low)? The answer to these questions is
that there are no precise specifi cations; in each case, the choice of a qualifying condition is a subjec-
tive one. However, Figures 9.1 through 9.4 should provide an intuitive sense of the types of days
that qualify as spikes.
 FIGURE  9.1 Spike High: Cotton Continuous Futures
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CHART PATTERNS
 FIGURE  9.2 Spike High: Copper Continuous Futures
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 FIGURE  9.3 Spike High: Swiss Franc Continuous Futures
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112A COMPLETE GUIDE TO THE FUTURES MARKET
 It is possible, though, to construct a mathematically precise defi nition for spike days. An example
of such a defi nition for a spike high might be a day that fulfi lled all three of the following conditions
(the defi nition for a spike low day would be analogous):
 1. H t − Max( H t −1 , H t +1 ) > k · ADTR 10 ,
 where H t = high on given day
 H t −1 = high on preceding day
 H t +1 = high on succeeding day
 k = multiplicative factor that must be defi ned (e.g., k = 0.75)
 ADTR 10 = average daily true range during past 10 days 1
 2. H t − C t > 3 · ( C t − L t ),
 where C t = close on given day
L t = low on given day
 3. H t > maximum high during past N days, where N = constant that must be defi ned (e.g., N = 50)
 The first of the preceding conditions assures us that the spike high will exceed the surround-
ing highs by an amount at least equal to three-quarters of the past 10-day average true range
(assuming the value of k is defined as 0.75). The second condition assures us that the spike day’s
close will be in the lower quartile of its range. The third condition, which requires that the spike
day’s high exceed the highest high during the past 50 days (assuming N = 50), guarantees that
 FIGURE  9.4 Spike Lows: British Pound Continuous Futures
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 1 The true range is equal to the true high minus the true low . The true high is the maximum of the current day’s
high and the previous day’s close. The true low is the minimum of the current day’s low and the previous day’s
close.
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CHART PATTERNS
the day was preceded by an upswing. (Generally speaking, higher values of N will require larger
prior advances.)
 The three-part definition just provided for a spike high day is only intended to offer an
example of how a mathematically precise definition can be constructed. Many other definitions
are possible.
 reversal Days
 The standard defi nition of a reversal high day is a day that makes a new high in an upmove and then
reverses to close below the preceding day’s close. Analogously, a reversal low day is a day that makes
a new low in a decline and then reverses to close above the preceding day’s close. The following dis-
cussion focuses on reversal high days, but mirror-image comments would apply to reversal low days.
 Similar to spike highs, a reversal high day is generally interpreted as suggesting a buying climax and
hence a relative high. However, the condition required for a reversal high day by the standard defi ni-
tion is a relatively weak one, meaning that reversal high days are fairly common. Hence, while many
market highs are reversal days, the problem is that the majority of reversal high days are not market
highs. Figure 9.5 , which illustrates this point, is fairly typical. It shows the fi nal leg of the crude oil
market’s historic rally to its all-time high in July 2008 and its equally impressive sell-off in the follow-
ing months. Note that although a reversal high day occurred just a few days before the July top, it had
been preceded by eight other reversal days since late February, only one of which (the seventh, in late
 FIGURE  9.5 Reversal Days: WTI Crude Oil Continuous Futures
 Note: R = reversal day.
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114A COMPLETE GUIDE TO THE FUTURES MARKET
May) was followed by a downswing of any signifi cance. The reversal low days that occurred from late
July to December paint a similar picture: Given crude oil futures fell another $20 before bottoming
in February 2009 (not shown), even the fi nal signal in December 2008 was extremely premature.
Figure 9.6 depicts another example of the commonplaceness of premature reversal day signals. In this
case, a reversal day actually occurred at the exact peak of a major rally dating back to the beginning of
2009. This incredible sell signal, however, was preceded by eight other reversal days, the majority of
which occurred far earlier in the advance. Anyone who might have traded this market based on rever-
sal signals would probably have thrown in the towel well before the valid signal fi nally materialized.
 In the examples just provided, at least a reversal day signal occurred at or near the actual high.
Frequently, however, an uptrend will witness a number of reversal highs that prove to be false signals
and then fail to register a reversal high near the actual top. It can be said that reversal high days suc-
cessfully call 100 out of every 10 highs. In other words, reversal days provide occasional excellent
signals, but far more frequent false signals.
