2022
DOI: 10.3390/e24091184
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Efficiency of the Moscow Stock Exchange before 2022

Abstract: This paper investigates the degree of efficiency for the Moscow Stock Exchange. A market is called efficient if prices of its assets fully reflect all available information. We show that the degree of market efficiency is significantly low for most of the months from 2012 to 2021. We calculate the degree of market efficiency by (i) filtering out regularities in financial data and (ii) computing the Shannon entropy of the filtered return time series. We developed a simple method for estimating volatility and pr… Show more

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Cited by 5 publications
(2 citation statements)
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“…The DTW distance, which is common in fields such as biometrics and computer animation, was used to study the topology of the currency network by Wang et al (2012) [28] and Gupta and Chatterjee (2020) [38]. In Shternshis et al (2022) [48], the clustering of financial time series into different groups according to the Kullback-Leibler entropy measure was performed. Chakraborty et al (2020) [49] examined the relationship between currencies and analyzed network clusters during periods of severe international crises using a method based on the Jensen-Shannon divergence.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The DTW distance, which is common in fields such as biometrics and computer animation, was used to study the topology of the currency network by Wang et al (2012) [28] and Gupta and Chatterjee (2020) [38]. In Shternshis et al (2022) [48], the clustering of financial time series into different groups according to the Kullback-Leibler entropy measure was performed. Chakraborty et al (2020) [49] examined the relationship between currencies and analyzed network clusters during periods of severe international crises using a method based on the Jensen-Shannon divergence.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In 1971, Barclays Investment Management in the United States issued the world's first fund using quantitative investment strategies [11]. The explosive growth and huge development prospects of the current global quantitative trading market have made stock-related time series forecasting a hot research topic [12].…”
Section: Literature Reviewmentioning
confidence: 99%