IDEAS home Printed from https://ideas.repec.org/p/cde/cdewps/197.html
   My bibliography  Save this paper

Modelling and Forecasting the Indian Re/US Dollar Exchange Rate

Author

Listed:
  • Pami Dua

    (Department of Economics, Delhi School of Economics, Delhi, India)

  • Rajiv Ranjan

    (Reserve Bank of India, India)

Abstract

This paper develops vector autoregressive and Bayesian vector autoregressive models to forecast the Indian Re/US dollar exchange rate which is governed by a managed floating exchange rate regime. It considers extensions of the monetary model that include the forward premium, capital inflows, volatility of capital flows, order flows and central bank intervention. The study finds that the monetary model generally outperforms the naïve model. It also finds that forecast accuracy can be improved by extending the monetary model to include forward premium, volatility of capital inflows and order flow. Information on intervention by the central bank also helps to improve forecasts at the longer end. The study also reports that the Bayesian vector autoregressive models generally outperform their corresponding VAR variants.

Suggested Citation

  • Pami Dua & Rajiv Ranjan, 2011. "Modelling and Forecasting the Indian Re/US Dollar Exchange Rate," Working papers 197, Centre for Development Economics, Delhi School of Economics.
  • Handle: RePEc:cde:cdewps:197
    as

    Download full text from publisher

    File URL: http://www.cdedse.org/pdf/work197.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bjonnes, Geir Hoidal & Rime, Dagfinn, 2005. "Dealer behavior and trading systems in foreign exchange markets," Journal of Financial Economics, Elsevier, vol. 75(3), pages 571-605, March.
    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. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    4. Christopher J. Neely, 2005. "An analysis of recent studies of the effect of foreign exchange intervention," Review, Federal Reserve Bank of St. Louis, vol. 87(Nov), pages 685-718.
    5. Meese, Richard, 1990. "Currency Fluctuations in the Post-Bretton Woods Era," Journal of Economic Perspectives, American Economic Association, vol. 4(1), pages 117-134, Winter.
    6. David Backus, 1984. "Empirical Models of the Exchange Rate: Separating the Wheat from the Chaff," Canadian Journal of Economics, Canadian Economics Association, vol. 17(4), pages 824-846, November.
    7. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    8. Pasquale Della Corte & Lucio Sarno & Ilias Tsiakas, 2009. "An Economic Evaluation of Empirical Exchange Rate Models," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3491-3530, September.
    9. Artis, M. J. & Zhang, W., 1990. "BVAR forecasts for the G-7," International Journal of Forecasting, Elsevier, vol. 6(3), pages 349-362, October.
    10. Dornbusch, Rudiger & Fischer, Stanley, 1980. "Exchange Rates and the Current Account," American Economic Review, American Economic Association, vol. 70(5), pages 960-971, December.
    11. Michel De Vroey & Pierre Malgrange, 2016. "Macroeconomics," Chapters, in: Gilbert Faccarello & Heinz D. Kurz (ed.), Handbook on the History of Economic Analysis Volume III, chapter 27, pages 372-390, Edward Elgar Publishing.
    12. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    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. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    2. Nyoni, Thabani, 2019. "An ARIMA analysis of the Indian Rupee/USD exchange rate in India," MPRA Paper 96908, University Library of Munich, Germany.
    3. Somesh Kumar Mathur & Surendra Babu, 2014. "Modelling & Forecasting of Re/$ Exchange rate – An empirical analysis," 2nd International Conference on Energy, Regional Integration and Socio-Economic Development 7741, EcoMod.
    4. Tamal Datta Chaudhuri & Indranil Ghosh, 2016. "Artificial Neural Network and Time Series Modeling Based Approach to Forecasting the Exchange Rate in a Multivariate Framework," Papers 1607.02093, arXiv.org.
    5. Riane de Bruyn & Rangan Gupta & Renee van Eyden, 2013. "Forecasting The Rand-Dollar And Rand-Pound Exchange Rates Using Dynamic Model Averaging," Working Papers 201307, University of Pretoria, Department of Economics.
    6. Niyati Bhanja & Arif Billah Dar & Aviral Kumar Tiwari, 2015. "Exchange Rate and Monetary Fundamentals: Long Run Relationship Revisited," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 62(1), pages 33-54, March.
    7. Hyeyoen Kim & Doojin Ryu, 2013. "Forecasting Exchange Rate from Combination Taylor Rule Fundamental," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(S4), pages 81-92, September.
    8. Danglun Luo & Qianwei Ying, 2014. "Political Connections and Bank Lines of Credit," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 50(03), pages 5-21, May.

