whether there are consistent patterns in the level of trend.
One question we hope to address using the SNR is how fourth quarter trends compare to the remainder of the year, on both a sector and overall level for futures. We can start by examining the SNR of a representative set of futures contracts from four different sectors (equity indices, commodities, currencies, and interest rates) from 1990 onwards. The average SNR from Q4 can be compared to the average SNR from quarters 1-3 by using a paired Student’s T-test. The null hypothesis of Q4 SNR equaling Q1-3 SNR is rejected in favor of the alternative that Q4 SNR is greater at the 10% level (p-value = 0.090, t=1.37). While this level of significance may only be modest, it does suggest that, at the very least, the trendiness of all quarters is not necessarily uniform.
To take this analysis a step further, we form sector- level SNR indices, which are the individual futures’ SNR indices averaged at the sector level. Since there are only 4 sectors we compare the values of Q4 SNR to the values of Q1-Q3 SNR. This results in an unequal sample size (25 observations for Q4 PL, 75 for Q1-Q3 PL), necessitating a Welch Two Sample T-test. However, this test has the unfortunate consequence of assuming that each sample follows a Gaussian distribution, but quarterly SNR fails a Jarque-Bera test for normality. Regardless, the t-test in Table 1 might give some insight into the source of the differing Q4 SNR.
Fig.3 NewEdge Returns versus SNR Index 0.15
Referring to Table 1 of p-values, we find that only one sector deviates at the 10% level in Q4 from the remainder of the year. Commodities tended to have stronger trends in Q4.
“Commodities tended to have stronger trends in Q4... we should also expect to see higher than average CTA returns in Q4.”
If this Q4 effect on trends exists, and if CTA returns relate positively to the trend index, we should also expect to see higher than average CTA returns in
Q4. We can perform the same t-test on Newedge CTA index quarterly returns. The null hypothesis that Newedge CTA Q4 returns have the same mean as Q1-Q3 is rejected in favor of the alternative that Q4 is greater at the 1% level (p-value = 0.00135, t=3.17). The average annualised return in Q4 was 14.4% vs. 2.67% in the remaining quarters. This effect is also apparent in other CTA indices, namely the Newedge CTA Trend Index, which has an even starker difference at 22.7% annualised in Q4 vs. 2.6% in the remaining quarters.
The available evidence suggests that commodity trends tend to be much stronger in Q4, possibly leading CTAs to perform much better than average during this period. In future research it may be worthwhile investigating what contributes to these Q4 trends (perhaps relatively low volatility or seasonal effects reflected in prices), as well as how to incorporate this information in the systems underlying a CTA strategy.
Relating SNR to CTA Crisis Alpha One appealing characteristic of CTAs is their performance under periods of market distress, or crisis. If we flag periods as crises using the following criterion: S&P 500 Index monthly returns below their 10% quantile (-4.7%), we observe that the Newedge CTA index realised an annual return of 19.5% in these months, compared to 3.3% in non-crisis periods. Based on the previous analysis, it is possible that this crisis alpha is in part driven by an increase in the
Fig.4 S&P Index Monthly Returns 80
0.10
60
0.05 40 0.00 20 -0.05 0 0.10 0.15 SNR INDEX LEVEL 0.20 -15 -10 -5 05 10 %
17
% PL
FREQUENCY
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