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 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.

ECONOMIC POLICY UNCERTAINTY AND THE BITCOIN MARKET: AN INVESTIGATION IN THE COVID-19 PANDEMIC WITH TRANSFER ENTROPY

2021 ◽  
pp. 1-27
Author(s):  
TOAN LUU DUC HUYNH ◽  
MEI WANG ◽  
VINH XUAN VO
Keyword(s):  
Economic Policy ◽  
Risk Premium ◽  
Trading Volume ◽  
Transfer Entropy ◽  
Policy Uncertainty ◽  
Risk Averse ◽  
Entropy Model ◽  
Economic Policy Uncertainty ◽  
Bid Ask Spread ◽  
Practical Implications

This paper investigates the prediction power of economic policy uncertainty on Bitcoin trading (return, volume, and volatility) over the period from May 2013 to June 2019. We employ the Transfer Entropy model with the following two different regimes (i) stationary and (ii) nonstationary assumption. We construct different algorithm calculations for returns, volume and volatility to test how this proxy impacts. We find that the global Economic Policy Uncertainty negatively causes Bitcoin volumes and volatilities. Therefore, under uncertain regimes, investors are risk-averse to trade, which makes the market less volatile. Our findings confirm the existence of pessimistic risk premium, the theory of deteriorating liquidity and the widen bid-ask spread, which lead to a decline in trading volume under uncertainties in the Bitcoin market. By using different reliable data sources as well as expanding timeframe until May 2020 with COVID-19 pandemic, our results remain robust. Hence, the practical implications will be the useful tools for different parties in the Bitcoin market in the financial turbulence context.

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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