Long memory of volatility measures in time series

The authors analyse relations between the long memory parameter of conditional variance and estimates of the long memory in squared residuals in FIGARCH models. The investigations are performed by means of simulations FIGARCH(0, d, 0) and FIGARCH(1, d, 1) models for selected parameters. Simulation results suggest, that estimates of the conditional variance long memory and the long memory in squared residuals can considerable differ. Moreover, only for small d positive relationship between the long memory estimates of squared residuals and the fractional integration parameter d of FIGARCH model can be observed.FIGARCH, long memory, simulations

Long-run properties of trading volume and volatility of equities listed in DJIA index

In this paper, the authors explain the notion of long memory and report their results concerned with the long memory properties of trading volume and the volatility of stock returns (given by absolute returns and alternatively by square returns) of American companies listed in DJIA index. The contributors focus on calculation of long memory parameters and try to answer the question of whether or not the degree of long memory is the same for the trading volume and for the return volatility data and whether these are fractionally cointegrated. Computations are performed on a daily basis for the whole period from January 1990 to November 2005 and in four sub-periods: January 1990 to December 1993, January 1994 to December 1997, January 1998 to December 2001 and January 2002 to November 2005. We established that for the equities listed in the DJIA index the log-volume (the logarithm of trading volume) and returns volatility exhibit long memory. Moreover, these two series have the same long-memory parameters for most of the equities. This common long memory of both series is especially strongly pronounced in the latest data. On the other hand, there is no evidence that log-volume and volatility share the same long memory component. One important question which arises here concerns the source of long memory in the series. The existence of long memory in the series under investigation may reflect the statistical properties of fundamental factors underlying their behaviour or qualitative changes which take place on stock markets. According to empirical investigations, the growing share of stocks by institutional investors is accompanied by an increasing autocorrelation in returns and trading volume data. On the other hand, long memory is related to autocorrelation. Thus, in our opinion the increasing presence of long memory in the latest American trading-volume data may be caused by the growing share of equities by institutional investors.DJIA, trading volume; univariate and bivariate long memory

Java Based Transistor Level CPU Simulation Speedup Techniques

Transistor level simulation of the CPU, while very accurate, brings also the performance challenge. MOS6502 CPU simulation algorithm is analysed with several optimisation techniques proposed. Application of these techniques improved the transistor level simulation speed by a factor of 3–4, bringing it to the levels on par with fastest RTL-level simulations so far

Visualizing CPU Microarchitecture

Deep understanding of microprocessor architecture, its internal structure and mechanics of its work is essential for engineers in the fields like computer science, integrated circuit design or embedded systems (including microcontrollers). Usually the CPU architecture is presented at the level of ISA, functional decomposition of the chip and data flows. In this paper we propose more tangible, interactive and effective approach to present the CPU microarchitecture. Based on the recent advancements in simulation of MOS6502, one of the most successful microprocessor of all times, that started the personal computing revolution, we present the CPU visualisation framework. The framework supports showing CPU internals at various levels (from single transistor, through logic gates, ending with registers, operation decoders and ALU). It allows for execution of real code and detailed analysis of fetch–decode–execute cycle, measurement of cycles per operation or measurement of the CPU activity factor. The analysis means provided by this framework will also enable us to propose the transistor level simulation speed improvements to the model in the future

Coulomb-driven organization and enhancement of spin-orbit fields in collective spin excitations

Spin-orbit (SO) fields in a spin-polarized electron gas are studied by angle-resolved inelastic light scattering on a CdMnTe quantum well. We demonstrate a striking organization and enhancement of SO fields acting on the collective spin excitation (spin-flip wave). While individual electronic SO fields have a broadly distributed momentum dependence, giving rise to D'yakonov-Perel' dephasing, the collective spin dynamics is governed by a single collective SO field which is drastically enhanced due to many-body effects. The enhancement factor is experimentally determined. These results provide a powerful indication that these constructive phenomena are universal to collective spin excitations of conducting systems.Comment: 5 pages, 4 figure

Magnetization dynamics down to zero field in dilute (Cd,Mn)Te quantum wells

The evolution of the magnetization in (Cd,Mn)Te quantum wells after a short pulse of magnetic field was determined from the giant Zeeman shift of spectroscopic lines. The dynamics in absence of magnetic field was found to be up to three orders of magnitude faster than that at 1 T. Hyperfine interaction and strain are mainly responsible for the fast decay. The influence of a hole gas is clearly visible: at zero field anisotropic holes stabilize the system of Mn ions, while in a magnetic field of 1 T they are known to speed up the decay by opening an additional relaxation channel

Spin order manipulations in nanostructures of II-VI ferromagnetic semiconductors

An overview of recent studies on ferromagnetism in Cr- and Mn-based II-VI diluted magnetic semiconductors is presented emphasizing differences in underlying exchange mechanisms. Examples of manipulations with spin ordering by carrier density, dimensionality, light, and electric field are given.Comment: 6 pages, 7 figures, Proceedings International Conference on Magnetism, Rome 2003, J. Magn. Magn. Mater., in pres