scholarly journals INFORMATION FLOWS IN CAUSAL NETWORKS

2008 ◽  
Vol 11 (01) ◽  
pp. 17-41 ◽  
Author(s):  
NIHAT AY ◽  
DANIEL POLANI
Keyword(s):  
Information Flow ◽  
Causal Effect ◽  
Fundamental Concept ◽  
Transfer Entropy ◽  
Information Flows ◽  
Causal Independence ◽  
Causal Networks

We use a notion of causal independence based on intervention, which is a fundamental concept of the theory of causal networks, to define a measure for the strength of a causal effect. We call this measure "information flow" and compare it with known information flow measures such as transfer entropy.

scholarly journals Applying transfer entropy approach to investigate the information flow among ASEAN stock markets

2020 ◽  
Vol 4 (1) ◽  
pp. First
Author(s):  
Tran Thi Tuan Anh
Keyword(s):  
Information Flow ◽  
Stock Markets ◽  
Investment Strategy ◽  
The Philippines ◽  
Transfer Entropy ◽  
The Other ◽  
Information Flows ◽  
Research Results ◽  
Region Data ◽  
Asean Countries

This paper uses transfer entropy to measure and identify the information flows between stock markets in the ASEAN region. Data on daily closing stock indices, including Vietnam, the Philippines, Malaysia, Indonesia, Thailand, and Singapore, are collected for the period from March 2012 to October 2019 to calculate these transfer entropies. The research results of this article can be considered in two aspects: one is, how information flow originating from one market will be accepted by other markets and secondly, information flow that markets receive. From the perspective of incoming transfer entropy, Vietnam is the country most affected by information from the other ASEAN markets while Indonesia and Malaysia are the least affected. In terms of outgoing entropy, Thailand is the largest source of information flow to the ASEAN markets. Malaysia and the Philippines are the two countries that receive minor information impact from other countries. The research also reveals that the Singapore stock market is rather separate from the other ASEAN countries. The research results also imply that, for investors and policymakers, defining the information flows among ASEAN stock markets can help to predict market movements, thereby developing a suitable investment strategy or establishing appropriate management policies.

scholarly journals Comparative performance of mutual information and transfer entropy for analyzing the balance of information flow and energy consumption at synapses

2020 ◽  
Author(s):  
Mireille Conrad ◽  
Renaud B Jolivet
Keyword(s):  
Information Theory ◽  
Mutual Information ◽  
Information Flow ◽  
Experimental Finding ◽  
Brain Regions ◽  
Transfer Entropy ◽  
Information Flows ◽  
Experimental Conditions ◽  
Information Theoretic ◽  
Thalamic Relay

AbstractInformation theory has become an essential tool of modern neuroscience. It can however be difficult to apply in experimental contexts when acquisition of very large datasets is prohibitive. Here, we compare the relative performance of two information theoretic measures, mutual information and transfer entropy, for the analysis of information flow and energetic consumption at synapses. We show that transfer entropy outperforms mutual information in terms of reliability of estimates for small datasets. However, we also show that a detailed understanding of the underlying neuronal biophysics is essential for properly interpreting the results obtained with transfer entropy. We conclude that when time and experimental conditions permit, mutual information might provide an easier to interpret alternative. Finally, we apply both measures to the study of energetic optimality of information flow at thalamic relay synapses in the visual pathway. We show that both measures recapitulate the experimental finding that these synapses are tuned to optimally balance information flowing through them with the energetic consumption associated with that synaptic and neuronal activity. Our results highlight the importance of conducting systematic computational studies prior to applying information theoretic tools to experimental data.Author summaryInformation theory has become an essential tool of modern neuroscience. It is being routinely used to evaluate how much information flows from external stimuli to various brain regions or individual neurons. It is also used to evaluate how information flows between brain regions, between neurons, across synapses, or in neural networks. Information theory offers multiple measures to do that. Two of the most popular are mutual information and transfer entropy. While these measures are related to each other, they differ in one important aspect: transfer entropy reports a directional flow of information, as mutual information does not. Here, we proceed to a systematic evaluation of their respective performances and trade-offs from the perspective of an experimentalist looking to apply these measures to binarized spike trains. We show that transfer entropy might be a better choice than mutual information when time for experimental data collection is limited, as it appears less affected by systematic biases induced by a relative lack of data. Transmission delays and integration properties of the output neuron can however complicate this picture, and we provide an example of the effect this has on both measures. We conclude that when time and experimental conditions permit, mutual information – especially when estimated using a method referred to as the ‘direct’ method – might provide an easier to interpret alternative. Finally, we apply both measures in the biophysical context of evaluating the energetic optimality of information flow at thalamic relay synapses in the visual pathway. We show that both measures capture the original experimental finding that those synapses are tuned to optimally balance information flowing through them with the concomitant energetic consumption associated with that synaptic and neuronal activity.

