Forecasting Foreign Exchange Rates Subject to De-volatilization
Abstract
There is a considerable literature analyzing the behavior of exchange rates. However, the modeling and forecasting of exchange rates has not been very successful. One of the obstacles to effective modeling of financial time series is heteroscedasticity. The recent availability of high frequency data, such as tick-by-tick data, provides us with extra information about the market. However, even with today’s computer power, analyzing data with order of gigabits is extremely expensive and time consuming. This article proposes to analyze a homoscedastic subsequence of such data. The procedure of obtaining such a homoscedastic subsequence is called de-volatilization. The empirical evidence suggests that de-volatilization can help us to detect trends of the market quickly. Our forecasting results indicate that the exchange market can be forecast to certain extend.
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