scholarly journals Information Flow between Bitcoin and Other Investment Assets

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1116 ◽  
Author(s):  
Jang ◽  
Yi ◽  
Kim ◽  
Ahn
Keyword(s):  
Granger Causality ◽  
Information Flow ◽  
Transfer Entropy ◽  
Asset Markets ◽  
Theoretic Approach ◽  
Causality Test ◽  
Information Theoretic ◽  
Symbolic Transfer Entropy ◽  
Information Theoretic Approach

This paper studies the causal relationship between Bitcoin and other investment assets. We first test Granger causality and then calculate transfer entropy as an information-theoretic approach. Unlike the Granger causality test, we discover that transfer entropy clearly identifies causal interdependency between Bitcoin and other assets, including gold, stocks, and the U.S. dollar. However, for symbolic transfer entropy, the dynamic rise–fall pattern in return series shows an asymmetric information flow from other assets to Bitcoin. Our results imply that the Bitcoin market actively interacts with major asset markets, and its long-term equilibrium, as a nascent market, gradually synchronizes with that of other investment assets.

An information-theoretic approach to study fluid–structure interactions

2018 ◽  
Vol 848 ◽  
pp. 968-986 ◽  
Author(s):  
Peng Zhang ◽  
Maxwell Rosen ◽  
Sean D. Peterson ◽  
Maurizio Porfiri
Keyword(s):  
Information Transfer ◽  
Transfer Entropy ◽  
The Other ◽  
Theoretic Approach ◽  
Fluid Structure Interactions ◽  
Fluid Medium ◽  
Fluid Structure ◽  
Information Theoretic ◽  
Model Free ◽  
Information Theoretic Approach

The question of causality is pervasive to fluid–structure interactions, where it finds its most alluring instance in the study of fish swimming in coordination. How and why fish align their bodies, synchronize their motion, and position in crystallized formations are yet to be fully understood. Here, we posit a model-free approach to infer causality in fluid–structure interactions through the information-theoretic notion of transfer entropy. Given two dynamical units, transfer entropy quantifies the reduction of uncertainty in predicting the future state of one of them due to additional knowledge about the past of the other. We demonstrate our approach on a system of two tandem airfoils in a uniform flow, where the pitch angle of one airfoil is actively controlled while the other is allowed to passively rotate. Through transfer entropy, we seek to unveil causal relationships between the airfoils from information transfer conducted by the fluid medium.

A Transfer Entropy Based Approach for Fault Isolation in Industrial Robots

2021 ◽  
pp. 1-23
Author(s):  
Sathish Vallachira ◽  
Mikael Norrlof ◽  
Michal Orkisz ◽  
Sachit Butail
Keyword(s):  
Friction Coefficient ◽  
Spot Welding ◽  
Fault Isolation ◽  
Industrial Robots ◽  
Transfer Entropy ◽  
Theoretic Approach ◽  
Information Theoretic ◽  
Robotic Simulation ◽  
Pick And Place ◽  
Information Theoretic Approach

Abstract In this paper, we cast the problem of fault isolation in industrial robots as that of causal analysis within coupled dynamical processes and evaluate the efficacy of the information theoretic approach of transfer entropy. To create a realistic and exhaustive dataset, we simulate wear induced failure by increasing friction coefficient on select axes within an in-house robotic simulation tool that incorporates an elastic gearbox model. The source axis of failure is identified as one which has the highest net transfer entropy across all pairs of axes. In an exhaustive simulation study, we vary the friction successively in each axis across three common industrial tasks: pick and place, spot welding, and arc welding. Our results show that transfer entropy based approach is able to detect the axis of failure more than 80 percent of the time when the friction coefficient is 5% above the nominal value and always when friction coefficient is 10% above the nominal value. The transfer entropy approach is more than twice as accurate as cross-correlation, a classical time-series analysis used to identify directional dependence among processes.

scholarly journals Entanglement revive and information flow within the decoherent environment

