scholarly journals Effective Transfer Entropy Approach to Information Flow Among EPU, Investor Sentiment and Stock Market

2020 ◽  
Vol 8 ◽  
Author(s):  
Can-Zhong Yao ◽  
Hong-Yu Li
Keyword(s):  
Stock Market ◽  
Information Flow ◽  
Investor Sentiment ◽  
Transfer Entropy ◽  
Effective Transfer

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.

scholarly journals Cross-Sectoral Information Transfer in the Chinese Stock Market around Its Crash in 2015

Entropy ◽  
2018 ◽  
Vol 20 (9) ◽  
pp. 663 ◽  
Author(s):  
Xudong Wang ◽  
Xiaofeng Hui
Keyword(s):  
Stock Market ◽  
Information Flow ◽  
Information Transfer ◽  
Spanning Trees ◽  
Information Source ◽  
Kernel Density ◽  
Transfer Entropy ◽  
Chinese Stock Market ◽  
Technology Sector ◽  
Effective Transfer

This paper applies effective transfer entropy to research the information transfer in the Chinese stock market around its crash in 2015. According to the market states, the entire period is divided into four sub-phases: the tranquil, bull, crash, and post-crash periods. Kernel density estimation is used to calculate the effective transfer entropy. Then, the information transfer network is constructed. Nodes’ centralities and the directed maximum spanning trees of the networks are analyzed. The results show that, in the tranquil period, the information transfer is weak in the market. In the bull period, the strength and scope of the information transfer increases. The utility sector outputs a great deal of information and is the hub node for the information flow. In the crash period, the information transfer grows further. The market efficiency in this period is worse than that in the other three sub-periods. The information technology sector is the biggest information source, while the consumer staples sector receives the most information. The interactions of the sectors become more direct. In the post-crash period, information transfer declines but is still stronger than the tranquil time. The financial sector receives the largest amount of information and is the pivot node.

scholarly journals RTransferEntropy — Quantifying information flow between different time series using effective transfer entropy

SoftwareX ◽  
2019 ◽  
Vol 10 ◽  
pp. 100265 ◽  
Author(s):  
Simon Behrendt ◽  
Thomas Dimpfl ◽  
Franziska J. Peter ◽  
David J. Zimmermann
Keyword(s):  
Time Series ◽  
Information Flow ◽  
Transfer Entropy ◽  
Effective Transfer

scholarly journals Information Flow Analysis between EPU and Other Financial Time Series

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 683
Author(s):  
Can-Zhong Yao
Keyword(s):  
Economic Policy ◽  
Exchange Rate ◽  
Information Flow ◽  
Bilateral Trade ◽  
Financial Time Series ◽  
Flow Analysis ◽  
Transfer Entropy ◽  
Policy Uncertainty ◽  
Novel Concept ◽  
Effective Transfer

We investigate the strength and direction of information flow among economic policy uncertainty (EPU), US imports and exports to China, and the CNY/US exchange rate by using the novel concept of effective transfer entropy (ETE) with a sliding window methodology. We verify that this new method can capture dynamic orders effectively by validating them with the linear transfer entropy (TE) and Granger causality methods. Analysis shows that since 2016, US economic policy has contributed substantially to China-US bilateral trade and that China is making passive adjustments based on this trade volume. Unlike trade market conditions, China’s economic policy has significantly influenced the exchange rate fluctuation since 2016, which has, in turn, affected US economic policy.

scholarly journals Information Flow Between the Zimbabwe Stock Exchange and the Johannesburg Stock Exchange: A Transfer Entropy Approach

2021 ◽  
Vol 12 (2) ◽  
pp. 353-376
Author(s):  
Kingstone Nyakurukwa
Keyword(s):  
Information Flow ◽  
Stock Exchange ◽  
Tail Dependence ◽  
Point Of View ◽  
Transfer Entropy ◽  
Significant Information ◽  
Fund Managers ◽  
Johannesburg Stock Exchange ◽  
Entropy Estimate ◽  
Effective Transfer

The purpose of this paper is to determine whether there was information flow between the stock markets of Zimbabwe and South Africa during the time the Zimbabwean economy was dollarized. The author used econophysics-based Shannonian and Rényian transfer entropy estimates to establish the flow of information between the markets in tranquil periods as well as at the tails of return distributions. The only significant Shannonian transfer entropy estimate was from Johannesburg Stock Exchange (JSE) resources index to Zimbabwe Stock Exchange (ZSE) mining index. The findings show that the only significant tail dependence was between JSE All Share Index (JALSH) and ZSE Mining on the one hand, and between JSE Resources and ZSE Mining on the other hand. However, the magnitudes of the effective transfer entropy values are relatively low, showing that there are weak linkages between the Zimbabwe Stock Exchange and the Johannesburg Stock Exchange. The lack of significant information flows between the exchanges of the two countries offer opportunities to fund managers for portfolio diversification. From a government point of view, it is imperative that the tempo of economic and political reform be accelerated so that integration between the markets can be fast-tracked. Integrated markets will benefit Zimbabwe as this will reduce the cost of equity and accelerate economic growth.

scholarly journals A New EEMD-Effective Transfer Entropy-Based Methodology for Exchange Rate Market Information Transmission in Southern Africa Development Community

