records sampled at 1 min
intervals for the 13-year period 1984-1996, database (ii) contains 8686 daily
records for the 35-year period 1962-1996, and database (iii) contains 852
monthly records for the 71-year period 1926-1996. We compute the probability
distributions of returns over a time scale , where varies
approximately over a factor of 10^4 - from 1 min up to more than 1 month. We
find that the distributions for 4 days (1560 mins) are
consistent with a power-law asymptotic behavior, characterized by an exponent
, well outside the stable L\'evy regime . To
test the robustness of the S&P result, we perform a parallel analysis on two
other financial market indices. Database (iv) contains 3560 daily records of
the NIKKEI index for the 14-year period 1984-97, and database (v) contains 4649
daily records of the Hang-Seng index for the 18-year period 1980-97. We find
estimates of consistent with those describing the distribution of S&P
500 daily-returns. One possible reason for the scaling of these distributions
is the long persistence of the autocorrelation function of the volatility. For
time scales longer than days, our results are
consistent with slow convergence to Gaussian behavior.Comment: 12 pages in multicol LaTeX format with 27 postscript figures
(Submitted to PRE May 20, 1999). See
http://polymer.bu.edu/~amaral/Professional.html for more of our work on this
are
Spike-Timing Precision and Neuronal Synchrony Are Enhanced by an Interaction between Synaptic Inhibition and Membrane Oscillations in the Amygdala
The basolateral complex of the amygdala (BLA) is a critical component of the neural circuit regulating fear learning. During fear learning and recall, the amygdala and other brain regions, including the hippocampus and prefrontal cortex, exhibit phase-locked oscillations in the high delta/low theta frequency band (∼2–6 Hz) that have been shown to contribute to the learning process. Network oscillations are commonly generated by inhibitory synaptic input that coordinates action potentials in groups of neurons. In the rat BLA, principal neurons spontaneously receive synchronized, inhibitory input in the form of compound, rhythmic, inhibitory postsynaptic potentials (IPSPs), likely originating from burst-firing parvalbumin interneurons. Here we investigated the role of compound IPSPs in the rat and rhesus macaque BLA in regulating action potential synchrony and spike-timing precision. Furthermore, because principal neurons exhibit intrinsic oscillatory properties and resonance between 4 and 5 Hz, in the same frequency band observed during fear, we investigated whether compound IPSPs and intrinsic oscillations interact to promote rhythmic activity in the BLA at this frequency. Using whole-cell patch clamp in brain slices, we demonstrate that compound IPSPs, which occur spontaneously and are synchronized across principal neurons in both the rat and primate BLA, significantly improve spike-timing precision in BLA principal neurons for a window of ∼300 ms following each IPSP. We also show that compound IPSPs coordinate the firing of pairs of BLA principal neurons, and significantly improve spike synchrony for a window of ∼130 ms. Compound IPSPs enhance a 5 Hz calcium-dependent membrane potential oscillation (MPO) in these neurons, likely contributing to the improvement in spike-timing precision and synchronization of spiking. Activation of the cAMP-PKA signaling cascade enhanced the MPO, and inhibition of this cascade blocked the MPO. We discuss these results in the context of spike-timing dependent plasticity and modulation by neurotransmitters important for fear learning, such as dopamine
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