IDEAS home Printed from https://ideas.repec.org/a/idn/journl/v19y2016i2ap129-152.html
   My bibliography  Save this article

Early Warning System And Currency Volatility Management In Emerging Market

Author

Listed:
  • Natasia Engeline S

    (Bank Indonesia)

  • Salomo Posmauli Matondang

    (Bank Indonesia)

Abstract

This paper adopts theoretical models from Candelon, Dumitrescu, and Hurlin and empirical model from Commerzbank to devise a set of indicators that can serve as an early warning system (EWS) on exchange rate. In light of the appreciation of emerging countries’ currencies during the Fed quantitative easing period, it is important to understand on how The Fed normalization would put pressure on managing volatility for central banks, especially for countries with large trade and fiscal deficit such as Indonesia. All in all, using both EWS models, central banks could discern potential exchange rate depreciation for intervention purpose.

Suggested Citation

  • Natasia Engeline S & Salomo Posmauli Matondang, 2016. "Early Warning System And Currency Volatility Management In Emerging Market," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 19(2), pages 129-152, October.
  • Handle: RePEc:idn:journl:v:19:y:2016:i:2a:p:129-152
    DOI: https://doi.org/10.21098/bemp.v19i2.627
    as

    Download full text from publisher

    File URL: https://bulletin.bmeb-bi.org/cgi/viewcontent.cgi?article=1162&context=bmeb
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.21098/bemp.v19i2.627?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
    ---><---

    References listed on IDEAS

    as
    1. Bank for International Settlements, 2005. "Foreign exchange market intervention in emerging market economies: an overview," BIS Papers chapters, in: Bank for International Settlements (ed.), Foreign exchange market intervention in emerging markets: motives, techniques and implications, volume 24, pages 1-3, Bank for International Settlements.
    2. Christopher J. Neely, 2001. "The practice of central bank intervention: looking under the hood," Review, Federal Reserve Bank of St. Louis, vol. 83(May), pages 1-10.
    3. Bank for International Settlements, 2013. "Market volatility and foreign exchange intervention in EMEs: what has changed?," BIS Papers, Bank for International Settlements, number 73.
    4. Frankel, Jeffrey A & Froot, Kenneth A, 1990. "Chartists, Fundamentalists, and Trading in the Foreign Exchange Market," American Economic Review, American Economic Association, vol. 80(2), pages 181-185, May.
    5. Graciela Kaminsky & Saul Lizondo & Carmen M. Reinhart, 1998. "Leading Indicators of Currency Crises," IMF Staff Papers, Palgrave Macmillan, vol. 45(1), pages 1-48, March.
    6. Heikki Kauppi & Pentti Saikkonen, 2008. "Predicting U.S. Recessions with Dynamic Binary Response Models," The Review of Economics and Statistics, MIT Press, vol. 90(4), pages 777-791, November.
    7. Basu, Kaushik & Varoudakis, Aristomene, 2013. "How to move the exchange rate if you must: the diverse practice of foreign exchange intervention by central banks and a proposal for doing it better," Policy Research Working Paper Series 6460, The World Bank.
    8. Garcia, Carlos J. & Restrepo, Jorge E. & Roger, Scott, 2011. "How much should inflation targeters care about the exchange rate?," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1590-1617.
    9. Candelon, Bertrand & Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2014. "Currency crisis early warning systems: Why they should be dynamic," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1016-1029.
    10. Kumar, Mohan & Moorthy, Uma & Perraudin, William, 2003. "Predicting emerging market currency crashes," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 427-454, September.
    11. Gustavo Adler & Mr. Camilo E Tovar Mora, 2011. "Foreign Exchange Intervention: A Shield Against Appreciation Winds?," IMF Working Papers 2011/165, International Monetary Fund.
    12. Elisabetta Falcetti & Merxe Tudela, 2006. "Modelling Currency Crises in Emerging Markets: A Dynamic Probit Model with Unobserved Heterogeneity and Autocorrelated Errors," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(4), pages 445-471, August.
    13. Bank for International Settlements, 2005. "Foreign exchange market intervention in emerging markets: motives, techniques and implications," BIS Papers, Bank for International Settlements, number 24.
    14. Berg, Andrew & Pattillo, Catherine, 1999. "Predicting currency crises:: The indicators approach and an alternative," Journal of International Money and Finance, Elsevier, vol. 18(4), pages 561-586, August.
    Full references (including those not matched with items on IDEAS)

