Patterns of financial crisis: EUR/CHF 2007-2008.

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Written by Forex Automaton   
Tuesday, 03 February 2009 13:51

As before, the time interval starting in August 2007 is split into two parts, or phases -- the "moderate" and the high volatility one, whose features are then compared. Among the currency pairs looked at so far in this series of "crisis" reports, EUR/CHF seems to be in a class of its own: unlike EUR/JPY, EUR/USD, and GBP/USD, and especially EUR/GBP, the autocorrelation patterns of the two phases have similar shapes. So they do for AUD/JPY, but in case of EUR/CHF, the "bipolar disorder" feature of the shape is pronounced more strongly. If this correlation shape is indeed a signature of the carry trade activity, one may conclude that the carry trade activity  in the less volatile EUR/CHF during the crisis remains popular.

Evolution of EUR/CHF exchange rate during the financial crisis, hour.

Fig.1:EUR/CHF during the financial crisis, hour time scale. Time axis is labeled in MM-YY format and spans the interval from August 2, 2007 through December 31, 2008.

Evolution of EUR/CHF autocorrelation peak structure during the financial crisis, hour.

Fig.2: Evolution of EUR/CHF autocorrelation peak structure during the financial crisis, hour time scale. Time bin is two weeks wide. The peak structure is represented by three correlation values: the one for the zero lag (essentially a volatility measure) downscaled by 10 for easier visual comparison, the one at one hour lag and the one at two hour lag. Time axis is labeled in MM-YY format and spans the interval from August 2, 2007 through December 31, 2008. Only trading hours from 1am to 1pm New York time (European trading hours), usually rich in non-trivial correlations, are included.

As before, the time interval starting in August 2007 is split into two parts, the "moderate" and the high volatility one, whose features are then compared. I define the visible phase of the present financial crisis to begin on August 16, 2007, the day of Countrywide Financial near-bankruptcy event, followed by an extraordinary half-percent Fed discount rate cut next day. This study covers 74 weeks from August 2, 2007 through December 31, 2008.

Fig.2 shows the evolution of the correlation structure in the vicinity of zero time lag, representing the correlation structure as a triplet of correlation values: those at zero, one and two hour lags. The increased volatility shows up as the increase in the magnitude of all these values, with variance (a measure of volatility) being fairly well represented by the magnitude of the zero time lag value.

The sub-range of extreme volatility can be roughly defined as the last 18 weeks of this 74-week range. Thus, I divide the time interval under study in two unequal parts, those of (relatively speaking) low and high volatility. The low volatility phase is from August 2, 2007 through August 27, 2008. The high volatility phase is from August 28 through the end of 2008. For the two time intevals defined, the autocorrelation is investigated in Fig.3 as a function of its time lag, rather than function of time as in Fig.2.

 

In this study, I only look at trading activity taking place from 1am to 1pm New York time, since the experience shows it to be the richest in non-trivial correlations.

Autocorrelation of logarithmic returns in EUR/CHF, European trading hours, hour scale, from August 2, 2007 to August 27, 2008. Autocorrelation of logarithmic returns in EUR/CHF, European trading hours, hour scale, from August 28, 2008 to January 01, 2009.

Fig.3: Autocorrelation of logarithmic returns in EUR/CHF for the European (Eurasian) trading shown against the backdrop of statistical noise (red). Top panel: the measurement time range is for the relatively low volatility phase of the crisis, from August 2, 2007 through August 27, 2008. Bottom panel: same for the high volatility phase, from August 28, 2008 through the end of 2008. The noise is obtained from martingale simulations based on the recorded volatilities of EUR/CHF in the trading hours under study for the period. The noise is presented as mean plus-minus 1 RMS, where RMS characterizes the distribution of the correlation value obtained for each particular bin by analyzing 20 independent simulated uncorrelated time series of the same average volatility.

In top and bottom panel of Fig.3, we see the familial pattern of "bipolar disorder", a tendency to form alternating rises and falls on next-hour time scale, more pronounced than in a fully unpredictable time series of the same volatility. This pattern shows up as negative deeps surrounding the zero-time lag peak, as has been seen before in forex exchange rates with considerable interest rate differential at stake, such as AUD/USD, AUD/JPY, GBP/JPY, EUR/CHF itself, and also in EUR/GBP and CHF/JPY, and in the LIBOR time series analyses.

The data used are from the period 2002-08-02 00:00:00 to 2009-01-01 00:00:00, New York time.

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Last Updated ( Monday, 04 January 2010 12:41 )