 In my opinion, the standard defi nition of reversal days is so prone to generating false signals that
it is worthless as a trading indicator. The problem with the standard defi nition is that merely requir-
ing a close below the prior day’s close is much too weak a condition. Instead, I suggest defi ning a
reversal high day as a day that witnesses a new high in an upmove and then reverses to close below
the preceding day’s low . (If desired, the condition can be made even stronger by requiring that the
close be below


ading indicator. The problem with the standard defi nition is that merely requir-
ing a close below the prior day’s close is much too weak a condition. Instead, I suggest defi ning a
reversal high day as a day that witnesses a new high in an upmove and then reverses to close below
the preceding day’s low . (If desired, the condition can be made even stronger by requiring that the
close be below the low of the prior two days.) This more restrictive defi nition will greatly reduce
the number of false reversal signals, but it will also knock out some valid signals. For example, this
 FIGURE  9.6 Reversal Days: Copper Continuous Futures
 Note: R = reversal day.
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115
CHART PATTERNS
revised defi nition would have eliminated all but the fourth signal in Figure 9.5 . In Figure 9.6 the
more restrictive defi nition for a reversal day would have avoided all but the fourth signal and the
ninth (fi nal and valid) signal.
 A reversal day may sound somewhat similar to a spike day, but the two patterns are not equiva-
lent. A spike day will not necessarily be a reversal day, and a reversal day will not necessarily be a
spike day. For example, a spike high day may not close below the previous day’s low (or even below
the previous day’s close, as specifi ed by the standard defi nition), even if the close is at the day’s low .
As an example of the reverse case, a reversal high day may not signifi cantly exceed the prior day’s
high, as required by the spike high defi nition, or exceed the subsequent day’s high at all, since the
subsequent day’s price action is not part of the reversal day defi nition. Also, it is possible that a rever-
sal day’s close may not be near the low , a standard characteristic of a spike day, even if it is below the
previous day’s close.
 Occasionally, a day will be both a reversal day and a spike day. Such days are far more signifi cant
than days that are only reversal days. An alternative to using the more restrictive defi nition for a
reversal day is using the standard defi nition, but requiring that the day also fulfi ll spike day conditions.
(Although a day that met both the strong reversal day condition and the spike day conditions would
be most meaningful of all, such days are fairly rare.) Figure 9.7 provides an example of a day that met
both spike and reversal low day conditions. Figure 9.8 highlights three days: a spike and reversal high
day that marked the high of the rally, a spike and reversal low day several days later that was followed
by a few days of sideways price action, and a spike and reversal low day that was followed by a correc-
tion within the prevailing downtrend.
 FIGURE  9.7 Spike and Reversal Day: July 2008 Soybeans
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116A COMPLETE GUIDE TO THE FUTURES MARKET
 thrust Days
 An upthrust day is a day with a close above the previous day’s high, while a downthrust day is a day
with a close below the previous day’s low . The signifi cance of thrust days is tied to the concept that the
close is by far the most important price of the day. A single thrust day is not particularly meaningful,
since thrust days are quite common. However, a series of upthrust days (not necessarily consecutive)
would refl ect pronounced strength. Similarly, a series of downthrust days would refl ect pronounced
market weakness.
 During bull markets upthrust days signifi cantly outnumber downthrust days—see, for example,
the especially bullish mid-May to early July period in Figure 9.9 . Conversely, in bear markets down-
thrust days signifi cantly outnumber upthrust days—see the July–September period in Figure 9.10 .
And, as should come as no surprise, in sideways markets, upthrust and downthrust days tend to be in
rough balance—for example, the March to mid-April period in Figure 9.9 and the October–November
period in Figure 9.10 .
 run Days
 A run day is a strongly trending day. Essentially, a run day is a more powerful version of a thrust day
(although it is possible for a run day to fail to meet the thrust day condition). Run days are defi ned
as follows:
 FIGURE  9.8 Spike and Reversal Days: Mexican Peso Continuous Futures
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CHART PATTERNS
 FIGURE  9.9 Upthrust and Downthrust Days in Bull Market: E-Mini S&P 500
Continuous Futures
 Note: /uni2191 = upthrust day; /uni2193 = downthrust day.
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 FIGURE  9.10 Upthrust and Downthrust Days in Bear Market: December 2014 Euro
 Note: /uni2191 = upthrust day; /uni2193 = downthrust day.
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118A COMPLETE GUIDE TO THE FUTURES MARKET
Up run day. A day that meets the following two conditions:
 1. The true high of the run day is greater than the maximum true high of the past
N days (e.g., N = 5).
