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Wavelet Based Volatility Clustering Estimation of Foreign Exchange Rates

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  • A. N. Sekar Iyengar

Abstract

We have presented a novel technique of detecting intermittencies in a financial time series of the foreign exchange rate data of U.S.- Euro dollar(US/EUR) using a combination of both statistical and spectral techniques. This has been possible due to Continuous Wavelet Transform (CWT) analysis which has been popularly applied to fluctuating data in various fields science and engineering and is also being tried out in finance and economics. We have been able to qualitatively identify the presence of nonlinearity and chaos in the time series of the foreign exchange rates for US/EURO (United States dollar to Euro Dollar) and US/UK (United States dollar to United Kingdom Pound) currencies. Interestingly we find that for the US-INDIA(United States dollar to Indian Rupee) foreign exchange rates, no such chaotic dynamics is observed. This could be a result of the government control over the foreign exchange rates, instead of the market controlling them.

Suggested Citation

  • A. N. Sekar Iyengar, 2009. "Wavelet Based Volatility Clustering Estimation of Foreign Exchange Rates," Papers 0910.0087, arXiv.org.
  • Handle: RePEc:arx:papers:0910.0087
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