Analysis of financial data series using fractional Fourier transform and multidimensional scaling

Machado, J. A. Tenreiro; Duarte, Fernando B.; Duarte, Gonçalo Monteiro

doi:10.1007/s11071-010-9885-1

Cited by 48 publications

(3 citation statements)

References 22 publications

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“…Regarding the use of MSA for the analysis of financial and economic time series, existing research has relied mainly on Euclidean (Machado et al 2011;Cox 2013) and spectral (Fourier-or wavelet-based) distance metrics (Camacho et al 2006;Aguiar-Conraria and Soares 2011;Aguiar-Conraria et al 2013). Our study is the first to use a time-series distance metric based on a heteroscedasticity-adjusted correlation coefficient.…”

Section: Introductionmentioning

confidence: 99%

Precious Metals Comovements in Turbulent Times: COVID-19 and the Ukrainian Conflict

Michis

2023

JRFM

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We examined the evolution of cross-market linkages between four major precious metals and US stock returns, before (Phase I) and after (Phase II) the COVID-19 outbreak. Phase II was also extended to encompass the Ukrainian conflict, which prolonged the period of uncertainty in financial markets. Due to the increase in volatility observed in Phase II, we used a heteroskedasticity-adjusted correlation coefficient to examine the evolution of correlation changes since the COVID-19 outbreak. We also propose a relevant dissimilarity measure in multidimensional scaling analysis that can be used for depicting associations between financial returns in turbulent times. Our results suggest that (i) the correlation levels of gold, silver, platinum, and palladium returns with US stock returns have not changed substantially since the COVID-19 outbreak, and (ii) all precious metal returns exhibit movements that are less synchronized with US stock returns, with palladium and gold being the least synchronized.

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Section: Introductionmentioning

confidence: 99%

Precious Metals Comovements in Turbulent Times: COVID-19 and the Ukrainian Conflict

Michis

2023

JRFM

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“…El método permite identificar diferentes particularidades de datos, agrupando con parámetros apropiados (3). Junto con la transformada de Fourier, MDS ha sido empleado para identificar patrones en variables económicas (4).…”

Section: Introductionunclassified

Aplicación Del Cálculo Fraccional a Una Serie De Temperaturas De La Zona Andina

Ramos Araujo,

Guerrero Hidalgo

2020

Perf

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Una aproximación para entender los fenómenos con dinámica compleja es el análisis de datos. El escalado multidimensional permite visualizar el comportamiento de los sistemas y capturar su evolución espaciotemporal. Mientras que el cálculo fraccional, aplicado mediante Fractional State Space Portrait permite identificar clústeres en grupos de datos, incluyendo variables meteorológicas como la temperatura. Para ello se ha utilizado la información mutua multivariante para encontrar el orden de derivada óptima que ha dado como resultado una visualización mejorada del sistema dinámico de temperaturas en 11 estaciones meteorológicas de la provincia de Chimborazo durante el año 2015. En el mapa del Fractional State Space Potrait se ha logrado identificar dos grandes clústeres que representan las dos estaciones típicas de un clima tropical ecuatorial. Tales clústeres se encuentran fuertemente influenciados por los diversos microclimas presentes en un territorio heterogéneo.

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“…The multidimensional scaling technique has been used in various areas of research, such as marketing and finance(Fenton &Pearce, 1988 andMachado et al, 2011). Recently, AbdRahman et al (2017) used the technique to indicate the differences between the original WIOD tables and their counterparts produced in a highly automated way, in a virtual laboratory.…”

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confidence: 99%

Multi-level comparisons of input–output tables using cross-entropy indicators

Rahman

Los

Owen

et al. 2021

Economic Systems Research

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We introduce a cross-entropy (CE) indicator to quantify the extent to which two input-output tables or two tables with results based on input-output analysis differ from each other. Our work deploys a unique feature of the CE indicator: it can be decomposed, allowing for matrix comparisons at various levels within one coherent framework. To illustrate the power of this approach, we apply the technique to five multi-region input-output (MRIO) tables for 2011, derived from the Eora, EXIOBASE, GTAP, OECD and WIOD databases. We make pairwise comparisons between MRIOs and between global value chain (GVC) computations based on these MRIOs. We find that answers to questions related to broader aggregates are generally quite similar, but that answers to questions at the level of single industries can be rather different across MRIOs.

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Analysis of financial data series using fractional Fourier transform and multidimensional scaling

Cited by 48 publications

References 22 publications

Precious Metals Comovements in Turbulent Times: COVID-19 and the Ukrainian Conflict

Precious Metals Comovements in Turbulent Times: COVID-19 and the Ukrainian Conflict

Aplicación Del Cálculo Fraccional a Una Serie De Temperaturas De La Zona Andina

Multi-level comparisons of input–output tables using cross-entropy indicators

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