Evolvement of Uniformity and Volatility in the Stressed Global Financial Village
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{"title"=>"Evolvement of uniformity and volatility in the stressed global financial village", "type"=>"journal", "authors"=>[{"first_name"=>"Dror Y.", "last_name"=>"Kenett", "scopus_author_id"=>"35275313400"}, {"first_name"=>"Matthias", "last_name"=>"Raddant", "scopus_author_id"=>"36574081300"}, {"first_name"=>"Thomas", "last_name"=>"Lux", "scopus_author_id"=>"7003769381"}, {"first_name"=>"Eshel", "last_name"=>"Ben-Jacob", "scopus_author_id"=>"7005078550"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84856755474", "pui"=>"364218406", "doi"=>"10.1371/journal.pone.0031144", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "sgr"=>"84856755474", "pmid"=>"22347444"}, "id"=>"bbfd9b1a-494a-3725-b0b7-a856bc1a62f7", "abstract"=>"BACKGROUND: In the current era of strong worldwide market couplings the global financial village became highly prone to systemic collapses, events that can rapidly sweep throughout the entire village. METHODOLOGY/PRINCIPAL FINDINGS: We present a new methodology to assess and quantify inter-market relations. The approach is based on the correlations between the market index, the index volatility, the market Index Cohesive Force and the meta-correlations (correlations between the intra-correlations.) We investigated the relations between six important world markets--U.S., U.K., Germany, Japan, China and India--from January 2000 until December 2010. We found that while the developed \"western\" markets (U.S., U.K., Germany) are highly correlated, the interdependencies between these markets and the developing \"eastern\" markets (India and China) are volatile and with noticeable maxima at times of global world events. The Japanese market switches \"identity\"--it switches between periods of high meta-correlations with the \"western\" markets and periods when it behaves more similarly to the \"eastern\" markets. CONCLUSIONS/SIGNIFICANCE: The methodological framework presented here provides a way to quantify the evolvement of interdependencies in the global market, evaluate a world financial network and quantify changes in the world inter market relations. Such changes can be used as precursors to the agitation of the global financial village. Hence, the new approach can help to develop a sensitive \"financial seismograph\" to detect early signs of global financial crises so they can be treated before they develop into worldwide events.", "link"=>"http://www.mendeley.com/research/evolvement-uniformity-volatility-stressed-global-financial-village", "reader_count"=>24, "reader_count_by_academic_status"=>{"Researcher"=>4, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>2, "Student > Bachelor"=>1, "Lecturer"=>2, "Professor"=>1}, "reader_count_by_user_role"=>{"Researcher"=>4, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>7, "Student > Postgraduate"=>2, "Student > Master"=>3, "Other"=>2, "Student > Bachelor"=>1, "Lecturer"=>2, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Materials Science"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>2, "Business, Management and Accounting"=>4, "Physics and Astronomy"=>5, "Social Sciences"=>2, "Computer Science"=>2, "Decision Sciences"=>1, "Economics, Econometrics and Finance"=>5}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Social Sciences"=>{"Social Sciences"=>2}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>5}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>5}, "Computer Science"=>{"Computer Science"=>2}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>4}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"Pakistan"=>1, "China"=>1, "Israel"=>1, "Switzerland"=>1}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/685031"], "description"=>"<p>Both calculated using a 66-day window. The U.S. and Germany show a higher similarity for both measures than the U.S. and Japan. While both measures fluctuate over time, we observe that high correlations do not necessarily show jointly in the top and the bottom figure. We can thus differentiate between times of identical price movements (high index correlation) and global stress (high index correlation and high meta-correlation).</p>", "links"=>[], "tags"=>["correlations", "meta-correlations", "germany", "japan"], "article_id"=>355518, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031144.g005", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Index_correlations_top_and_Meta_correlations_bottom_for_the_U_S_vs_Germany_left_and_Japan_right_/355518", "title"=>"Index correlations (top) and Meta-correlations (bottom) for the U.S vs. Germany (left) and Japan (right).