667 research outputs found
Analysis of stock market indices through multidimensional scaling
We propose a graphical method to visualize possible time-varying correlations between fifteen
stock market values. The method is useful for observing stable or emerging clusters of
stock markets with similar behaviour. The graphs, originated from applying multidimensional
scaling techniques (MDS), may also guide the construction of multivariate econometric
models
Analysis of financial data series using fractional Fourier transform and multidimensional scaling
The goal of this study is the analysis of
the dynamical properties of financial data series from
worldwide stock market indexes during the period
2000–2009. We analyze, under a regional criterium,
ten main indexes at a daily time horizon. The methods
and algorithms that have been explored for the
description of dynamical phenomena become an effective
background in the analysis of economical data.
We start by applying the classical concepts of signal
analysis, fractional Fourier transform, and methods of
fractional calculus. In a second phase we adopt the
multidimensional scaling approach. Stock market indexes
are examples of complex interacting systems for
which a huge amount of data exists. Therefore, these
indexes, viewed from a different perspectives, lead to
new classification patterns
Analysis of stock market indices with multidimensional scaling and wavelets
Stock market indices SMIs are important measures of financial and economical performance.
Considerable research efforts during the last years demonstrated that these signals have a chaotic
nature and require sophisticated mathematical tools for analyzing their characteristics. Classical
methods, such as the Fourier transform, reveal considerable limitations in discriminating different
periods of time. This paper studies the dynamics of SMI by combining the wavelet transform
and the multidimensional scaling MDS . Six continuous wavelets are tested for analyzing the
information content of the stock signals. In a first phase, the real Shannon wavelet is adopted for
performing the evaluation of the SMI dynamics, while their comparison is visualized by means of
the MDS. In a second phase, the other wavelets are also tested, and the corresponding MDS plots
are analyzed
Power law analysis of financial index dynamics
Power law PL and fractional calculus are two faces of phenomena with long memory behavior.
This paper applies PL description to analyze different periods of the business cycle. With such
purpose the evolution of ten important stock market indices DAX, Dow Jones, NASDAQ, Nikkei,
NYSE, S&P500, SSEC, HSI, TWII, and BSE over time is studied. An evolutionary algorithm is
used for the fitting of the PL parameters. It is observed that the PL curve fitting constitutes a good
tool for revealing the signal main characteristics leading to the emergence of the global financial
dynamic evolution
Analysis of financial indices by means of the windowed Fourier transform
The goal of this study is to analyze the dynamical
properties of financial data series from nineteen worldwide
stock market indices (SMI) during the period 1995–2009.
SMI reveal a complex behavior that can be explored since it
is available a considerable volume of data. In this paper is
applied the window Fourier transform and methods of fractional
calculus. The results reveal classification patterns typical
of fractional order systems
Role of SPARC in Bone Remodeling and Cancer‐Related Bone Metastasis
There is a growing socioeconomic recognition that clinical bone diseases such as bone infections, bone tumors and osteoporotic bone loss mainly
associated with ageing, are major issues in today0s society. SPARC (secreted protein, acidic and rich in cysteine), a matricellular glycoprotein,
may be a promising therapeutic target for preventing or treating bone‐related diseases. In fact, SPARC is associated with tissue remodeling,
repair, development, cell turnover, bone mineralization and may also participate in growth and progression of tumors, namely cancer‐related
bone metastasis. Yet, the function of SPARC in such biological processes is poorly understood and controversial. The main objective of this work
is to review the current knowledge related to the activity of SPARC in bone remodeling, tumorigenesis, and bone metastasis. Progress in
understanding SPARC biology may provide novel strategies for bone regeneration and the development of anti‐angiogenic, anti‐proliferative, or
counter‐adhesive treatments specifically against bone metastasis
Matrix Converter-Based Unified Power-Flow Controllers: Advanced Direct Power Control Method
This paper presents a direct power control (DPC) for three-phase matrix converters operating as unified power flow controllers (UPFCs). Matrix converters (MCs) allow the direct ac/ac power conversion without dc energy storage links; therefore, the MC-based UPFC (MC-UPFC) has reduced volume and cost, reduced capacitor power losses, together with higher reliability. Theoretical principles of direct power control (DPC) based on sliding mode control techniques are established for an MC-UPFC dynamic model including the input filter. As a result, line active and reactive power, together with ac supply reactive power, can be directly controlled by selecting an appropriate matrix converter switching state guaranteeing good steady-state and dynamic responses. Experimental results of DPC controllers for MC-UPFC show decoupled active and reactive power control, zero steady-state tracking error, and fast response times. Compared to an MC-UPFC using active and reactive power linear controllers based on a modified Venturini high-frequency PWM modulator, the experimental results of the advanced DPC-MC guarantee faster responses without overshoot and no steady-state error, presenting no cross-coupling in dynamic and steady-state responses
A buck-boost converter with extended duty-cycle range in the buck voltage region for renewable energy sources
Buck-boost DC-DC converters are useful as DC grid interfaces for renewable energy resources. In the classical buck-boost converter, output voltages smaller than the input voltage (the buck region) are observed for duty cycles between 0 and 0.5. Several recent buck-boost converters have been designed to present higher voltage gains. Nevertheless, those topologies show a reduced duty-cycle range, leading to output voltages in the buck region, and thus require the use of very low duty cycles to achieve the lower range of buck output voltages. In this work, we propose a new buck-boost DC-DC converter that privileges the buck region through the extension of the duty-cycle range, enabling buck operation. In fact, the converter proposed here allows output voltages below the input voltage even with duty cycles higher than 0.6. We present the analysis, design, and testing of the extended buck-boost DC-DC converter. Several tests were conducted to illustrate the characteristics of the extended buck-boost DC-DC converter. Test results were obtained using both simulation software and a laboratory prototype.info:eu-repo/semantics/publishedVersio
Direct Power Control of Matrix Converter Based Unified Power Flow Controllers
This paper presents the Direct Power Control of Three-Phase Matrix Converters (DPC-MC) operating as Unified Power Flow Controllers (UPFC). Since matrix converters allow direct AC/AC power conversion without intermediate energy storage link, the resulting UPFC has reduced volume and cost, together with higher reliability. Theoretical principles of DPC-MC method are established based on an UPFC model, together with a new direct power control approach based on sliding mode control techniques. As a result, active and reactive power can be directly controlled by selection of an appropriate switching state of matrix converter. This new direct power control approach associated to matrix converters technology guarantees decoupled active and reactive power control, zero error tracking, fast response times and timely control actions. Simulation results show good performance of the proposed system
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