IDEAS home Printed from https://ideas.repec.org/p/imf/imfwpa/2016-130.html
   My bibliography  Save this paper

A Network Model of Multilaterally Equilibrium Exchange Rates

Author

Listed:
  • Mr. Alexei P Kireyev
  • Andrei Leonidov

Abstract

This paper proposes a network model of multilaterally equilibrium exchange rates. The model introduces a topological component into the exchange rate analysis, consistently taking into account simultaneous higher-order interactions among all currencies. The paper defines the currency demand indicator. On its base, it derives a multilateral exchange rate network, finds its dynamically stationary position, and identifies the multilaterally equilibrium levels of bilateral exchanges rates. Potentially, the model can be developed further to calculate the deviations of the observed bilateral exchange rates from their multilaterally equilibrium levels, which can be interpreted as their over- or undervaluation. For illustration, the model is applied to daily 1995-2016 exchange rates among 130 currencies sourced from the Thomson Reuters Datastream.

Suggested Citation

  • Mr. Alexei P Kireyev & Andrei Leonidov, 2016. "A Network Model of Multilaterally Equilibrium Exchange Rates," IMF Working Papers 2016/130, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2016/130
    as

    Download full text from publisher

    File URL: http://www.imf.org/external/pubs/cat/longres.aspx?sk=44060
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. repec:cup:cbooks:9781107034662 is not listed on IDEAS
    2. Gautier M Krings & Jean-François Carpantier & Jean-Charles Delvenne, 2014. "Trade Integration and Trade Imbalances in the European Union: A Network Perspective," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-14, January.
    3. Brooks,Chris, 2014. "Introductory Econometrics for Finance," Cambridge Books, Cambridge University Press, number 9781107661455, December.
    4. Daron Acemoglu & Ufuk Akcigit & William Kerr, 2016. "Networks and the Macroeconomy: An Empirical Exploration," NBER Macroeconomics Annual, University of Chicago Press, vol. 30(1), pages 273-335.
    5. David Matesanz & Guillermo Ortega, 2014. "Network analysis of exchange data: interdependence drives crisis contagion," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 1835-1851, July.
    6. Tiziano Squartini & Diego Garlaschelli, 2014. "Stationarity, non-stationarity and early warning signals in economic networks," Papers 1403.4460, arXiv.org, revised May 2014.
    7. Mr. Steven T Phillips & Mr. Luis Catão & Mr. Luca A Ricci & Mr. Rudolfs Bems & Ms. Mitali Das & Mr. Julian Di Giovanni & Ms. Filiz D Unsal & Marola Castillo & Jungjin Lee & Jair Rodriguez & Mr. Mauric, 2013. "The External Balance Assessment (EBA) Methodology," IMF Working Papers 2013/272, International Monetary Fund.
    8. Sitabhra Sinha & Uday Kovur, 2013. "Uncovering the network structure of the world currency market: Cross-correlations in the fluctuations of daily exchange rates," Papers 1305.0239, arXiv.org.
    9. repec:zbw:bofrdp:urn:nbn:fi:bof-201512101464 is not listed on IDEAS
    10. Alexei Kireyev & Andrei Leonidov, 2018. "Network Effects of International Shocks and Spillovers," Networks and Spatial Economics, Springer, vol. 18(4), pages 805-836, December.
    11. M. Serrano & Marián Boguñá & Alessandro Vespignani, 2007. "Patterns of dominant flows in the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(2), pages 111-124, December.
    12. Mr. Alexei P Kireyev & Andrei Leonidov, 2016. "China’s Imports Slowdown: Spillovers, Spillins, and Spillbacks," IMF Working Papers 2016/051, International Monetary Fund.
    13. repec:zbw:bofrdp:2015_025 is not listed on IDEAS
    14. Simone Caschili & Francesca Medda & Alan Wilson, 2015. "An Interdependent Multi-Layer Model: Resilience of International Networks," Networks and Spatial Economics, Springer, vol. 15(2), pages 313-335, June.
    15. Fracasso, Andrea & Schiavo, Stefano, 2009. "Global imbalances, exchange rates adjustment and the crisis: Implications from network analysis," Journal of Policy Modeling, Elsevier, vol. 31(5), pages 601-619, September.
    16. Bouchaud,Jean-Philippe & Potters,Marc, 2003. "Theory of Financial Risk and Derivative Pricing," Cambridge Books, Cambridge University Press, number 9780521819169, January.
    17. Syngjoo Choi & Andrea Galeotti & Sanjeev Goyal, 2017. "Trading in Networks: Theory and Experiments," Journal of the European Economic Association, European Economic Association, vol. 15(4), pages 784-817.
    18. M. Angeles Serrano & Marian Boguna & Alessandro Vespignani, 2007. "Patterns of dominant flows in the world trade web," Papers 0704.1225, arXiv.org.
    19. Jaroslaw Kwapien & Sylwia Gworek & Stanislaw Drozdz & Andrzej Gorski, 2009. "Analysis of a network structure of the foreign currency exchange market," Papers 0906.0480, arXiv.org.
    20. Andreas Joseph & Irena Vodenska & Eugene Stanley & Guanrong Chen, 2014. "Netconomics: Novel Forecasting Techniques from the Combination of Big Data, Network Science and Economics," Papers 1403.0848, arXiv.org.
