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

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.

Energy consumption, economic growth, foreign direct investment and globalization causality nexus in OECD countries: a symbolic transfer entropy analysis

In this paper, we investigate the validity and usefulness of the symbolic transfer entropy (STE) test for longitudinal data by examining causality relationships among foreign direct investment, energy consumption, globalization and economic growth respectively, between the periods 1970-2015 using Organization for Economic Co-operation and Development (OECD) countries as a case study. Also, a comparison to validate or contrast with other existing studies results generated using other forms of causality test is given. Our findings suggest that the STE causality test is suitable approach for our OECD panel of countries.

What Drives Bitcoin? An Approach from Continuous Local Transfer Entropy and Deep Learning Classification Models

Bitcoin has attracted attention from different market participants due to unpredictable price patterns. Sometimes, the price has exhibited big jumps. Bitcoin prices have also had extreme, unexpected crashes. We test the predictive power of a wide range of determinants on bitcoins’ price direction under the continuous transfer entropy approach as a feature selection criterion. Accordingly, the statistically significant assets in the sense of permutation test on the nearest neighbour estimation of local transfer entropy are used as features or explanatory variables in a deep learning classification model to predict the price direction of bitcoin. The proposed variable selection do not find significative the explanatory power of NASDAQ and Tesla. Under different scenarios and metrics, the best results are obtained using the significant drivers during the pandemic as validation. In the test, the accuracy increased in the post-pandemic scenario of July 2020 to January 2021 without drivers. In other words, our results indicate that in times of high volatility, Bitcoin seems to self-regulate and does not need additional drivers to improve the accuracy of the price direction.

Effective transfer entropy to measure information flows in credit markets

In 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.

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

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.