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A Complete Guide to the Futures mArket
series. For example, a 15­year test run for a typical market would require using approximately 60 to  
90 individual contract price series. Moreover, using the individual contract series requires an algo­
rithm for determining what action to take at the rollover points. As an example of the type of problem 
that may be encountered, it is entirely possible for a given system to be long in the old contract and 
short in the new contract or vice versa. These problems are hardly insurmountable, but they make the 
use of individual contract series a somewhat unwieldy approach.
The awkwardness involved in using a multitude of individual contracts is not, however, the main 
problem. The primary drawback in using individual contract series is that the period of meaningful 
liquidity in most contracts is very short—much shorter than the already limited contract life spans. 
T o see the scope of this problem, examine a cross section of futures price charts depicting the price 
action in the one
­year period prior to expiration. In many markets, contracts don’t achieve meaning­
ful liquidity until the final five or six months of trading, and sometimes even less. This problem was 
illustrated in Chapter 5. The limited time span of liquid trading in individual contracts means that any 
technical system or method that requires looking back at more than about six months of data—as 
would be true for a whole spectrum of longer
­term approaches—cannot be applied to individual 
contract series. Thus, with the exception of short­term system traders, the use of individual contract 
series is not a viable alternative. It’s not merely a matter of the approach being difficult but, rather, its 
being impossible because the necessary data simply do not exist.
 ■ Nearest Futures
The problems in using individual contract series as just described has led to the construction of vari­
ous linked price series. The most common approach is almost universally known as nearest futures. 
This price series is constructed by taking each individual contract series until its expiration and then 
continuing with the next contract until its expiration, and so on. This approach may be useful for 
constructing long
­term price charts for purposes of chart analysis, but it is worthless for providing a 
series that can be used in the computer testing of trading systems.
The problem in using a nearest futures series is that there are price gaps between expiring and new 
contracts—and quite frequently these gaps can be very substantial. For example, assume the July corn 
contract expires at $4 and that the next nearest contract (September) closes at $3.50 on the same day. 
Assume that on the next day September corn moves from $3.50 to $3.62. A nearest futures price series 
will show the following closing levels on these two successive days: $4, $3.62. In other words, the near­
est futures contract would imply a 38
­cent loss on a day on which longs would have enjoyed (or shorts 
would have suffered) a price gain of 12 cents. This example is by no means artificial. In fact, it would 
be easy to find a plethora of similarly extreme situations in actual price histories. Moreover, even if the 
typical distortion at rollover is considerably less extreme, the point is that there is virtually always some 
distortion, and the cumulative effect of these errors would destroy the validity of any computer test.
Fortunately, few traders are naive enough to use the nearest futures type of price series for computer 
testing. The two alternative linked price series described in the next sections have become the approaches 
employed by most traders wishing to use a single price series for each market in computer testing.