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

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 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 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

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

Heart rate variability behavior in athletes after a sports concussion: A systematic review

Objective This systematic review aims to investigate the adaptations of the autonomic nervous system (ANS) after a concussion by measuring HRV in athletes over the age of 16 after injury. Methods This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). Web of Science, Pubmed, SCOPUS, and Sport Discus were searched using predefined search terms to identify relevant original cross-sectional, longitudinal, and cohort epidemiological studies published before December 2021. Results After screening 1737 potential articles, four studies met the inclusion criteria. Studies included participants with concussion (n = 63) and healthy control athletes (n = 140) who practised different sports. Two studies describe a decrease in HRV following a sports concussion, and one proposed that the resolution of symptoms does not necessarily reflect ANS recovery. Lastly, one study concluded that submaximal exercise induces alteration in ANS, not seen in rest after an injury. Conclusions In the frequency domain, a decrease in high frequency power and an increase of low frequency/high frequency ratio is expected, as the activity of the sympathetic nervous system increases, and the parasympathetic nervous system decreases after injury. In the frequency domain, heart rate variability (HRV) may help monitor the activity of ANS evaluating signals of somatic tissue distress and early identification of other types of musculoskeletal injuries. Further research should investigate the relationship between HRV and other musculoskeletal injuries.info:eu-repo/semantics/publishedVersio

Identifying economic periods and crisis with the multidimensional scaling

This paper applied MDS and Fourier transform to analyze different periods of the business cycle. With such purpose, four important stock market indexes (Dow Jones, Nasdaq, NYSE, S&P500) were studied over time. The analysis under the lens of the Fourier transform showed that the indexes have characteristics similar to those of fractional noise. By the other side, the analysis under the MDS lens identified patterns in the stock markets specific to each economic expansion period. Although the identification of patterns characteristic to each expansion period is interesting to practitioners (even if only in a posteriori fashion), further research should explore the meaning of such regularities and target to find a method to estimate future crisis

Manual de Procedimentos de Trabalho de Campo em Pomares de Cajueiro na Guiné-Bissau

O projeto TCP/GBS/3081 “Apoio à luta contra doenças e pragas do cajueiro na Guiné-Bissau” é uma iniciativa da delegação da FAO na Guiné-Bissau, que conta com a colaboração e apoio técnico-científico dos parceiros portugueses da Universidade de Lisboa, em particular do cE3c (Centre for Ecology, Evolution and Environmental Changes / Faculdade de Ciências) e o LEAF (Linking Landscape, Environment, Agriculture and Food / Instituto Superior de Agronomia). Este projeto tem como objetivo geral identificar os inimigos do cajueiro na Guiné-Bissau, determinar a sua incidência, severidade, e impacto na produtividade dos pomares, com o objetivo final de propor medidas de mitigação e disseminação contra as principais doenças, pragas e parasitas do cajueiro identificados no paísinfo:eu-repo/semantics/publishedVersio