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The Economic Value of Fundamental and Technical Information in Emerging Currency Markets

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  • de Zwart, G.J.
  • Markwat, T.D.
  • Swinkels, L.A.P.
  • van Dijk, D.J.C.

Abstract

We measure the economic value of information derived from macroeconomic variables and from technical trading rules for emerging markets currency investments. Our analysis is based on a sample of 21 emerging markets with a floating exchange rate regime over the period 1997-2007 and explicitly accounts for trading restrictions on foreign capital movements by using non-deliverable forward data. We document that both types of information can be exploited to implement profitable trading strategies. In line with evidence from surveys of foreign exchange professionals concerning the use of fundamental and technical analysis, we find that combining the two types of information improves the risk-adjusted performance of the investment strategies.

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Bibliographic Info

Paper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam in its series ERIM Report Series Research in Management with number ERS-2007-096-F&A.

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Date of creation: 21 Dec 2007
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Handle: RePEc:ems:eureri:10891

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Keywords: emerging markets; foreign exchange rates; heterogeneous agents; structural exchange rate models; technical trading;

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Cited by:
  1. Tajaddini, Reza & Crack, Timothy Falcon, 2012. "Do momentum-based trading strategies work in emerging currency markets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(3), pages 521-537.
  2. Carl Chiarella & Xue-Zhong He & Remco C.J. Zwinkels, 2014. "Heterogeneous Expectations in Asset Pricing:Empirical Evidence from the S&P500," Research Paper Series 344, Quantitative Finance Research Centre, University of Technology, Sydney.
  3. Stephen Gilmore & Fumio Hayashi, 2008. "Emerging Market Currency Excess Returns," NBER Working Papers 14528, National Bureau of Economic Research, Inc.
  4. Kuang, P. & Schröder, M. & Wang, Q., 2014. "Illusory profitability of technical analysis in emerging foreign exchange markets," International Journal of Forecasting, Elsevier, vol. 30(2), pages 192-205.
  5. Michael Melvin & John Prins & Duncan Shand, 2013. "Forecasting Exchange Rates: An Investor Perspective," CESifo Working Paper Series 4238, CESifo Group Munich.
  6. A. Carriero & G. Kapetanios & M. Marcellino, 2008. "Forecasting Exchange Rates with a Large Bayesian VAR," Economics Working Papers ECO2008/33, European University Institute.
  7. Doukas, John A. & Zhang, Hao, 2013. "The performance of NDF carry trades," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 172-190.
  8. Neely, Christopher J. & Weller, Paul A., 2013. "Lessons from the evolution of foreign exchange trading strategies," Journal of Banking & Finance, Elsevier, vol. 37(10), pages 3783-3798.
  9. Christopher J. Neely & Paul A. Weller, 2011. "Technical analysis in the foreign exchange market," Working Papers 2011-001, Federal Reserve Bank of St. Louis.
  10. de Jong, Eelke & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2010. "Heterogeneity of agents and exchange rate dynamics: Evidence from the EMS," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1652-1669, December.
  11. Evzen Kocenda & Vit Bubak & Filip Zikes, 2011. "Volatility Transmission in Emerging European Foreign Exchange Markets," William Davidson Institute Working Papers Series wp1020, William Davidson Institute at the University of Michigan.

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