Information Flow Dependence in Financial Markets

In response to empirical evidence, we propose a continuous-time model for multivariate asset returns with a two-layered dependence structure. The price process is subject to multivariate information arrivals driving the market activity modeled by nondecreasing pure-jump Lévy processes. A Lévy copula determines the jump dependence and allows for a generic multivariate information flow with a flexible structure. Conditional on the information flow, asset returns are jointly normal. Within this setup, we provide an estimation framework based on maximum simulated likelihood. We apply novel multivariate models to equity data and obtain estimates which meet an economic intuition with respect to the two-layered dependence structure.

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Exploitation of Information as a Trading Characteristic: A Causality-Based Analysis of Simulated and Financial Data

Entropy ◽

10.3390/e22101139 ◽

2020 ◽

Vol 22 (10) ◽

pp. 1139

Author(s):

Catherine Kyrtsou ◽

Christina Mikropoulou ◽

Angeliki Papana

Keyword(s):

Financial Markets ◽

Empirical Evidence ◽

Information Flow ◽

Diffusion Mechanism ◽

Trading Strategies ◽

Financial Data ◽

Financial Products ◽

Resulting Effect ◽

Causality Tests ◽

Multivariate Systems

In financial markets, information constitutes a crucial factor contributing to the evolution of the system, while the presence of heterogeneous investors ensures its flow among financial products. When nonlinear trading strategies prevail, the diffusion mechanism reacts accordingly. Under these conditions, information englobes behavioral traces of traders’ decisions and represents their actions. The resulting effect of information endogenization leads to the revision of traders’ positions and affects connectivity among assets. In an effort to investigate the computational dimensions of this effect, we first simulate multivariate systems including several scenarios of noise terms, and then we apply direct causality tests to analyze the information flow among their variables. Finally, empirical evidence is provided in real financial data.

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Detection of Information Flow in Major International Financial Markets by Interactivity Network Analysis

Asia-Pacific Financial Markets ◽

10.1007/s10690-010-9133-1 ◽

2010 ◽

Vol 18 (3) ◽

pp. 319-344 ◽

Cited By ~ 3

Author(s):

Abdelwahab Allali ◽

Amor Oueslati ◽

Abdelwahed Trabelsi

Keyword(s):

Network Analysis ◽

Financial Markets ◽

Information Flow ◽

International Financial Markets

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Information Flow Dependence in Return and Trading Volume Across Different Stocks

SSRN Electronic Journal ◽

10.2139/ssrn.3357537 ◽

2019 ◽

Author(s):

Markus Michaelsen

Keyword(s):

Information Flow ◽

Trading Volume ◽

Flow Dependence

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Information Flow from COVID-19 Pandemic to Islamic and Conventional Equities: An ICEEMDAN-Induced Transfer Entropy Analysis

Complexity ◽

10.1155/2021/4917051 ◽

2021 ◽

Vol 2021 ◽

pp. 1-20

Author(s):

Ahmed Bossman

Keyword(s):

Financial Markets ◽

Information Flow ◽

Portfolio Management ◽

Short Term ◽

Data Set ◽

Fund Managers ◽

Steady Growth ◽

Management Techniques ◽

The Impact

With the steady growth in the data set on the COVID-19 pandemic, empirical works that employ novel and yet appropriate statistical techniques to corroborate previous findings of the pandemic and its consequences on financial markets are necessary. This paper examined the impact of COVID-19 information flow on the Islamic and conventional equities within the short-, mid-, and long-term horizons to assess possible diversification prospects in the era of the pandemic. To the studied equities markets, a novel technique based on a denoised frequency-domain entropy paradigm was applied. The operability of entrenched market dynamics in the long-term horizon of the COVID-19 pandemic period is reinforced by the results. The findings divulge diversification opportunities between Islamic and conventional equities in the short- and mid-term periods of the COVID-19 pandemic. The risks on equities from Japan or Bahrain could be diversified by equities from Jordan in the short-term, while in the intermediate-term stocks from Japan could diversify with the UAE and USA equities. The results imply that it is imperative for investors and fund managers to employ portfolio management techniques that show how to use benefits together with risk prevention and management across distinct time scales.

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Information Flow between Global Equities and Cryptocurrencies: A VMD-Based Entropy Evaluating Shocks from COVID-19 Pandemic

Complexity ◽

10.1155/2021/4753753 ◽

2021 ◽

Vol 2021 ◽

pp. 1-25

Author(s):

Emmanuel Asafo-Adjei ◽

Peterson Owusu Junior ◽

Anokye M. Adam

Keyword(s):

Financial Markets ◽

Information Flow ◽

Sample Period ◽

Significant Information ◽

Full Sample ◽

Mode Decomposition ◽

The World ◽

The One ◽

Effective Transfer ◽

Digital Assets

The world has witnessed the adverse impact of the COVID-19 pandemic. Accordingly, it is expected that information transmission between equities and digital assets has been altered due to the hostile impact of the pandemic outbreak on financial markets. As a result, the ensuing perverse risk among markets is presumed to rise during severe uncertainties occasioned by the COVID-19 pandemic. The impetus of this study is to examine the degree of asymmetry and nonlinear directional causality between global equities and cryptocurrencies in the frequency domain. Hence, we employ both the variational mode decomposition (VMD) and the Rényi effective transfer entropy techniques. Analyses of the study are presented for three sample periods; these are the full sample period, the pre-COVID-19 period, and the COVID-19 pandemic period. We gauge a mixture of asymmetric and nonlinear bidirectional and unidirectional causality between global equities and cryptocurrencies for the sample periods. However, the COVID-19 pandemic period appears to be driving the estimates for the full sample period, which indicates a negative flow. Thus, the direction and significance of the information flow between the markets for the full sample correspond to the one observed during the COVID-19 pandemic period. We, consequently, establish a significant directional, dynamical, and scale-dependent information flow between global equities and cryptocurrencies. Notwithstanding, throughout the study samples, we mainly find a negative significant information flow from global equities to cryptocurrencies. We detect that most cryptocurrencies exhibit similar behaviour of information flow to global equities for each of the sample periods. The outcome provides pertinent signals to investors with diverse investment horizons who would want to diversify, hedge, or employ cryptocurrencies as a safe haven for global equities during uncertainties, specifically the COVID-19 pandemic.

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