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This paper studies the dynamics of Brazilian interest rates for short-term maturities. The paper employs developed techniques in the econophysics literature and tests for long-range dependence in the term structure of these interest rates for the last decade. Empirical results suggest that the degree of long-range dependence has changed over time due to changes in monetary policy, specially in ...

This paper is devoted to establish an invariance principle where the limit process is a multifractional Gaussian process with a multifractional function which takes its values in (1/2,1). Some properties, such as regularity and local self-similarity of this process are studied. Moreover the limit process is compared to the multifractional Brownian motion. Résumé. Ce papier a pour but d’établir ...

We consider an e-business web-server system where the network traffic exhibits self-similarity. We demonstrate that traditional techniques are unsuitable for predicting the network performance under such traffic conditions. Instead, we propose and demonstrate a novel decomposition approximation technique that helps predict delays more accurately and thus is better suited for capacity planning a...

The notion of long range dependence has traditionally been deened through a slow decay of correlations. This approach may be completely inappropriate in the case of a stochastic process with heavy tails. Yet long memory has been reported to be found in various elds where heavy tails are a standard feature of the commonly used stochastic models. Financial and communications networks data are amo...

There has been a growing concern about the potential impact of long-term correlations (second-order statistic) in variable-bit-rate (VBR) video traac on ATM buuer dimen-sioning. Previous studies have shown that video traac exhibits long-range dependence (LRD) (Hurst parameter large than 0.5). We investigate the practical implications of LRD in the context of realistic ATM traac engineering by s...

Over the last few years, the network community has started to make heavy use of novel concepts such as self-similarity and Long-Range Dependence (LRD). Despite their wide use, there is still much confusion regarding the identification of such phenomena in real network traffic data. In this paper, we show that estimating Long-Range Dependence is not straightforward: there is no systematic or def...

Analysis and modeling of computer network traffic is a daunting task considering the amount of available data. This is quite obvious when considering the spatial dimension of the problem, since the number of interacting computers, gateways and switches can easily reach several thousands, even in a Local Area Network (LAN) setting. This is also true for the time dimension: W. Willinger and V. Pa...

Multivariate processes with long-range dependent properties are found in a large number of applications including finance, geophysics and neuroscience. For real data applications, the correlation between time series is crucial. Usual estimations of correlation can be highly biased due to phase-shifts caused by the differences in the properties of autocorrelation in the processes. To address thi...