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Open AccessArticle

Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions

by Nikolaos Antonakakis, Ioannis Chatziantoniou and David Gabauer

J. Risk Financial Manag. 2020, 13(4), 84; https://doi.org/10.3390/jrfm13040084 - 24 Apr 2020

Cited by 921 | Viewed by 26001

In this study, we enhance the dynamic connectedness measures originally introduced by Diebold and Yılmaz (2012, 2014) with a time-varying parameter vector autoregressive model (TVP-VAR) which predicates upon a time-varying variance-covariance structure. This framework allows to capture possible changes in the underlying structure of the data in a more flexible and robust manner. Specifically, there is neither a need to arbitrarily set the rolling-window size nor a loss of observations in the calculation of the dynamic measures of connectedness, as no rolling-window analysis is involved. Given that the proposed framework rests on multivariate Kalman filters, it is less sensitive to outliers. Furthermore, we emphasise the merits of this approach by conducting Monte Carlo simulations. We put our framework into practice by investigating dynamic connectedness measures of the four most traded foreign exchange rates, comparing the TVP-VAR results to those obtained from three different rolling-window settings. Finally, we propose uncertainty measures for both TVP-VAR-based and rolling-window VAR-based dynamic connectedness measures. Full article

(This article belongs to the Special Issue Time Series Econometrics)

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18 pages, 12888 KiB

Open AccessArticle

Photons Probe Entropic Potential Variation during Molecular Confinement in Nanocavities

by Vassilios Gavriil, Margarita Chatzichristidi, Zoe Kollia, Alkiviadis-Constantinos Cefalas, Nikolaos Spyropoulos-Antonakakis, Vadim V. Semashko and Evangelia Sarantopoulou

Entropy 2018, 20(8), 545; https://doi.org/10.3390/e20080545 - 24 Jul 2018

Cited by 3 | Viewed by 4019

Abstract

In thin polymeric layers, external molecular analytes may well be confined within tiny surface nano/microcavities, or they may be attached to ligand adhesion binding sites via electrical dipole forces. Even though molecular trapping is followed by a variation of the entropic potential, the experimental evidence of entropic energy variation from molecular confinement is scarce because tiny thermodynamic energy density diverseness can be tracked only by sub-nm surface strain. Here, it is shown that water confinement within photon-induced nanocavities in Poly (2-hydroxyethyl methacrylate), (PHEMA) layers could be trailed by an entropic potential variation that competes with a thermodynamic potential from electric dipole attachment of molecular adsorbates in polymeric ligands. The nano/microcavities and the ligands were fabricated on a PHEMA matrix by vacuum ultraviolet laser photons at 157 nm. The entropic energy variation during confinement of water analytes on the photon processed PHEMA layer was monitored via sub-nm surface strain by applying white light reflectance spectroscopy, nanoindentation, contact angle measurements, Atomic Force Microscopy (AFM) imaging, and surface and fractal analysis. The methodology has the potency to identify entropic energy density variations less than 1 pJm⁻³ and to monitor dipole and entropic fields on biosurfaces. Full article

(This article belongs to the Special Issue Entropy: From Physics to Information Sciences and Geometry)

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