IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v479y2017icp299-308.html
   My bibliography  Save this article

Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective

Author

Listed:
  • Wen, Shaobo
  • An, Haizhong
  • Chen, Zhihua
  • Liu, Xueyong

Abstract

In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government’s policy mix.

Suggested Citation

  • Wen, Shaobo & An, Haizhong & Chen, Zhihua & Liu, Xueyong, 2017. "Driving factors of interactions between the exchange rate market and the commodity market: A wavelet-based complex network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 299-308.
    • Handle: RePEc:eee:phsmap:v:479:y:2017:i:c:p:299-308
    DOI: 10.1016/j.physa.2017.03.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437117302352
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2017.03.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stefan Reitz & Frank Westerhoff, 2007. "Commodity price cycles and heterogeneous speculators: a STAR–GARCH model," Empirical Economics, Springer, vol. 33(2), pages 231-244, September.
    2. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    3. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2015. "Identifying the multiscale impacts of crude oil price shocks on the stock market in China at the sector level," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 434(C), pages 13-24.
    4. Yu-Chin Chen & Kenneth S. Rogoff & Barbara Rossi, 2010. "Can Exchange Rates Forecast Commodity Prices?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(3), pages 1145-1194.
    5. Chi Wei Su & Heng-Guo Zhang & Hsu-Ling Chang & Rui Nian, 2016. "Is exchange rate stability beneficial for stabilizing consumer prices in China?," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 25(6), pages 857-879, September.
    6. Rua, António & Nunes, Luís C., 2009. "International comovement of stock market returns: A wavelet analysis," Journal of Empirical Finance, Elsevier, vol. 16(4), pages 632-639, September.
    7. Stephen D. Williamson & Randall Wright, 2010. "New monetarist economics: methods," Review, Federal Reserve Bank of St. Louis, vol. 92(May), pages 265-302.
    8. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    9. Byrne, Joseph P. & Fazio, Giorgio & Fiess, Norbert, 2013. "Primary commodity prices: Co-movements, common factors and fundamentals," Journal of Development Economics, Elsevier, vol. 101(C), pages 16-26.
    10. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian & Sebastien Mcmahon, 2008. "Forecasting commodity prices: GARCH, jumps, and mean reversion," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 279-291.
    11. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    12. Maslov, Sergei & Sneppen, Kim & Zaliznyak, Alexei, 2004. "Detection of topological patterns in complex networks: correlation profile of the internet," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 529-540.
    13. Li, Huajiao & An, Haizhong & Huang, Jiachen & Huang, Xuan & Mou, Songtao & Shi, Yanli, 2016. "The evolutionary stability of shareholders’ co-holding behavior for China’s listed energy companies based on associated maximal connected sub-graphs of derivative holding-based networks," Applied Energy, Elsevier, vol. 162(C), pages 1601-1607.
    14. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    15. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    16. Lorna Katusiime & Frank W. Agbola & Abul Shamsuddin, 2016. "Exchange rate volatility--economic growth nexus in Uganda," Applied Economics, Taylor & Francis Journals, vol. 48(26), pages 2428-2442, June.
    17. Zhang, Hui Jun & Dufour, Jean-Marie & Galbraith, John W., 2016. "Exchange rates and commodity prices: Measuring causality at multiple horizons," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 100-120.
    18. Hilke Brockmann & Jan Delhey & Christian Welzel & Hao Yuan, 2009. "The China Puzzle: Falling Happiness in a Rising Economy," Journal of Happiness Studies, Springer, vol. 10(4), pages 387-405, August.
    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. Das, Debojyoti & Bhowmik, Puja & Jana, R.K., 2018. "A multiscale analysis of stock return co-movements and spillovers: Evidence from Pacific developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 379-393.

    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. Coudert, Virginie & Mignon, Valérie, 2016. "Reassessing the empirical relationship between the oil price and the dollar," Energy Policy, Elsevier, vol. 95(C), pages 147-157.
    2. Jung, Young Cheol & Das, Anupam & McFarlane, Adian, 2020. "The asymmetric relationship between the oil price and the US-Canada exchange rate," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 198-206.
    3. Bermpei, Theodora & Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2024. "Commodity currencies revisited: The role of global commodity price uncertainty," Journal of International Money and Finance, Elsevier, vol. 145(C).
    4. Liu, Li & Tan, Siming & Wang, Yudong, 2020. "Can commodity prices forecast exchange rates?," Energy Economics, Elsevier, vol. 87(C).
    5. Thobekile Qabhobho, 2023. "Assessing the Asymmetric Effect of Local Realized Exchange Rate Volatility and Implied Volatilities in Energy Market on Exchange Rate Returns in BRICS," International Journal of Energy Economics and Policy, Econjournals, vol. 13(2), pages 231-239, March.
    6. Alam, Md. Samsul & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2019. "Causal flows between oil and forex markets using high-frequency data: Asymmetries from good and bad volatility," Energy Economics, Elsevier, vol. 84(C).
    7. Ma, Xiuying & Yang, Zhihua & Xu, Xiangyun & Wang, Chengqi, 2018. "The impact of Chinese financial markets on commodity currency exchange rates," Global Finance Journal, Elsevier, vol. 37(C), pages 186-198.
    8. Bork, Lasse & Kaltwasser, Pablo Rovira & Sercu, Piet, 2022. "Aggregation bias in tests of the commodity currency hypothesis," Journal of Banking & Finance, Elsevier, vol. 135(C).
    9. Athanasios Triantafyllou & Dimitrios Bakas & Marilou Ioakimidis, 2023. "Commodity price uncertainty as a leading indicator of economic activity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4194-4219, October.
    10. Chatziantoniou, Ioannis & Elsayed, Ahmed H. & Gabauer, David & Gozgor, Giray, 2023. "Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies," Energy Economics, Elsevier, vol. 120(C).
    11. Feng, Wenjun & Zhang, Zhengjun, 2023. "Currency exchange rate predictability: The new power of Bitcoin prices," Journal of International Money and Finance, Elsevier, vol. 132(C).
    12. Ciner, Cetin, 2017. "Predicting white metal prices by a commodity sensitive exchange rate," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 309-315.
    13. Wang, Wenhao & Cheung, Yin-Wong, 2023. "Commodity price effects on currencies," Journal of International Money and Finance, Elsevier, vol. 130(C).
    14. Joseph P Byrne & Ryuta Sakemoto & Bing Xu, 2020. "Commodity price co-movement: heterogeneity and the time-varying impact of fundamentals [Oil price shocks and the stock market: evidence from Japan]," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(2), pages 499-528.
    15. Cai, Guixin & Zhang, Hao & Chen, Ziyue, 2019. "Comovement between commodity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1247-1258.
    16. Degiannakis, Stavros & Filis, George, 2017. "Forecasting oil price realized volatility using information channels from other asset classes," Journal of International Money and Finance, Elsevier, vol. 76(C), pages 28-49.
    17. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    18. Fry-McKibbin, Renée & McKinnon, Kate, 2023. "The evolution of commodity market financialization: Implications for portfolio diversification," Journal of Commodity Markets, Elsevier, vol. 32(C).
    19. Chuffart Thomas & Flachaire Emmanuel & Péguin-Feissolle Anne, 2018. "Testing for misspecification in the short-run component of GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-17, December.
    20. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.

    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:eee:phsmap:v:479:y:2017:i:c:p:299-308. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.