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-08 01:31:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/684652"], "description"=>"<p>All indices have been normalized by their mean. The indices of the U.S., U.K. and Germany (blue, green and red line) appear almost as if they are shifted parallel, which is a sign of their high correlation. Note that all price indices are based on stock prices in local currency.</p>", "links"=>[], "tags"=>["500", "ftse", "350", "dax", "30", "nikkei", "bse", "100", "sse", "composite"], "article_id"=>355125, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031144.g001", "stats"=>{"downloads"=>2, "page_views"=>47, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Normalized_stock_price_indices_S_amp_P_500_U_S_FTSE_350_U_K_DAX_30_Performance_Germany_NIKKEI_500_Japan_BSE_100_India_and_SSE_Composite_China_/355125", "title"=>"Normalized stock price indices; S&P 500 (U.S.), FTSE 350 (U.K.), DAX 30 Performance (Germany), NIKKEI 500 (Japan), BSE 100 (India), and SSE Composite (China).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-08 01:25:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/349239", "https://ndownloader.figshare.com/files/349271", "https://ndownloader.figshare.com/files/349307", "https://ndownloader.figshare.com/files/349356", "https://ndownloader.figshare.com/files/349393", "https://ndownloader.figshare.com/files/349437", "https://ndownloader.figshare.com/files/349491", "https://ndownloader.figshare.com/files/349517", "https://ndownloader.figshare.com/files/349559", "https://ndownloader.figshare.com/files/349594", "https://ndownloader.figshare.com/files/349633", "https://ndownloader.figshare.com/files/349670", "https://ndownloader.figshare.com/files/349699", "https://ndownloader.figshare.com/files/349723", "https://ndownloader.figshare.com/files/349745", "https://ndownloader.figshare.com/files/349788"], "description"=>"<div><h3>Background</h3><p>In the current era of strong worldwide market couplings the global financial village became highly prone to systemic collapses, events that can rapidly sweep throughout the entire village.</p> <h3>Methodology/Principal Findings</h3><p>We present a new methodology to assess and quantify inter-market relations. The approach is based on the correlations between the market index, the index volatility, the market Index Cohesive Force and the meta-correlations (correlations between the intra-correlations.) We investigated the relations between six important world markets—U.S., U.K., Germany, Japan, China and India—from January 2000 until December 2010. We found that while the developed “western” markets (U.S., U.K., Germany) are highly correlated, the interdependencies between these markets and the developing “eastern” markets (India and China) are volatile and with noticeable maxima at times of global world events. The Japanese market switches “identity”—it switches between periods of high meta-correlations with the “western” markets and periods when it behaves more similarly to the “eastern” markets.</p> <h3>Conclusions/Significance</h3><p>The methodological framework presented here provides a way to quantify the evolvement of interdependencies in the global market, evaluate a world financial network and quantify changes in the world inter market relations. Such changes can be used as precursors to the agitation of the global financial village. Hence, the new approach can help to develop a sensitive “financial seismograph” to detect early signs of global financial crises so they can be treated before they develop into worldwide events.</p> </div>", "links"=>[], "tags"=>["evolvement", "uniformity", "volatility", "stressed"], "article_id"=>129058, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0031144.s001", "https://dx.doi.org/10.1371/journal.pone.0031144.s002", "https://dx.doi.org/10.1371/journal.pone.0031144.s003", "https://dx.doi.org/10.1371/journal.pone.0031144.s004", "https://dx.doi.org/10.1371/journal.pone.0031144.s005", "https://dx.doi.org/10.1371/journal.pone.0031144.s006", "https://dx.doi.org/10.1371/journal.pone.0031144.s007", "https://dx.doi.org/10.1371/journal.pone.0031144.s008", "https://dx.doi.org/10.1371/journal.pone.0031144.s009", "https://dx.doi.org/10.1371/journal.pone.0031144.s010", "https://dx.doi.org/10.1371/journal.pone.0031144.s011", "https://dx.doi.org/10.1371/journal.pone.0031144.s012", "https://dx.doi.org/10.1371/journal.pone.0031144.s013", "https://dx.doi.org/10.1371/journal.pone.0031144.s014", "https://dx.doi.org/10.1371/journal.pone.0031144.s015", "https://dx.doi.org/10.1371/journal.pone.0031144.s016"], "stats"=>{"downloads"=>12, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Evolvement_of_Uniformity_and_Volatility_in_the_Stressed_Global_Financial_Village/129058", "title"=>"Evolvement of Uniformity and Volatility in the Stressed Global Financial