393 research outputs found
On the distribution of high-frequency stock market traded volume: a dynamical scenario
This manuscript reports a stochastic dynamical scenario whose associated
stationary probability density function is exactly a previously proposed one to
adjust high-frequency traded volume distributions. This dynamical conjecture,
physically connected to superstatiscs, which is intimately related with the
current nonextensive statistical mechanics framework, is based on the idea of
local fluctuations in the mean traded volume associated to financial markets
agents herding behaviour. The corroboration of this mesoscopic model is done by
modelising NASDAQ 1 and 2 minute stock market traded volume
Thermoelectrical regulation of microinjection moulds
Microinjection is one of the major replication
techniques for producing low cost micro parts.
The small scale of the microinjection
processes presents different challenges from
those usually encountered in conventional injection
moulding. One particular aspect, very important for
part quality, is mould temperature control.
In conventional injection moulding, the
temperature control system is set to a fixed value
during the injection cycle. In microinjection
moulding such behaviour is not acceptable, which
as lead to the development of “active” control
temperature of the mould named “variotherm”
systems.
In the present paper a study will be presented
for the implementation of thermo electric elements
in dynamic temperature control of microinjection
moulds and its impact on the process cycle time
and part quality
Liquidity and the multiscaling properties of the volume traded on the stock market
We investigate the correlation properties of transaction data from the New
York Stock Exchange. The trading activity f(t) of each stock displays a
crossover from weaker to stronger correlations at time scales 60-390 minutes.
In both regimes, the Hurst exponent H depends logarithmically on the liquidity
of the stock, measured by the mean traded value per minute. All multiscaling
exponents tau(q) display a similar liquidity dependence, which clearly
indicates the lack of a universal form assumed by other studies. The origin of
this behavior is both the long memory in the frequency and the size of
consecutive transactions.Comment: 7 pages, 3 figures, submitted to Europhysics Letter
Statistical mixing and aggregation in Feller diffusion
We consider Feller mean-reverting square-root diffusion, which has been
applied to model a wide variety of processes with linearly state-dependent
diffusion, such as stochastic volatility and interest rates in finance, and
neuronal and populations dynamics in natural sciences. We focus on the
statistical mixing (or superstatistical) process in which the parameter related
to the mean value can fluctuate - a plausible mechanism for the emergence of
heavy-tailed distributions. We obtain analytical results for the associated
probability density function (both stationary and time dependent), its
correlation structure and aggregation properties. Our results are applied to
explain the statistics of stock traded volume at different aggregation scales.Comment: 16 pages, 3 figures. To be published in Journal of Statistical
Mechanics: Theory and Experimen
Why do Hurst exponents of traded value increase as the logarithm of company size?
The common assumption of universal behavior in stock market data can
sometimes lead to false conclusions. In statistical physics, the Hurst
exponents characterizing long-range correlations are often closely related to
universal exponents. We show, that in the case of time series of the traded
value, these Hurst exponents increase logarithmically with company size, and
thus are non-universal. Moreover, the average transaction size shows scaling
with the mean transaction frequency for large enough companies. We present a
phenomenological scaling framework that properly accounts for such
dependencies.Comment: 10 pages, 4 figures, to appear in the Proceedings of the
International Workshop on Econophysics of Stock Markets and Minority Games,
Calcutta, 200
Superstatistical fluctuations in time series: Applications to share-price dynamics and turbulence
We report a general technique to study a given experimental time series with
superstatistics. Crucial for the applicability of the superstatistics concept
is the existence of a parameter that fluctuates on a large time scale
as compared to the other time scales of the complex system under consideration.
The proposed method extracts the main superstatistical parameters out of a
given data set and examines the validity of the superstatistical model
assumptions. We test the method thoroughly with surrogate data sets. Then the
applicability of the superstatistical approach is illustrated using real
experimental data. We study two examples, velocity time series measured in
turbulent Taylor-Couette flows and time series of log returns of the closing
prices of some stock market indices
Accuracy of a teleported trapped field state inside a single bimodal cavity
We propose a simplified scheme to teleport a superposition of coherent states
from one mode to another of the same bimodal lossy cavity. Based on current
experimental capabilities, we present a calculation of the fidelity that can be
achieved, demonstrating accurate teleportation if the mean photon number of
each mode is at most 1.5. Our scheme applies as well for teleportation of
coherent states from one mode of a cavity to another mode of a second cavity,
both cavities embedded in a common reservoir.Comment: 4 pages, 2 figures, in appreciation for publication in Physical
Review
On low-sampling-rate Kramers-Moyal coefficients
We analyze the impact of the sampling interval on the estimation of
Kramers-Moyal coefficients. We obtain the finite-time expressions of these
coefficients for several standard processes. We also analyze extreme situations
such as the independence and no-fluctuation limits that constitute useful
references. Our results aim at aiding the proper extraction of information in
data-driven analysis.Comment: 9 pages, 4 figure
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