scholarly journals Non-disclosure for distributed mobile code

2011 ◽  
Vol 21 (6) ◽  
pp. 1111-1181
Author(s):  
ANA ALMEIDA MATOS ◽  
JAN CEDERQUIST
Keyword(s):  
Programming Language ◽  
Information Flow ◽  
Flow Property ◽  
Mobile Code ◽  
Information Flows ◽  
Distributed Programs ◽  
Security Issues ◽  
Code Mobility ◽  
Global Computing ◽  
Language Based Security

With the emergence of the new possibilities offered by global computing, new security issues follow from the fact that these possibilities can be equally exploited by parties with malicious intentions. Many attacks arise at the application level, and can be tackled by means of programming language techniques. For instance, confidentiality can be violated during the execution of programs that reveal secret information. This kind of program behaviour can be avoided by information flow analyses that detect the encoding of illegal flows.This paper studies information flows that occur in distributed programs with code mobility from a language-based security perspective. New forms of security leaks that are introduced by code mobility, which we callmigration leaks, are presented and compared with well-known forms of illegal flow. We propose an information flow property that is adequate for networks consisting of a generalisation of the non-disclosure policy. We design a type and effect system for enforcing it on an expressive distributed calculus, and explain a soundness proof methodology in detail.

ASSOCIATION-BASED INFORMATION FLOW CONTROL IN OBJECT-ORIENTED SYSTEMS

2004 ◽  
Vol 14 (03) ◽  
pp. 291-322
Author(s):  
SHIH-CHIEN CHOU ◽  
YING-KAI WEN
Keyword(s):  
Flow Control ◽  
Information Flow ◽  
Information Leakage ◽  
Object Oriented ◽  
Control Model ◽  
Program Execution ◽  
Information Flows ◽  
Information Flow Control ◽  
Object Oriented Systems

Controlling information flows to prevent information leakage within an application is essential. According to the maturity of object-oriented techniques, many models were developed for the control in object-oriented systems. Since objects may be dynamically instantiated during program execution, controlling information flows among objects is difficult. Our research revealed that association is useful in the control. We developed an association-based information flow control model for object-oriented systems. It precisely controls information flows among objects through associations and constraints. It also offers features such as controlling method invocation through argument sensitivity, allowing declassification, allowing purpose-oriented method invocation, and precisely controlling write access. This paper proposes the model and the implementation of the model, which is composed of the language AbFlow (association-based flow) and its supporting environment.

Supply chain information governance: toward a conceptual framework

2019 ◽  
Vol 30 (2) ◽  
pp. 506-526 ◽  
Author(s):  
Joonhwan In ◽  
Randy Bradley ◽  
Bogdan C. Bichescu ◽  
Chad W. Autry
Keyword(s):  
Supply Chain ◽  
Conceptual Framework ◽  
Information Flow ◽  
Information Quality ◽  
Theoretical Framework ◽  
Performance Outcomes ◽  
Organizational Level ◽  
Information Flows ◽  
Content Type ◽  
Information Governance

Purpose The purpose of this paper is to propose a scalable conceptual framework for governance of supply chain (SC) information flows by re-contextualizing the organizational concept of information governance as an SC concept. Design/methodology/approach This study leverages the strategy-structure-process-performance (SSPP) theory base to explain how effective SC information governance relates to improved internal SC performance. Via an in-depth literature review followed by conceptual theory building, the key features of organizational-level information governance are cast into a theoretical framework. Findings This study presents the theoretical framework that explains how SC information governance should contribute to improved internal SC performance. The proposed framework provides a theoretical basis for future research on SC information governance and would become a useful first step to extend the concept of SC information governance at the SC level. Practical implications SC managers should be aware that information governance mechanisms, rather than the management of basic, information flow-directed processes, to yield the best performance outcomes. Because of the numerous touch points information has in complex SCs, managing the quality of SC information through broader, higher-level governance standards is more important than maximizing connectivity and information flows, and information governance structures/policies across organizations should be designed accordingly. Originality/value This study theoretically links SC information governance and internal SC performance via information quality. It also advances the understanding of SC information flow by challenging the implicit but flawed assumption that uniformity of information quality within the supply chain to create the best outcomes.

scholarly journals Effective transfer entropy to measure information flows in credit markets

2021 ◽  
Author(s):  
Nicoló Andrea Caserini ◽  
Paolo Pagnottoni
Keyword(s):  
Credit Risk ◽  
Bond Market ◽  
Small Sample ◽  
Transfer Entropy ◽  
Information Flows ◽  
Directional Information ◽  
Crisis Period ◽  
Model Free ◽  
Effective Transfer ◽  
Sovereign Bond Markets

