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

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

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 $\beta$ 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

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