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Efficiency of the Moscow Stock Exchange before 2022
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 d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497593/ https://www.ncbi.nlm.nih.gov/pubmed/36141070 http://dx.doi.org/10.3390/e24091184 |
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author | Shternshis, Andrey Mazzarisi, Piero Marmi, Stefano |
author_facet | Shternshis, Andrey Mazzarisi, Piero Marmi, Stefano |
author_sort | Shternshis, Andrey |
collection | PubMed |
description | 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 price staleness in empirical data in order to filter out such regularity patterns from return time series. The resulting financial time series of stock returns are then clustered into different groups according to some entropy measures. In particular, we use the Kullback–Leibler distance and a novel entropy metric capturing the co-movements between pairs of stocks. By using Monte Carlo simulations, we are then able to identify the time periods of market inefficiency for a group of 18 stocks. The inefficiency of the Moscow Stock Exchange that we have detected is a signal of the possibility of devising profitable strategies, net of transaction costs. The deviation from the efficient behavior for a stock strongly depends on the industrial sector that it belongs to. |
format | Online Article Text |
id | pubmed-9497593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94975932022-09-23 Efficiency of the Moscow Stock Exchange before 2022 Shternshis, Andrey Mazzarisi, Piero Marmi, Stefano Entropy (Basel) Article 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 price staleness in empirical data in order to filter out such regularity patterns from return time series. The resulting financial time series of stock returns are then clustered into different groups according to some entropy measures. In particular, we use the Kullback–Leibler distance and a novel entropy metric capturing the co-movements between pairs of stocks. By using Monte Carlo simulations, we are then able to identify the time periods of market inefficiency for a group of 18 stocks. The inefficiency of the Moscow Stock Exchange that we have detected is a signal of the possibility of devising profitable strategies, net of transaction costs. The deviation from the efficient behavior for a stock strongly depends on the industrial sector that it belongs to. MDPI 2022-08-25 /pmc/articles/PMC9497593/ /pubmed/36141070 http://dx.doi.org/10.3390/e24091184 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shternshis, Andrey Mazzarisi, Piero Marmi, Stefano Efficiency of the Moscow Stock Exchange before 2022 |
title | Efficiency of the Moscow Stock Exchange before 2022 |
title_full | Efficiency of the Moscow Stock Exchange before 2022 |
title_fullStr | Efficiency of the Moscow Stock Exchange before 2022 |
title_full_unstemmed | Efficiency of the Moscow Stock Exchange before 2022 |
title_short | Efficiency of the Moscow Stock Exchange before 2022 |
title_sort | efficiency of the moscow stock exchange before 2022 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9497593/ https://www.ncbi.nlm.nih.gov/pubmed/36141070 http://dx.doi.org/10.3390/e24091184 |
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