Search results for "Time Series Analysi"
showing 7 items of 57 documents
Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development
2005
The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of daily Foreign Exchange rates, Stock Market indices and fixed income instruments by using the generalized Hurst approach. We show that the scaling exponents are associated with characteristics of the specific markets and can be used to differentiate markets in their stage of development. The robustness of the results is tested by both Monte-Carlo studies and a computation of the scaling in the frequency-domain.
Information transfer and information modification to identify the structure of cardiovascular and cardiorespiratory networks
2017
To fully elucidate the complex physiological mechanisms underlying the short-term autonomic regulation of heart period (H), systolic and diastolic arterial pressure (S, D) and respiratory (R) variability, the joint dynamics of these variables need to be explored using multivariate time series analysis. This study proposes the utilization of information-theoretic measures to measure causal interactions between nodes of the cardiovascular/cardiorespiratory network and to assess the nature (synergistic or redundant) of these directed interactions. Indexes of information transfer and information modification are extracted from the H, S, D and R series measured from healthy subjects in a resting…
Multiscale Information Decomposition Dissects Control Mechanisms of Heart Rate Variability at Rest and During Physiological Stress.
2019
Heart rate variability (HRV
Wiener-Granger Causality in Network Physiology with Applications to Cardiovascular Control and Neuroscience
2016
Since the operative definition given by C. W. J. Granger of an idea expressed by N. Wiener, the Wiener–Granger causality (WGC) has been one of the most relevant concepts exploited by modern time series analysis. Indeed, in networks formed by multiple components, working according to the notion of segregation and interacting with each other according to the principle of integration, inferring causality has opened a window on the effective connectivity of the network and has linked experimental evidences to functions and mechanisms. This tutorial reviews predictability improvement, information-based and frequency domain methods for inferring WGC among physiological processes from multivariate…
Land-use changes in an agro-pastoral area (Djougou, Benin) from Landsat archive images (1984 and 2012): a regressive approach combining remote sensin…
2018
Extended abstract:The vegetation of the district of Djougou is affected by large changes due to tree logging, crop field clearing and grazing by increasing numbers of livestock. The dynamics of the landscape is analyzed with a time series of Landsat satellite images (1984-2012). A regressive approach, exploiting the field observations and semi-structured interviews conducted in 2012-2013 in the Bakou-Wewe territory, documents the evolution of land use and facilitates the analysis of Landsat images. An original procedure targets the building of Region of interest (ROIs) for the historic images for which no available field observations exists. The study area is located in central Benin (Plate…
Inferring directionality of coupled dynamical systems using Gaussian process priors: Application on neurovascular systems
2022
Dynamical system theory has recently shown promise for uncovering causality and directionality in complex systems, particularly using the method of convergent cross mapping (CCM). In spite of its success in the literature, the presence of process noise raises concern about CCM's ability to uncover coupling direction. Furthermore, CCM's capacity to detect indirect causal links may be challenged in simulated unidrectionally coupled Rossler-Lorenz systems. To overcome these limitations, we propose a method that places a Gaussian process prior on a cross mapping function (named GP-CCM) to impose constraints on local state space neighborhood comparisons. Bayesian posterior likelihood and…
How news affect the trading behavior of different categories of investors in a financial market
2015
We investigate the trading behavior of a large set of single investors trading the highly liquid Nokia stock over the period 2003-2008 with the aim of determining the relative role of endogenous and exogenous factors that may affect their behavior. As endogenous factors we consider returns and volatility, whereas the exogenous factors we use are the total daily number of news and a semantic variable based on a sentiment analysis of news. Linear regression and partial correlation analysis of data show that different categories of investors are differently correlated to these factors. Governmental and non profit organizations are weakly sensitive to news and returns or volatility, and, typica…