A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis
We find that exchange rate networks are significantly similar from the perspective of topological structure, though with relatively great differences in fluctuation characteristics from perspective of exchange rate time series. First, we transform central parity rate time series of US dollar, Euro,...
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2017/5632374 |
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| _version_ | 1849307373561184256 |
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| author | Can-Zhong Yao Ji-Nan Lin |
| author_facet | Can-Zhong Yao Ji-Nan Lin |
| author_sort | Can-Zhong Yao |
| collection | DOAJ |
| description | We find that exchange rate networks are significantly similar from the perspective of topological structure, though with relatively great differences in fluctuation characteristics from perspective of exchange rate time series. First, we transform central parity rate time series of US dollar, Euro, Yen, and Sterling against CNY into exchange rate networks with visibility graph algorithm and find consistent topological characteristics in four exchange rate networks, with their average path lengths 5 and average clustering coefficients 0.7. Further, we reveal that all four transformed exchange rate networks show hierarchical structure and small-world and scale-free properties, with their hierarchy indexes 0.5 and power exponents 1.5. Both of the US dollar network and Sterling network exhibit assortative mixing features, while the Euro network and Yen network exhibit disassortative mixing features. Finally, we research community structure of exchange rate networks and uncover the fact that the communities are actually composed by large amounts of continuous time point fractions and small amounts of discrete time point fractions. In this way, we can observe that the spread of time series values corresponding to nodes inside communities is significantly lower than the spread of those values corresponding to nodes of the whole networks. |
| format | Article |
| id | doaj-art-291bb4a775ec4f92ae47173bcd87fb4c |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-291bb4a775ec4f92ae47173bcd87fb4c2025-08-20T03:54:47ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2017-01-01201710.1155/2017/56323745632374A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic AnalysisCan-Zhong Yao0Ji-Nan Lin1School of Economics and Commerce, South China University of Technology, Guangzhou 510006, ChinaDepartment of Economics, The Chinese University of Hong Kong, Shatin, Hong KongWe find that exchange rate networks are significantly similar from the perspective of topological structure, though with relatively great differences in fluctuation characteristics from perspective of exchange rate time series. First, we transform central parity rate time series of US dollar, Euro, Yen, and Sterling against CNY into exchange rate networks with visibility graph algorithm and find consistent topological characteristics in four exchange rate networks, with their average path lengths 5 and average clustering coefficients 0.7. Further, we reveal that all four transformed exchange rate networks show hierarchical structure and small-world and scale-free properties, with their hierarchy indexes 0.5 and power exponents 1.5. Both of the US dollar network and Sterling network exhibit assortative mixing features, while the Euro network and Yen network exhibit disassortative mixing features. Finally, we research community structure of exchange rate networks and uncover the fact that the communities are actually composed by large amounts of continuous time point fractions and small amounts of discrete time point fractions. In this way, we can observe that the spread of time series values corresponding to nodes inside communities is significantly lower than the spread of those values corresponding to nodes of the whole networks.http://dx.doi.org/10.1155/2017/5632374 |
| spellingShingle | Can-Zhong Yao Ji-Nan Lin A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis Discrete Dynamics in Nature and Society |
| title | A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis |
| title_full | A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis |
| title_fullStr | A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis |
| title_full_unstemmed | A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis |
| title_short | A Visibility Graph Approach to CNY Exchange Rate Networks and Characteristic Analysis |
| title_sort | visibility graph approach to cny exchange rate networks and characteristic analysis |
| url | http://dx.doi.org/10.1155/2017/5632374 |
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