AbstractIn this paper we propose to study the dynamics of financial contagion between the credit default swap (CDS) and the sovereign bond markets through effective transfer entropy, a model-free methodology which enables to overcome the required hypotheses of classical price discovery measures in the statistical and econometric literature, without being restricted to linear dynamics. By means of effective transfer entropy we correct for small sample biases which affect the traditional Shannon transfer entropy, as well as we are able to conduct inference on the estimated directional information flows. In our empirical application, we analyze the CDS and bond market data for eight countries of the European Union, and aim to discover which of the two assets is faster at incorporating the information on the credit risk of the underlying sovereign. Our results show a clear and statistically significant prominence of the bond market for pricing the sovereign credit risk, especially during the crisis period. During the post-crisis period, instead, a few countries behave dissimilarly from the others, in particular Spain and the Netherlands.

scholarly journals Quantification of Information Exchange in Idealized and Climate System Applications

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1094
Author(s):  
Praveen Kumar Pothapakula ◽  
Cristina Primo ◽  
Bodo Ahrens
Keyword(s):  
Nonlinear Systems ◽  
Sample Size ◽  
Information Flow ◽  
Air Temperature ◽  
Information Exchange ◽  
Nearest Neighbor ◽  
Climate System ◽  
Transfer Entropy ◽  
K Nearest Neighbor ◽  
Lorenz 96

Often in climate system studies, linear and symmetric statistical measures are applied to quantify interactions among subsystems or variables. However, they do not allow identification of the driving and responding subsystems. Therefore, in this study, we aimed to apply asymmetric measures from information theory: the axiomatically proposed transfer entropy and the first principle-based information flow to detect and quantify climate interactions. As their estimations are challenging, we initially tested nonparametric estimators like transfer entropy (TE)-binning, TE-kernel, and TE k-nearest neighbor and parametric estimators like TE-linear and information flow (IF)-linear with idealized two-dimensional test cases along with their sensitivity on sample size. Thereafter, we experimentally applied these methods to the Lorenz-96 model and to two real climate phenomena, i.e., (1) the Indo-Pacific Ocean coupling and (2) North Atlantic Oscillation (NAO)–European air temperature coupling. As expected, the linear estimators work for linear systems but fail for strongly nonlinear systems. The TE-kernel and TE k-nearest neighbor estimators are reliable for linear and nonlinear systems. Nevertheless, the nonparametric methods are sensitive to parameter selection and sample size. Thus, this work proposes a composite use of the TE-kernel and TE k-nearest neighbor estimators along with parameter testing for consistent results. The revealed information exchange in Lorenz-96 is dominated by the slow subsystem component. For real climate phenomena, expected bidirectional information exchange between the Indian and Pacific SSTs was detected. Furthermore, expected information exchange from NAO to European air temperature was detected, but also unexpected reversal information exchange. The latter might hint to a hidden process driving both the NAO and European temperatures. Hence, the limitations, availability of time series length and the system at hand must be taken into account before drawing any conclusions from TE and IF-linear estimations.

scholarly journals Quantifying the Information Flow between Ghana Stock Market Index and Its Constituents Using Transfer Entropy

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Prince Mensah Osei ◽  
Anokye M. Adam
Keyword(s):  
Stock Market ◽  
Information Flow ◽  
Information Exchange ◽  
Oil And Gas ◽  
Transfer Entropy ◽  
Stock Market Index ◽  
Insurance Sector ◽  
Market Index ◽  
The Individual ◽  
Effective Transfer

We quantify the strength and the directionality of information transfer between the Ghana stock market index and its component stocks as well as observe the same among the individual stocks on the market using transfer entropy. The information flow between the market index and its components and among individual stocks is measured by the effective transfer entropy of the daily logarithm returns generated from the daily market index and stock prices of 32 stocks ranging from 2nd January 2009 to 16th February 2018. We find a bidirectional and unidirectional flow of information between the GSE index and its component stocks, and the stocks dominate the information exchange. Among the individual stocks, SCB is the most active stock in the information exchange as it is the stock that receives the highest amount of information, but the most informative source is EGL (an insurance company) that has the highest net information outflow while the most information sink is PBC that has the highest net information inflow. We further categorize the stocks into 9 stock market sectors and find the insurance sector to be the largest source of information which confirms our earlier findings. Surprisingly, the oil and gas sector is the information sink. Our results confirm the fact that other sectors including oil and gas mitigate their risk exposures through insurance companies and are always expectant of information originating from the insurance sector in relation to regulatory compliance issues. It is our firm conviction that this study would allow stakeholders of the market to make informed buy, sell, or hold decisions.

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