 2. The true low on the run day is less than the minimum true low on the
subsequent N days.
Down run day. A day that meets the following two conditions:
 1. The true low of the run day is less than the minimum true low of the past N days.
 2. The true high on the run day is greater than the maximum true high on the
subsequent N days.
 As can be seen by these defi nitions, run days cannot be defi ned until N days after their occurrence.
Also, note that although most run days are also thrust days, it is possible for the run day conditions to
be met on a day that is not a thrust day. For example, it is entirely possible for a day’s low to be lower
than the past fi ve-day low , its high to be higher than the subsequent fi ve-day high, and its close to be
higher than the previous day’s low .
 Figures 9.11 and 9.12 provide examples of run days (based on a defi nition of

eBooks\A Complete Guide to the Futures Market Technical Analysis, Trading Systems, Fundamental Analysis, Options, Spreads\A Complete Guide to the Futures Market Technical Analysis, Trading Systems, Fundamental Analysis, Options, Spreads.pdf


e also thrust days, it is possible for the run day conditions to
be met on a day that is not a thrust day. For example, it is entirely possible for a day’s low to be lower
than the past fi ve-day low , its high to be higher than the subsequent fi ve-day high, and its close to be
higher than the previous day’s low .
 Figures 9.11 and 9.12 provide examples of run days (based on a defi nition of N = 5). As these charts
show , run days tend to occur when a market is in a trend run—hence the name. The materialization
of up run days, particularly in clusters, can be viewed as evidence the market is in a bullish phase (see
Figure 9.11 ). Similarly, a predominance of down run days provides evidence the market is in a bearish
state (see Figure 9.12 ). In Chapter 17 , we use the concept of run days to construct trading systems.
 FIGURE  9.11 Run Days in Bull Market: Euro Stoxx 50 Continuous Futures
Note: /uni2191 up run day; /uni2193 down run day.
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119
CHART PATTERNS
Note: Although the basic premise of thrust days and run days would apply to longer time frames,
it does not hold on intraday charts. The closing prices of intraday bars—especially on very short time
frames, such as one or two minutes—do not carry the same weight as the closing prices of daily and
weekly bars, which mark the end of signifi cant trading periods.
 Wide-ranging Days
 A wide-ranging day is a day whose volatility signifi cantly exceeds the average volatility of recent trad-
ing days. Wide-ranging days are defi ned as follows:
Wide-ranging day . A day the volatility ratio (VR) is greater than k (e.g., k = 2.0). The
VR is equal to today’s true range divided by the average true range of the past N -day
period (e.g., N = 15).
 Wide-ranging days can have special signifi cance. For example, a wide-ranging day with a
strong close that materializes after an extended decline often signals an upside trend reversal.
Similarly, a wide-ranging day with a weak close that occurs after an extended advance can signal a
downside reversal. In Figure 9.13 , strong-closing wide-ranging days marked the reversals of two
downswings in euro futures. (Note that although the back-to-back wide-ranging days in July did
not close in the upper reaches of their respective ranges, both closed near or above the previous
days’ highs.) Figure 9.14 features two sets of consecutive weak-closing wide-ranging days that
 FIGURE  9.12 Run Days in Bear Market: March 2015 Sugar
 Note: /uni2191 = up run day; /uni2193 = down run day.
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120A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.13 Wide-Ranging Up Days: Euro Continuous Futures
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 FIGURE  9.14 Wide-Ranging Down Days: Silver Continuous Futures
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ended rallies in silver in dramatic fashion. The weekly chart inset shows these events marked the
eff ective end of the market’s longer-term uptrend, ushering in an extended period of sideways-
to-lower price action.
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CHART PATTERNS
 Figures 9.15 and 9.16 highlight days that satisfy the previously described example of wide-ranging
day criteria: The true range of each wide-ranging day is greater than twice the average true range of
the preceding 15 days. In Figure 9.15 , the fi rst of these days, a weak-closing wide-ranging day in May
2012 marked the defi nitive end of a WTI crude oil rally following the consolidation that had formed
near the market highs. The second downside wide-ranging day had no special signifi cance, as it formed
after a large decline had already occurred. The third (strong-closing) wide-ranging day signaled a
major market reversal to the upside.