    21. Jarosław Kwapień & Sylwia Gworek & Stanisław Drożdż & Andrzej Górski, 2009. "Analysis of a network structure of the foreign currency exchange market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 4(1), pages 55-72, June.
    22. Daron Acemoglu & Asuman Ozdaglar & Alireza Tahbaz-Salehi, 2013. "The Network Origins of Large Economic Downturns," NBER Working Papers 19230, National Bureau of Economic Research, Inc.
    23. Heiberger, Raphael H., 2014. "Stock network stability in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 376-381.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    2. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Helian & Cheng, Long, 2016. "The QAP weighted network analysis method and its application in international services trade," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 91-101.
    2. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    3. Mr. Alexei P Kireyev & Andrei Leonidov, 2016. "China’s Imports Slowdown: Spillovers, Spillins, and Spillbacks," IMF Working Papers 2016/051, International Monetary Fund.
    4. Bartesaghi, Paolo & Clemente, Gian Paolo & Grassi, Rosanna & Luu, Duc Thi, 2022. "The multilayer architecture of the global input-output network and its properties," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 304-341.
    5. Danau, Daniel, 2020. "Prudence and preference for flexibility gain," European Journal of Operational Research, Elsevier, vol. 287(2), pages 776-785.
    6. Tan T. M. Le & Franck Martin & Duc K. Nguyen, 2018. "Dynamic connectedness of global currencies: a conditional Granger-causality approach," Economics Working Paper Archive (University of Rennes & University of Caen) 2018-04, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    7. Arcagni, Alberto & Cerqueti, Roy & Grassi, Rosanna, 2024. "Higher-order assortativity for directed weighted networks and Markov chains," European Journal of Operational Research, Elsevier, vol. 316(1), pages 215-227.
    8. Mansooreh Kazemilari & Maman Abdurachman Djauhari & Zuhaimy Ismail, 2016. "Foreign Exchange Market Performance: Evidence from Bivariate Time Series Approach," Papers 1608.07694, arXiv.org.
    9. Alexei Kireyev & Andrei Leonidov, 2018. "Network Effects of International Shocks and Spillovers," Networks and Spatial Economics, Springer, vol. 18(4), pages 805-836, December.
    10. Célestin Coquidé & José Lages & Dima Shepelyansky, 2020. "Interdependence of sectors of economic activities for world countries from the reduced Google matrix analysis of WTO data," Post-Print hal-02132487, HAL.
    11. Aller, Carlos & Ductor, Lorenzo & Herrerias, M.J., 2015. "The world trade network and the environment," Energy Economics, Elsevier, vol. 52(PA), pages 55-68.
    12. Coletti, Paolo, 2016. "Comparing minimum spanning trees of the Italian stock market using returns and volumes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 246-261.
    13. Gang-Jin Wang & Chi Xie & H. Eugene Stanley, 2018. "Correlation Structure and Evolution of World Stock Markets: Evidence from Pearson and Partial Correlation-Based Networks," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 607-635, March.
    14. Trucmel Irina-Maria & Vintila Alexandra & Capbun Andreea Gabriela & Roman Mihai Daniel, 2022. "An International Trade Disputes Analysis using Network Theory," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 639-649, August.
    15. Marco Dueñas & Giorgio Fagiolo, 2013. "Modeling the International-Trade Network: a gravity approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 155-178, April.
    16. Erik Braun & Emese Braun & András Gyimesi & Zita Iloskics & Tamás Sebestyén, 2023. "Exposure to trade disruptions in case of the Russia–Ukraine conflict: A product network approach," The World Economy, Wiley Blackwell, vol. 46(10), pages 2950-2982, October.
    17. Shangkun Deng & Kazuki Yoshiyama & Takashi Mitsubuchi & Akito Sakurai, 2015. "Hybrid Method of Multiple Kernel Learning and Genetic Algorithm for Forecasting Short-Term Foreign Exchange Rates," Computational Economics, Springer;Society for Computational Economics, vol. 45(1), pages 49-89, January.
    18. Andrea Fracasso & Stefano Schiavo, 2009. "Trade-imbalances networks and exchange rate adjustments: the paradox of a new Plaza. The XIVth Spring Meeting of Young Economists (SMYE-2009), Istanbul, April 2009," Post-Print hal-01053278, HAL.
    19. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.
    20. Giorgio Fagiolo & Javier Reyes & Stefano Schiavo, 2010. "The evolution of the world trade web: a weighted-network analysis," Journal of Evolutionary Economics, Springer, vol. 20(4), pages 479-514, August.

    More about this item

    Keywords

    WP; base currency; currency pair; world currency market; equilibrium exchange rates; exchange rate; networks; equilibrium; trade; network; exchange rate network; network consist; network stationarity; Exchange rates; Currencies; Currency markets; Exchange rate modelling; Reserve currencies; Global;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:imf:imfwpa:2016/130. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Akshay Modi (email available below). General contact details of provider: https://edirc.repec.org/data/imfffus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.