Transfer Entropy Approach for Portfolio Optimization: An Empirical Approach for CESEE Markets

Škrinjarić, Tihana; Quintino, Derick David; Ferreira, Paulo

doi:10.3390/jrfm14080369

Cited by 7 publications

(4 citation statements)

References 41 publications

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“…Transfer entropy has been used for portfolio construction as an alternative way to estimate the correlation between stock market indices [47]. However, in the context of portfolio construction based on network science (using centralities), to the best of our knowledge, we are the first to compare the impact of different ways for estimating the stock correlation network.…”

Section: Significance Of the Study-comparison Of The Key Findings Wit...mentioning

confidence: 99%

“…Therefore, the resulting network is positively weighted and directed with zero self-weights w i↔i = 0. Transfer Entropy is a widely used association measure in finance [47][48][49], biomedical research [50,51], and neuroscience [52,53], as well as other disciplines.…”

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confidence: 99%

“…As we use effective transfer entropy, there is no need to filter the resulting network with some threshold. For the discretization-binning of data (time series of daily returns), we follow the usual method based on the relevance of tails of distributions, which is widely used for financial data [46,47,49].…”

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Portfolio Construction: A Network Approach

Ioannidis,

Sarikeisoglou,

Angelidis

2023

Mathematics

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A key parameter when investing is Time Horizon. One of the biggest mistakes investors make is not aligning the timeline of their goals with their investment portfolio. In other words, time horizons determine the investment portfolio you should construct. We examine which portfolios are the best for long-term investing, short-term investing, and intraday trading. This study presents a novel approach for portfolio construction based on Network Science. We use daily returns of stocks that compose the Dow Jones Industrial Average (DJIA) for a 25-year period from 1998 to 2022. Stock networks are estimated from (i) Pearson correlation (undirected linear statistical correlations), as well as (ii) Transfer Entropy (directed non-linear causal relationships). Portfolios are constructed in two main ways: (a) only four stocks are selected, depending on their centrality, with Markowitz investing weights, or (b) all stocks are selected with centrality-based investing weights. Portfolio performance is evaluated in terms of the following indicators: return, risk (total and systematic), and risk-adjusted return (Sharpe ratio and Treynor ratio). Results are compared against two benchmarks: the index DJIA, and the Markowitz portfolio based on Modern Portfolio Theory. The key findings are as follows: (1) Peripheral portfolios of low centrality stocks based on Pearson correlation network are the best in the long-term, achieving an extremely high cumulative return of around 3000% as well as high risk-adjusted return; (2) Markowitz portfolio is the safest in the long-term, while on the contrary, central portfolios of high centrality stocks based on Pearson correlation network are the riskiest; (3) In times of crisis, no portfolio is always the best. However, portfolios based on Transfer Entropy network perform better in most of the crises; (4) Portfolios of all stocks selected with centrality-based investing weights outperform in both short-term investing and intraday trading. A stock brokerage company may utilize the above findings of our work to enhance its portfolio management services.

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Portfolio Construction: A Network Approach

Ioannidis,

Sarikeisoglou,

Angelidis

2023

Mathematics

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“…The transfer entropy methodology effectively quantifies the reduction in uncertaintyprovided by past values of variablesin predicting the dependent variable, as it is conditioned on these past values, and is considered as a model-free statistic capable of measuring the time-directed transfer of information between stochastic variables as well as providing the asymmetric information transfer measures in multivariate distributions [37]. A number of previous investigations have applied the TE methodology to analyze the financial markets [11,38,39].…”

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The Global Equity Market Reactions of the Oil & Gas Midstream and Marine Shipping Industries to COVID-19: An Entropy Analysis

Nasiri¹,

Nasiri²,

Nasiri³

et al. 2021

HighTech. Innov. J.

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This article quantifies the information flow between major equities in the Oil & Gas Midstream and Marine Shipping industries, on the basis of the effective transfer entropy methodology. In addition, the article provides the first analysis of the investors` fear and market expectations in these sectors, according to Rényi entropy approach. The period of study was extended over five years, to fully capture the pre/post-COVID situations. The entropy results reveal a major change in the underlying information flow pattern among equities in the Oil & Gas Midstream and Marine Shipping sectors, in the aftermath of COVID-19. According to the new (post-COVID) paradigm, the stocks in the Oil & Gas Midstream and Integrated Freight & Logistics industries have gained momentum in occupying six of the ten positions within the list of most-influencing equities in the market, in terms of information transmission. The disorder and randomness has decreased for over 89% of the studied equities, after virus outbreak. For the equities detected with high information-transmission standing, the Rényi entropy results indicate that investors more likely showed higher level of future expectations and lower level of fear regarding frequent market events, within the post-COVID timeline. Doi: 10.28991/HIJ-2021-02-04-07 Full Text: PDF

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Examining the asymmetric information flow between pairs of gold, silver, and oil: a transfer entropy approach

Kayal,

Maiti

2023

SN Bus Econ

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Transfer Entropy Approach for Portfolio Optimization: An Empirical Approach for CESEE Markets

Cited by 7 publications

References 41 publications

Portfolio Construction: A Network Approach

Portfolio Construction: A Network Approach

The Global Equity Market Reactions of the Oil & Gas Midstream and Marine Shipping Industries to COVID-19: An Entropy Analysis

Examining the asymmetric information flow between pairs of gold, silver, and oil: a transfer entropy approach

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