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Anokye M. Adam ◽  
Emmanuel N. Gyamfi ◽  
Kwabena A. Kyei ◽  
Simiso Moyo ◽  
Ryan S. Gill
Keyword(s):  
Exchange Rates ◽  
Information Flow ◽  
Monetary Union ◽  
Ensemble Empirical Mode Decomposition ◽  
Transfer Entropy ◽  
Economic Policies ◽  
Monetary Unions ◽  
Low Frequencies ◽  
Southern Africa Development Community ◽  
Effective Transfer

The desire to form monetary unions among regional blocs in Africa has necessitated the need to assess the degree of financial systems interdependencies in Africa economic blocs for their suitability to have harmonised economic policies of eventual monetary unions. In this regard, SADC has pursued policies to harmonise and integrate its financial system as a precursor to its intended monetary union. However, the ensuing risk among exchange rates of economies in SADC is presumed to rise during severe uncertainties. This study examines the degree of asymmetry and nonlinear directional causality between exchange rates in SADC in the frequency domain. We employ both the ensemble empirical mode decomposition (EEMD) and the Rényi effective transfer entropy techniques to investigate the multiscale information that might be disregarded and further quantify the directional flow of information. Analysis of the study is presented for four frequency-domains: high-, medium-, and low frequencies, representing short-, medium-, and long-terms, respectively, in addition to the residue (fundamental feature). We find a mixture of asymmetric and nonlinear bidirectional and unidirectional causality between exchange rates in SADC for the sampled period. The study reveals a significant positive information flow in the high frequency, but negative flow in the medium and low frequencies. In addition, we gauge a bidirectional significant negative information flow within all the 15 economies for the residue. This suggests a higher risk of uncertainties in exchange rates of SADC. Our findings for low probability events at multiscales have implications for the direction of the future of the SADC monetary union. This calls for further sustained policy harmonisation in the region.

scholarly journals Effective transfer entropy approach to information flow between exchange rates and stock markets

2014 ◽  
Vol 68 ◽  
pp. 180-185 ◽  
Author(s):  
Ahmet Sensoy ◽  
Cihat Sobaci ◽  
Sadri Sensoy ◽  
Fatih Alali
Keyword(s):  
Exchange Rates ◽  
Information Flow ◽  
Stock Markets ◽  
Transfer Entropy ◽  
Effective Transfer

scholarly journals Synergistic Information Transfer in the Global System of Financial Markets

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 1000
Author(s):  
Tomas Scagliarini ◽  
Luca Faes ◽  
Daniele Marinazzo ◽  
Sebastiano Stramaglia ◽  
Rosario N. Mantegna
Keyword(s):  
Stock Market ◽  
Granger Causality ◽  
Information Flow ◽  
Information Transfer ◽  
Partial Information ◽  
Higher Order ◽  
Transfer Entropy ◽  
Order Effects ◽  
Target Market ◽  
Stock Market Index

Uncovering dynamic information flow between stock market indices has been the topic of several studies which exploited the notion of transfer entropy or Granger causality, its linear version. The output of the transfer entropy approach is a directed weighted graph measuring the information about the future state of each target provided by the knowledge of the state of each driving stock market index. In order to go beyond the pairwise description of the information flow, thus looking at higher order informational circuits, here we apply the partial information decomposition to triplets consisting of a pair of driving markets (belonging to America or Europe) and a target market in Asia. Our analysis, on daily data recorded during the years 2000 to 2019, allows the identification of the synergistic information that a pair of drivers carry about the target. By studying the influence of the closing returns of drivers on the subsequent overnight changes of target indexes, we find that (i) Korea, Tokyo, Hong Kong, and Singapore are, in order, the most influenced Asian markets; (ii) US indices SP500 and Russell are the strongest drivers with respect to the bivariate Granger causality; and (iii) concerning higher order effects, pairs of European and American stock market indices play a major role as the most synergetic three-variables circuits. Our results show that the Synergy, a proxy of higher order predictive information flow rooted in information theory, provides details that are complementary to those obtained from bivariate and global Granger causality, and can thus be used to get a better characterization of the global financial system.

scholarly journals Susceptibility of Stock Market Returns to International Economic Policy: Evidence from Effective Transfer Entropy of Africa with the Implication for Open Innovation

2020 ◽  
Vol 6 (3) ◽  
pp. 71 ◽  
Author(s):  
Anokye M. Adam
Keyword(s):  
South Africa ◽  
International Economic ◽  
Economic Policy ◽  
Stock Market ◽  
Stock Markets ◽  
Open Innovation ◽  
Transfer Entropy ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Effective Transfer

This study contributes to the scant finance literature on information flow from international economic policy uncertainty to emerging stock markets in Africa, using daily US economic policy uncertainty as a proxy and the daily stock market index for Botswana, Egypt, Ghana, Kenya, Morocco, Nigeria, Namibia, South Africa, and Zambia from 31 December 2010 to 27 May 2020, using the Rényi effective transfer entropy. International economic policy uncertainty transmits significant information to Egypt, Ghana, Morocco, Namibia, and South Africa, and insignificant information to Botswana, Kenya, Nigeria, and Zambia. The asymmetry in the information transfer tends to make the African market an alternative for the diversification of international portfolios when the uncertainty of the global economic policy is on the rise. The findings also have implications for the adoption of open innovation in African stock markets.

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