GBP/USD 2002-2008: Predictability Overview

The US Dollar/Pound Sterling currency pair does not show much predictability from the point of view of basic two-point correlation approach adopted in these series of articles, besides the trend repetition signal with a 24-hour-multiple time lag seen in most other currency pairs.

In this report we focus on the period from 00:00 2002-08-20 to 00:00 2008-02-01 (New York time).

GBP/USD autocorrelation 1 hour time-lag bin

Fig.1: Autocorrelation of hourly logarithmic returns in GBP/USD. The time lag is in “business time” (periods without update ticks are excluded). The red band shows the level of noise as iferred from martingale simulations (see text).

The basic autocorrelation

As before we employ autocorrelation as a straightforward, inter-disciplinary, non-proprietary technique to test market efficiency. In Fig.1 we look for features on the time scale of up to 48 hours such as to suit the time scale of day trading or swing trading. The hatched red band shows the range of statistical noise (namely its expectation plus minus its RMS deviation). Statistical noise was obtained by simulating 20 independent time series of the length corresponding to that of the GBP/USD series, each one constructed to reproduce the measured distribution of returns for GBP/USD for the time period under study (including the fat tails!), but completely devoid of correlations ( martingale time series ). From these, the expectation and RMS or the autocorrelation amplitude in each time lag bin were calculated. The one-hour time lag “contrarian” feature (a significant anticorrelation) we saw on this plot in other currency pairs involving GBP ( GBP/JPY ) and USD ( USD/CAD, AUD/USD ) is not present in the GBP/USD autocorrelation.

GBP/USD autocorrelation 4 hour time-lag bin

Fig.2: GBP/USD autocorrelation as in Fig.1, but with time lag bin increased to 4 hours.

GBP/USD autocorrelation 12 hour time-lag bin

Fig.3: GBP/USD autocorrelation as in Fig.1, but with time lag bin increased to 12 hours.

In Fig.2, the time lag bin has been increased to 4 hours, and in Fig.3 — to 12 hours. These figures do not reveal any reliable patterns.

24-hour trading cycle.

GBP/USD bullish and bearish autocorrelation

Fig.4: GBP/USD bullish and bearish autocorrelations. Yellow: correlating only positive hourly returns. Blue: correlating only negative hourly returns.

In Fig.3 we construct autocorrelations of the subsamples of the full time series (the “bullish” and “bearish” ones) selected by taking only positive and negative returns respectively. The 24 hour cycle of bullish and bearish action is again clearly seen as the maxima of the correlation are located at multiples of the 24 hour lag: 24, 48, 72, 96, 120 hours and so on. Therefore, smart trend following means something more than following a trend that existed in the near past. It means following a trend that existed this time of the day yesterday, the day before yesterday, and so on — that gives you better than average chance of winning! Conversely, buying because the currency went up 12 hours ago (or selling because it went down 12 hours ago), all the rest being equal, is the least recommended strategy. (See why this periodic correlation feature is not in itself a prediction strategy.) Needless to say, this effect is not present in the simulated martingale data.

Note that whether this oscillation pattern is equally strong in all time zones is a question that requires a separate study.

GBP/USD bullish and bearish autocorrelation long range

Fig.4: GBP/USD bullish and bearish autocorrelations. Axes and color codes as in the previous figure. Range expanded compared to the previous figure to show the characteristic time length of this market memory effect.

Similar patterns have been seen before with most other currency pairs in this series of predictability reviews.


GBP/USD looks like a fairly difficult currency pair to trade on the basis of two-point correlations alone. Long term prospects of GBP/USD are the subject of fundamental analysis and are outside the scope of this article. Cross-correlations with other markets are to be discussed in the up-coming articles.