THE EXCHANGE RATE AND RELATED FINANCIAL DATA

The FX market is perhaps the only market that is open 24 hours a day, seven days a
week. The market opens in Australasia, followed by the Far East, the Middle East and
Europe, and finally America. Upon the close of America, Australasia returns to the market
and begins the next 24-hour cycle. The implication for forecasting applications is that in
certain circumstances, because of time-zone differences, researchers should be mindful
when considering which data and which subsequent time lags to include.
In any time series analysis it is critical that the data used is clean and error free since
the learning of patterns is totally data-dependent. Also significant in the study of FX time
series forecasting is the rate at which data from the market is sampled. The sampling
frequency depends on the objectives of the researcher and the availability of data. For
example, intra day time series can be extremely noisy and “a typical off-floor trader. . .
would most likely use daily data if designing a neural network as a component of an
overall trading system” (Kaastra and Boyd, 1996: 220). For these reasons the time series
used in this chapter are all daily closing data obtained from a historical database provided
by Datastream.
The investigation is based on the London daily closing prices for the EUR/USD
exchange rate.3 In the absence of an indisputable theory of exchange rate determination,
we assumed that the EUR/USD exchange rate could be explained by that rate’s
recent evolution, volatility spillovers from other financial markets, and macro-economic
and monetary policy expectations. With this in mind it seemed reasonable to include,
as potential inputs, other leading traded exchange rates, the evolution of important stock
and commodity prices, and, as a measure of macro-economic and monetary policy expectations,
the evolution of the yield curve.