704 research outputs found
Applications of physical methods in high-frequency futures markets
In the present work we demonstrate the application of different physical
methods to high-frequency or tick-by-tick financial time series data. In
particular, we calculate the Hurst exponent and inverse statistics for the
price time series taken from a range of futures indices. Additionally, we show
that in a limit order book the relaxation times of an imbalanced book state
with more demand or supply can be described by stretched exponential laws
analogous to those seen in many physical systems.Comment: 14 Pages and 10 figures. Proceeding to the SPIE conference, 4 - 7
December 2007 Australian National Univ. Canberra, ACT, Australi
Entropy of the Nordic electricity market: anomalous scaling, spikes, and mean-reversion
The electricity market is a very peculiar market due to the large variety of
phenomena that can affect the spot price. However, this market still shows many
typical features of other speculative (commodity) markets like, for instance,
data clustering and mean reversion. We apply the diffusion entropy analysis
(DEA) to the Nordic spot electricity market (Nord Pool). We study the waiting
time statistics between consecutive spot price spikes and find it to show
anomalous scaling characterized by a decaying power-law. The exponent observed
in data follows a quite robust relationship with the one implied by the DEA
analysis. We also in terms of the DEA revisit topics like clustering,
mean-reversion and periodicities. We finally propose a GARCH inspired model but
for the price itself. Models in the context of stochastic volatility processes
appear under this scope to have a feasible description.Comment: 16 pages, 7 figure
Spurious memory in non-equilibrium stochastic models of imitative behavior
The origin of the long-range memory in the non-equilibrium systems is still
an open problem as the phenomenon can be reproduced using models based on
Markov processes. In these cases a notion of spurious memory is introduced. A
good example of Markov processes with spurious memory is stochastic process
driven by a non-linear stochastic differential equation (SDE). This example is
at odds with models built using fractional Brownian motion (fBm). We analyze
differences between these two cases seeking to establish possible empirical
tests of the origin of the observed long-range memory. We investigate
probability density functions (PDFs) of burst and inter-burst duration in
numerically obtained time series and compare with the results of fBm. Our
analysis confirms that the characteristic feature of the processes described by
a one-dimensional SDE is the power-law exponent of the burst or
inter-burst duration PDF. This property of stochastic processes might be used
to detect spurious memory in various non-equilibrium systems, where observed
macroscopic behavior can be derived from the imitative interactions of agents.Comment: 11 pages, 5 figure
Components of multifractality in high-frequency stock returns
We analyzed multifractal properties of 5-minute stock returns from a period
of over two years for 100 highly capitalized American companies. The two
sources: fat-tailed probability distributions and nonlinear temporal
correlations, vitally contribute to the observed multifractal dynamics of the
returns. For majority of the companies the temporal correlations constitute a
much more significant related factor, however.Comment: to appear in Physica
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