    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. Pami Dua & Rajiv Ranjan & Deepika Goel, 2023. "Forecasting the INR/USD Exchange Rate: A BVAR Framework," Springer Books, in: Pami Dua (ed.), Macroeconometric Methods, chapter 0, pages 183-224, Springer.
    2. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    3. Dibooglu, Selahattin, 1993. "Multiple cointegration and structural models: applications to exchange rate determination," ISU General Staff Papers 1993010108000011419, Iowa State University, Department of Economics.
    4. Paolo Vitale, 2007. "An assessment of some open issues in the analysis of foreign exchange intervention," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 155-170.
    5. Vitale, Paolo, 2006. "A Critical Appraisal of Recent Developments in the Analysis of Foreign Exchange Intervention," CEPR Discussion Papers 5729, C.E.P.R. Discussion Papers.
    6. Amano, R. A. & van Norden, S., 1998. "Oil prices and the rise and fall of the US real exchange rate," Journal of International Money and Finance, Elsevier, vol. 17(2), pages 299-316, April.
    7. Roman Frydman & Michael D. Goldberg, 2001. "Macroeconomic Fundamentals and the DM/$ Exchange Rate: Temporal Instability and the Monetary Model," Working Papers 50, Oesterreichische Nationalbank (Austrian Central Bank).
    8. Rime, Dagfinn & Sarno, Lucio & Sojli, Elvira, 2010. "Exchange rate forecasting, order flow and macroeconomic information," Journal of International Economics, Elsevier, vol. 80(1), pages 72-88, January.
    9. Menzie D. Chinn & Michael J. Moore, 2011. "Order Flow and the Monetary Model of Exchange Rates: Evidence from a Novel Data Set," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(8), pages 1599-1624, December.
    10. Lucio Sarno & Giorgio Valente, 2009. "Exchange Rates and Fundamentals: Footloose or Evolving Relationship?," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 786-830, June.
    11. Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3455-3480.
    12. Works, Richard Floyd, 2016. "Econometric modeling of exchange rate determinants by market classification: An empirical analysis of Japan and South Korea using the sticky-price monetary theory," MPRA Paper 76382, University Library of Munich, Germany.
    13. Morales-Arias, Leonardo & Moura, Guilherme V., 2013. "Adaptive forecasting of exchange rates with panel data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 493-509.
    14. King, Michael R. & Osler, Carol L. & Rime, Dagfinn, 2013. "The market microstructure approach to foreign exchange: Looking back and looking forward," Journal of International Money and Finance, Elsevier, vol. 38(C), pages 95-119.
    15. Phornchanok Cumperayot, 2003. "Dusting off the Perception of Risk and Returns in FOREX Markets," CESifo Working Paper Series 904, CESifo.
    16. Paolo Vitale, 2007. "A Guided Tour Of The Market Microstructure Approach To Exchange Rate Determination," Journal of Economic Surveys, Wiley Blackwell, vol. 21(5), pages 903-934, December.
    17. O. P. C. Muhammed Rafi & M. Ramachandran, 2018. "Capital flows and exchange rate volatility: experience of emerging economies," Indian Economic Review, Springer, vol. 53(1), pages 183-205, December.
    18. Douglas, Christopher C. & Kolar, Marek, 2009. "Capturing the time dynamics of central bank intervention," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(5), pages 950-968, December.
    19. Rituparna Kar & Nityananda Sarkar, 2006. "Mean and volatility dynamics of Indian rupee/US dollar exchange rate series: an empirical investigation," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 13(1), pages 41-69, March.
    20. Smita Roy Trivedi, 2020. "The Moses effect: can central banks really guide foreign exchange markets?," Empirical Economics, Springer, vol. 58(6), pages 2837-2865, June.

    More about this item

    Keywords

    exchange rate; monetary model; VAR and Bayesian VAR models;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • 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
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cde:cdewps:197. 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: Sanjeev Sharma (email available below). General contact details of provider: https://edirc.repec.org/data/cdudein.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.