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  4. The Stochastic Properties of Major Canadian Exchange Rates
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The Stochastic Properties of Major Canadian Exchange Rates

Journal
Financial Review
Date Issued
May 1994
Author(s)
Theodossiou, Panayiotis  
DOI
10.1111/j.1540-6288.1994.tb00818.x
Abstract
This paper extends the results of Akgiray and Booth [2] on the stochastic properties of five major Canadian exchange rates using the EGARCH‐M model along with the generalized error distribution (GED). In addition to the issue of first‐ and second‐order dependencies, explored by the authors, the paper (1) addresses the issue of asymmetric volatility, (2) examines the extent to which volatility affects future movements in these exchange rates, (3) measures the amount of kurtosis in the data, and (4) investigates the transmission mechanism of innovations and volatility shocks across the five Canadian exchange rate markets. The five Canadian dollar exchange rates are for the U.S. dollar, the Japanese yen, the British pound, the German mark, and the French franc. Changes in Canadian exchange rates are conditionally heteroskedastic, a finding which is in line with that of Akgiray and Booth [2]. There is no evidence supporting the assertion that volatility triggers such changes. The hypothesis of asymmetric volatility is rejected for all Canadian exchange rates; thus unexpected appreciations and depreciations of the Canadian currency have similar impact on future volatility of these exchange rates. Innovations in the Canadian exchange rate markets for the U.S. dollar, the British pound, and French franc influence the Japanese yen market, while innovations in the markets of the British pound and German mark influence the French franc market. Significant but negative volatility spillovers radiate from the German mark market to the U.S. dollar market and from the French franc market to the German mark market, resulting in lower levels of volatility in both the U.S. and German markets. The distributions of all five series of Canadian exchange rates are highly leptokurtic relative to the normal distribution. The GED distribution provides a good characterization of these distributions.
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