Assessment of Sector Bond, Equity Indices and Green Bond Index Using Information Theory Quantifiers and Clusters Techniques

Fernandes, Leonardo H.S.; Araujo, Fernando Henrique Antunes de; Silva, José W L; Filho, Marcos C. M.; Tabak, Benjamin Miranda

doi:10.1142/s0218348x23500172

Cited by 7 publications

(5 citation statements)

References 47 publications

(78 reference statements)

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“…Other articles by the authors, see: [36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60]…”

Section: Discussionmentioning

confidence: 99%

The (in)efficiency of USA Education Group stocks: before, during and after COVID-19

Fernandes,

Silva

et al. 2024

Preprint

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This paper represents a pioneering effort to investigate multifractal dynamics that exclusively encompass the return time series of USA Education Group Stocks concerning two non-overlapping periods (before, during,. Given this, we employ the Multifractal Detrended Fluctuations Analysis (MF-DFA). In this sense, we investigate the generalized Hurst exponent ℎ(𝑞) and the Rényi exponent 𝜏 (𝑞) for each asset and quantify their statistical properties, which allowed us to observe separately the contributing small scale (primarily via the negative moments 𝑞) and the large scale (via the positive moments 𝑞). We perform a fourth-degree polynomial regression fit to estimate the complexity parameters that describe the degree of multifractality of the underlying process. Also, we shall apply the inefficiency multifractal index to assess the COVID-19 shock for both periods. Our findings show that for both periods, the majority of these assets are marked by multifractal dynamics associated with persistent behaviour (𝛼 0 > 0.5), a higher degree of multifractality and the dominance of large fluctuations. At the same time, most of these assets show asymmetry parameter (𝑅 > 1) for both periods, indicating that large fluctuations contributed more to multifractality in the time series of returns.

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“…Other articles by the authors, see: [36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60]…”

Section: Discussionmentioning

confidence: 99%

The (in)efficiency of USA Education Group stocks: before, during and after COVID-19

Fernandes,

Silva

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Other articles by the authors, see: [23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46]…”

Section: Discussionmentioning

confidence: 99%

The synergic interplay between entropy, predictability, and informational efficiency of the Shanghai sectoral index

Fernandes¹,

Araujo

Silva³

et al. 2023

Preprint

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We explore the synergic interplay between entropy (disorder), predictability, and informational efficiency of the daily closing price time series of 13 sectoral economics components of the Shanghai index letter considering three non-overlapping periods (before and during COVID-19 and Russia-Ukraine war). Our findings reveal that the telecom services, financials, and consumer discretionary sectors are marked by higher informational efficiency. Otherwise, the industrials, utilities, and transportation sectors exhibit lower informational efficiency. These insights are relevant for financial agents to make informed decisions, manage risk, and seek opportunities in an ever-changing market environment.

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“…Other articles by the authors, see: [30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54]…”

Section: Discussionmentioning

confidence: 99%

Quantifying the COVID-19 shock in cryptocurrencies

Fernandes,

Silva,

Bariviera

et al. 2023

Preprint

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This paper sheds light on the changes suffered in cryptocurrencies due to the COVID-19 shock through a non-linear cross-correlations and similarity perspective. We have collected daily price and volume data for the seven largest cryptocurrencies considering trade volume and market capitalization. For both attributes (price and volume), we calculate their volatility and compute the Multifractal Detrended Cross-Correlations (MF-DCCA) to estimate the complexity parameters that describe the degree of multifractality of the underlying process. We detect (before and during COVID-19) a standard multifractal behaviour for these volatility time series pairs and an overall persistent long-term correlation. However, multifractality for price volatility time series pairs displays more persistent behaviour than the volume volatility time series pairs. From a financial perspective, it reveals that the volatility time series pairs for the price are marked by an increase in the non-linear crosscorrelations excluding the pair Bitcoin vs Dogecoin (𝛼 𝑥𝑦 (0) = −1.14%). At the same time, all volatility time series pairs considering the volume attribute are marked by a decrease in the non-linear cross-correlations. The K-means technique indicates that these volatility time series for the price attribute were resilient to the shock of COVID-19. While for these volatility time series for the volume attribute, we find that the COVID-19 shock drove changes in cryptocurrency groups.

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Assessment of Sector Bond, Equity Indices and Green Bond Index Using Information Theory Quantifiers and Clusters Techniques

Cited by 7 publications

References 47 publications

The (in)efficiency of USA Education Group stocks: before, during and after COVID-19

The (in)efficiency of USA Education Group stocks: before, during and after COVID-19

The synergic interplay between entropy, predictability, and informational efficiency of the Shanghai sectoral index

Quantifying the COVID-19 shock in cryptocurrencies

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