{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T01:13:53Z","timestamp":1769822033813,"version":"3.49.0"},"reference-count":12,"publisher":"SAGE Publications","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2022,11,11]]},"abstract":"<jats:p>In recent years it has become popular to represent the foreign exchange market as a correlation network using the Pearson correlation coefficient as a measure of co-movement of exchange rates. We show that the Pearson correlation of financial time series could be misleading in analyzing their co-movements. We propose representing the co-movement of exchange rates as a non-directed graph using the measure of local trends associations (LTA). Each node in the graph represents a currency, and an edge between nodes represents an existing high association between currencies. We present several methods for network summary visualization showing the highest associations between nodes. One method allows comparing graphs corresponding to different correlation and association measures. Another one is appropriate for comparing graphs using the same association measure. We present a dynamic analysis of association networks and the network of associations with a selected currency named a \u201cnode of interest.\u201d We show that the currency networks based on LTA are better explainable than networks based on Pearson correlation. LTA based relationships between currencies better reflect geographical, economic or political relationships between corresponding countries.<\/jats:p>","DOI":"10.3233\/jifs-220840","type":"journal-article","created":{"date-parts":[[2022,8,5]],"date-time":"2022-08-05T11:19:51Z","timestamp":1659698391000},"page":"6925-6932","source":"Crossref","is-referenced-by-count":0,"title":["Measures of association of local trends and networks of foreign exchange market in analysis of currency co-movement"],"prefix":"10.1177","volume":"43","author":[{"given":"Diego","family":"Aguilar","sequence":"first","affiliation":[{"name":"Instituto Polit\u00e9cnico Nacional, CIC-IPN, Av. Juan de Dios B\u00e1tiz S\/N, Nueva Industrial Vallejo, Gustavo A. Madero, 07738, Ciudad de M\u00e9xico, M\u00e9xico"}]},{"given":"Ildar","family":"Batyrshin","sequence":"additional","affiliation":[{"name":"Instituto Polit\u00e9cnico Nacional, CIC-IPN, Av. Juan de Dios B\u00e1tiz S\/N, Nueva Industrial Vallejo, Gustavo A. Madero, 07738, Ciudad de M\u00e9xico, M\u00e9xico"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-220840_ref1","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.physa.2017.09.068","article-title":"Currency co-movement and network correlation structure of foreign exchange market","volume":"492","author":"Mai","year":"2018","journal-title":"Physica A: Statistical Mechanics and its Applications"},{"key":"10.3233\/JIFS-220840_ref2","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1090\/S0002-9939-1956-0078686-7","article-title":"On the shortest spanning subtree of a graph and the traveling salesman problem","volume":"7","author":"Kruskal","year":"1956","journal-title":"Proceedings of the American Mathematical Sciety"},{"key":"10.3233\/JIFS-220840_ref3","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.physa.2007.02.019","article-title":"Topology of foreign exchange markets using hierarchical structure methods","volume":"382","author":"Naylor","year":"2007","journal-title":"Physica A: Statistical Mechanics and its Applications"},{"key":"10.3233\/JIFS-220840_ref5","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s11403-009-0047-9","article-title":"of a network structure of the foreign currency exchangemarket","volume":"4","author":"Kwapie\u0144","year":"2009","journal-title":"Journal of Economic Interaction and Coordination"},{"key":"10.3233\/JIFS-220840_ref6","doi-asserted-by":"crossref","unstructured":"Lien K. , Day Trading and Swing Trading the Currency Market, 3rd ed. JohnWiley & Sons, New Jersey, 2016.","DOI":"10.1002\/9781119212997"},{"key":"10.3233\/JIFS-220840_ref7","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1016\/j.neucom.2015.05.127","article-title":"Time series shape association measures and local trend association patterns","volume":"175","author":"Batyrshin","year":"2016","journal-title":"Neurocomputing"},{"key":"10.3233\/JIFS-220840_ref8","doi-asserted-by":"crossref","first-page":"3337","DOI":"10.3233\/JIFS-169515","article-title":"Analysis of relationships between tweets and stock market trends","volume":"34","author":"Garcia-Lopez","year":"2018","journal-title":"Journal of Intelligent and Fuzzy Systems"},{"key":"10.3233\/JIFS-220840_ref9","doi-asserted-by":"crossref","unstructured":"Batyrshin I. , Herrera-Avelar R. , Sheremetov L. , Panova A. , Moving approximation transform and local trend associations in time series data bases, in: Perception-based Data Mining and Decision Making in Economics and Finance, I. 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