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Origins of scaling in FX markets

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Author Info
Mercik, Szymon
Weron, Rafal

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Abstract

Typical data sets employed by economists and financial analysts do not exceed a few hundred or thousand observations per series. However, in the last decade data sets containing tick-by-tick observations have become available. The studies of these data have turned up new and interesting facts about the pricing of assets. In this article we show that foreign exchange (FX) rate returns satisfy scaling with an exponent significantly different from that of a random walk. But what is more important, we also show that the conditionally exponential decay (CED) model can be used to solve a long standing problem in the analysis of intra-daily data, i.e. it can be used to identify the mathematical structure of the distributions of FX returns corresponding to the empirical scaling laws.

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File URL: http://mpra.ub.uni-muenchen.de/2294/
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 2294.

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Date of creation: Jul 2002
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Handle: RePEc:pra:mprapa:2294

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Related research
Keywords: FX market scaling law volatility CED model high frequency data

Find related papers by JEL classification:
C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
F31 - International Economics - - International Finance - - - Foreign Exchange
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation

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  1. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-55, January. [Downloadable!] (restricted)
  2. Muller, Ulrich A. & Dacorogna, Michel M. & Olsen, Richard B. & Pictet, Olivier V. & Schwarz, Matthias & Morgenegg, Claude, 1990. "Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis," Journal of Banking & Finance, Elsevier, vol. 14(6), pages 1189-1208, December. [Downloadable!] (restricted)
  3. Andersen, Torben G, 2000. "Some Reflections on Analysis of High-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 146-53, April.
  4. Stefan Mittnik & Svetlozar Rachev, 1993. "Modeling asset returns with alternative stable distributions," Econometric Reviews, Taylor and Francis Journals, vol. 12(3), pages 261-330. [Downloadable!] (restricted)
  5. Simon Hurst & Eckhard Platen & Svetlozar Rachev, 1997. "Subordinated Market Index Models: A Comparison," Asia-Pacific Financial Markets, Springer, vol. 4(2), pages 97-124, May. [Downloadable!] (restricted)
  6. Blattberg, Robert C & Gonedes, Nicholas J, 1974. "A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices," Journal of Business, University of Chicago Press, vol. 47(2), pages 244-80, April. [Downloadable!] (restricted)
  7. Tucker, Alan L & Pond, Lallon, 1988. "The Probability Distribution of Foreign Exchange Price Changes: Tests of Candidate Processes," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 638-47, November. [Downloadable!] (restricted)
  8. Richard B. Olsen & Ulrich A. Müller & Michel M. Dacorogna & Olivier V. Pictet & Rakhal R. Davé & Dominique M. Guillaume, 1997. "From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets (*)," Finance and Stochastics, Springer, vol. 1(2), pages 95-129. [Downloadable!] (restricted)
  9. Iram Gleria & Raul Matsushita & Sergio Da Silva, 2002. "Scaling power laws in the Sao Paulo Stock Exchange," Economics Bulletin, Economics Bulletin, vol. 7(3), pages 1-12. [Downloadable!]
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