    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. Nuttathum Chutasripanich & James Yetman, 2015. "Foreign exchange intervention: strategies and effectiveness," BIS Working Papers 499, Bank for International Settlements.
    2. Candelon, Bertrand & Dumitrescu, Elena-Ivona & Hurlin, Christophe, 2014. "Currency crisis early warning systems: Why they should be dynamic," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1016-1029.
    3. Hasse, Jean-Baptiste & Lecourt, Christelle & Siagh, Souhila, 2024. "Setting up a sovereign wealth fund to reduce currency crises," Emerging Markets Review, Elsevier, vol. 62(C).
    4. Allaj, Erindi & Sanfelici, Simona, 2023. "Early Warning Systems for identifying financial instability," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1777-1803.
    5. Ahmed, Jameel & Straetmans, Stefan, 2015. "Predicting exchange rate cycles utilizing risk factors," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 112-130.
    6. Fu, Junhui & Zhou, Qingling & Liu, Yufang & Wu, Xiang, 2020. "Predicting stock market crises using daily stock market valuation and investor sentiment indicators," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    7. Quentin LAJAUNIE, 2021. "Nonlinear Impulse Response Function for Dichotomous Models," LEO Working Papers / DR LEO 2852, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    8. Yanping Zhao & Jakob Haan & Bert Scholtens & Haizhen Yang, 2014. "Leading Indicators of Currency Crises: Are They the Same in Different Exchange Rate Regimes?," Open Economies Review, Springer, vol. 25(5), pages 937-957, November.
    9. Cumperayot, Phornchanok & Kouwenberg, Roy, 2013. "Early warning systems for currency crises: A multivariate extreme value approach," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 151-171.
    10. Abdul Rishad & Sanjeev Gupta & Akhil Sharma, 2021. "Official Intervention and Exchange Rate Determination: Evidence from India," Global Journal of Emerging Market Economies, Emerging Markets Forum, vol. 13(3), pages 357-379, September.
    11. Cruz-Rodríguez Alexis, 2013. "The Relationship between Fiscal Sustainability and Currency Crises in Some Selected Countries," Review of Economic Perspectives, Sciendo, vol. 13(4), pages 176-194, December.
    12. Tjeerd M. Boonman & Jan P. A. M. Jacobs & Gerard H. Kuper & Alberto Romero, 2019. "Early Warning Systems for Currency Crises with Real-Time Data," Open Economies Review, Springer, vol. 30(4), pages 813-835, September.
    13. Pham, Thi Hoang Anh, 2017. "Are global shocks leading indicators of currency crisis in Viet Nam?," Research in International Business and Finance, Elsevier, vol. 42(C), pages 605-615.
    14. Seyma Caliskan Cavdar & Alev Dilek Aydin, 2015. "A Different Perspective for Current Account Deficit Issue on Some OECD Member Countries: A Binary Panel Logit Approach," Research in World Economy, Research in World Economy, Sciedu Press, vol. 6(3), pages 14-22, September.
    15. Biswajit Banerjee & Juraj Zeman & Ľudovít Ódor & William O. Riiska, 2018. "On the Effectiveness of Central Bank Intervention in the Foreign Exchange Market: The Case of Slovakia, 1999–2007," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 60(3), pages 442-474, September.
    16. Bertrand Candelon & Elena-Ivona Dumitrescu & Christophe Hurlin & Franz C. Palm, 2013. "Multivariate Dynamic Probit Models: An Application to Financial Crises Mutation," Advances in Econometrics, in: VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims, volume 32, pages 395-427, Emerald Group Publishing Limited.
    17. Dieter Gerdesmeier & Hans‐Eggert Reimers & Barbara Roffia, 2010. "Asset Price Misalignments and the Role of Money and Credit," International Finance, Wiley Blackwell, vol. 13(3), pages 377-407, December.
    18. Lanbiao Liu & Chen Chen & Bo Wang, 2022. "Predicting financial crises with machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 871-910, August.
    19. Hasse, Jean-Baptiste & Lajaunie, Quentin, 2022. "Does the yield curve signal recessions? New evidence from an international panel data analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 9-22.
    20. Geraldine Dany-Knedlik & Martina Kämpfe & Tobias Knedlik, 2021. "The appropriateness of the macroeconomic imbalance procedure for Central and Eastern European Countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(1), pages 123-139, February.

    More about this item

    Keywords

    Dynamic Logit Model; Foreign Exchange; Early Warning System; Emerging Countries; Foreign Exchange Intervention;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F37 - International Economics - - International Finance - - - International 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:idn:journl:v:19:y:2016:i:2a:p:129-152. 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: Lutzardo Tobing The email address of this maintainer does not seem to be valid anymore. Please ask Lutzardo Tobing to update the entry or send us the correct address or Jimmy Kathon (email available below). General contact details of provider: https://edirc.repec.org/data/bigovid.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.