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jia-dong Shi ◽  
Dong Wang ◽  
Liu Ye
Keyword(s):  
Information Flow ◽  
Composite System ◽  
Theoretic Approach ◽  
Noisy Environment ◽  
Bipartite Entanglement ◽  
State Information ◽  
Information Theoretic ◽  
Correlation Distribution ◽  
Information Theoretic Approach ◽  
Insight Into

Abstract In this paper, the dynamics of entanglement is investigated in the presence of a noisy environment. We reveal its revival behavior and probe the mechanisms of this behavior via an information-theoretic approach. By analyzing the correlation distribution and the information flow within the composite system including the qubit subsystem and a noisy environment, it has been found that the subsystem-environment coupling can induce the quasi-periodic entanglement revival. Furthermore, the dynamical relationship among tripartite correlations, bipartite entanglement and local state information is explored, which provides a new insight into the non-Markovian mechanisms during the evolution.

scholarly journals Maternal and offspring effects on the timing of parturition in western Steller sea lions (Eumetopias jubatus)

2018 ◽  
Vol 96 (4) ◽  
pp. 333-339 ◽  
Author(s):  
John M. Maniscalco ◽  
Pamela Parker
Keyword(s):  
Random Effect ◽  
Theoretic Approach ◽  
Eumetopias Jubatus ◽  
Steller Sea Lions ◽  
Information Theoretic ◽  
Sea Lions ◽  
Limited Support ◽  
Long Term Trends ◽  
Information Theoretic Approach

Identifying factors that affect the timing of parturition among annual breeders is important to aid our understanding of how variations may adversely affect population trends over both short and long temporal scales. We investigated the effect of several parameters on the timing of parturition among individual Steller sea lions (Eumetopias jubatus (Schreber, 1776)) over 6 years between 2005 and 2016 using an information–theoretic approach. In addition to the random effect of year, birth and care of a pup in the previous year had the largest effect on parturition, causing a 2.4 day delay. Maternal age was negatively correlated with timing of parturition and male pups were born nearly a day earlier than female pups, on average. There was limited support for effects of sex and mass, with heavier pups born marginally earlier than lighter ones. This study illustrates some of the complexity of variables that can influence the timing of birth in this species and which should be considered in models that attempt to identify long-term trends in changing marine ecosystems.

scholarly journals Transfer entropy as a tool for inferring causality from observational studies in epidemiology

2017 ◽  
Author(s):  
N. Ahmad Aziz
Keyword(s):  
Information Flow ◽  
Observational Studies ◽  
Epidemiological Data ◽  
Entropy Method ◽  
Transfer Entropy ◽  
Theoretic Approach ◽  
Information Theoretic ◽  
Clear Cut ◽  
Model Free ◽  
Obesity And Diabetes

AbstractRecently Wiener’s causality theorem, which states that one variable could be regarded as the cause of another if the ability to predict the future of the second variable is enhanced by implementing information about the preceding values of the first variable, was linked to information theory through the development of a novel metric called ‘transfer entropy’. Intuitively, transfer entropy can be conceptualized as a model-free measure of directed information flow from one variable to another. In contrast, directionality of information flow is not reflected in traditional measures of association which are completely symmetric by design. Although information theoretic approaches have been applied before in epidemiology, their value for inferring causality from observational studies is still unknown. Therefore, in the present study we use a set of simulation experiments, reflecting the most classical and widely used epidemiological observational study design, to validate the application of transfer entropy in epidemiological research. Moreover, we illustrate the practical applicability of this information theoretic approach to ‘real-world’ epidemiological data by demonstrating that transfer entropy is able to extract the correct direction of information flow from longitudinal data concerning two well-known associations, i.e. that between smoking and lung cancer and that between obesity and diabetes risk. In conclusion, our results provide proof-of-concept that the recently developed transfer entropy method could be a welcome addition to the epidemiological armamentarium, especially to dissect those situations in which there is a well-described association between two variables but no clear-cut inclination as to the directionality of the association.

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