Village", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-02-08 02:30:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/684840"], "description"=>"<p>For each market, we use a 22-day window, and in each window calculate the intra-correlation. This results in the dynamics of the intra-correlation for the period of 2000–2010, for each market separately. Each horizontal line represents the average correlation of one stock (the left y-axis displays the number of the stock). The western markets and Japan show a similar behavior, visualized through vertical stripes at the same time, showing synchronized waves of strong correlations. The black line shows the average of all correlations at a given 22-day window (corresponding to the right y-axis). The trend is increasing for all countries except for China.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "physics", "mathematics"], "article_id"=>355324, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031144.g003", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dynamics_of_the_intra_correlation_/355324", "title"=>"Dynamics of the intra-correlation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-08 01:28:44"}
  • {"files"=>["https://ndownloader.figshare.com/files/684706"], "description"=>"<p>The price indices data was standardized for the 10-year interval (the mean is zero and the variance is 1 for each complete time series). The volatility peaks for the U.S, U.K. and Germany mostly coincide while there is less similarity with Japan. India and China show a very different behavior of volatility, especially until 2007.</p>", "links"=>[], "tags"=>["volatility", "markets", "22-day"], "article_id"=>355193, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031144.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relative_volatility_in_the_markets_within_a_22_day_window_/355193", "title"=>"Relative volatility in the markets within a 22-day window.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-08 01:26:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/685101"], "description"=>"<p>The width of the edges of the graph is proportional to the meta-correlation between the markets it connects (right legend). The node size is proportional to the inter-correlations (left legend). For 2000 we observe markets with low intra-correlations and inter-correlations of similar magnitude, excluding China. For 2010 we observe much higher intra-correlations in all markets and a denser network of interdependencies. (The nodes for the U.K. and Germany are further away from each other than their geographical position).</p>", "links"=>[], "tags"=>["years", "2000", "2010"], "article_id"=>355589, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031144.g006", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_global_financial_village_for_the_years_2000_left_and_2010_right_/355589", "title"=>"The global financial village for the years 2000 (left) and 2010 (right).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-08 01:33:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/685153"], "description"=>"<p>Summary of data used.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "physics", "mathematics"], "article_id"=>355649, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031144.t001", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_data_used_/355649", "title"=>"Summary of data used.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-02-08 01:34:09"}
  • {"files"=>["https://ndownloader.figshare.com/files/684953"], "description"=>"<p>The dynamics of the ICF for each market is plotted, for the period of 2000–2010.</p>", "links"=>[], "tags"=>["genetics and genomics", "Computational biology", "physics", "mathematics"], "article_id"=>355442, "categories"=>["Physics", "Mathematics", "Biological Sciences", "Genetics"], "users"=>["Dror Y. Kenett", "Matthias Raddant", "Thomas Lux", "Eshel Ben-Jacob"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0031144.g004", "stats"=>{"downloads"=>1, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Dynamics_of_the_ICF_/355442", "title"=>"Dynamics of the ICF.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-02-08 01:30:42"}

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Relative Metric

{"start_date"=>"2012-01-01T00:00:00Z", "end_date"=>"2012-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/People and places", "average_usage"=>[330, 562, 680, 783, 875, 964, 1062, 1152, 1240, 1327, 1406, 1483, 1561, 1632, 1701, 1770, 1849, 1922, 1993, 2059, 2131, 2197, 2271, 2335, 2403]}, {"subject_area"=>"/Social sciences", "average_usage"=>[354, 585, 710, 810, 904, 998, 1090, 1181, 1268, 1361, 1435, 1525, 1594, 1657, 1731, 1813, 1878, 1948, 2016, 2094, 2158, 2219, 2294, 2347, 2410]}]}
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