 In Figure 9.16 there are four wide-ranging days, the fi rst three of which were the start of major
trend reversals; the fourth failed to witness any follow-through price action. However, there is an
important caveat: The “wide-ranging day” in early May, which signaled a reversal near the market
top, did not, in fact, strictly meet the wide-ranging day criteria based on the parameters we used as
an example (2.0 multiple and 15 days)—its true range was only 1.94 times the size of the 15-day
average true range. Had we instead chosen a multiple of 1.9 instead of 2.0 to defi ne wide-ranging
days, this day would have represented a wide-ranging day without any qualifi cation. There is noth-
ing special about the parameter values of 2.0 and 15 days chosen in our example. Moderate shifts of
these values up or down would still preserve the spirit of the wide-ranging day, as was indeed the case
with the early May wide-ranging day, which had a larger-than-normal range with a very weak close
following a major uptrend. There is a trade-off in choosing the parameter value for the multiple: The
lower the multiple chosen to defi ne wide-ranging days, the greater the probability of capturing valid
wide-ranging day reversal signals, but the greater the chance of identifying wide-ranging days that are
meaningless. In this context, it may make sense for a trader to use more than one set of parameter
values to defi ne wide-ranging days to be aware of days that just miss the selected defi nition. Of course,
days defi ned by higher multiples would carry greater weight.
 FIGURE  9.15 Wide-Ranging Up and Down Days: October 2012 WTI Crude Oil
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122A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.16 Wide-Ranging Up and Down Days: September 2011 Coff ee
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 Figures 9.17 and 9.18 show instances of wide-ranging bars on diff erent timeframes. The wide-
ranging week


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122A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.16 Wide-Ranging Up and Down Days: September 2011 Coff ee
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 Figures 9.17 and 9.18 show instances of wide-ranging bars on diff erent timeframes. The wide-
ranging weeks in Figure 9.17 marked the beginning of an uptrend in Japanese yen futures that
extended into early 2012, as shown in the monthly chart inset. In Figure 9.18 the weak-closing
wide-ranging hourly bar reversed a seven-day advance. In Chapter 17 , we will use the concept of
wide-ranging days as the primary element in constructing a sample trading system.
 ■ Continuation Patterns
Continuation patterns are various types of congestion phases that materialize within long-term trends.
As the name implies, a continuation pattern is expected to be resolved by a price swing in the same
direction that preceded its formation.
 triangles
 There are three basic types of triangle patterns: symmetrical (see Figures 9.19 through 9.21 ), ascend-
ing (Figures 9.22 and 9.23 ), and descending (Figures 9.24 and 9.25 ). A symmetrical triangle is usually
followed by a continuation of the trend that preceded it, as in Figures 9.19 through 9.21 . Conven-
tional chart wisdom suggests that nonsymmetrical triangles will yield to a trend in the direction of
the slope of the hypotenuse, as is the case in Figures 9.22 through 9.25 . However, the direction of the
breakout from a triangle formation is more important than the type. For example, in Figure 9.26 ,
although the two congestion patterns are descending triangles—and the second is preceded by a price
decline—both break out to the upside and are followed by rallies.
123
CHART PATTERNS
 FIGURE  9.17 Wide-Ranging Up W eeks: Japanese Y en Continuous Futures
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 FIGURE  9.18 Wide-Ranging Down Bar: September 2015 E-Mini Nasdaq 100 Futures
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124A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.19 Symmetrical Triangle: Japanese Y en Continuous Futures
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 FIGURE  9.20 Symmetrical Triangle: March 2015 DAX
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125
CHART PATTERNS
 FIGURE  9.21 Symmetrical Triangle: Copper Continuous Futures
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 FIGURE  9.22 Ascending Triangle: Euro Stoxx 50 Continuous Futures
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126A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.24 Descending Triangle: Euro Continuous Futures
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 FIGURE  9.23 Ascending Triangle: Euro Continuous Futures
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127
CHART PATTERNS
 FIGURE  9.26 Descending Triangles with Upside Breakouts: 10- Y ear T -Note
Continuous Futures
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 FIGURE  9.25 Descending Triangle: September 2015 E-Mini Dow
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128A COMPLETE GUIDE TO THE FUTURES MARKET
 Flags and pennants
 Flags and pennants are narrow-band, short-duration (e.g., one to three weeks) congestion phases
within trends. The formation is called a fl ag when it is enclosed by parallel lines and a pennant when
the lines converge. Figures 9.27 through 9.31 illustrate both types of patterns. Figure 9.29 shows
fl ags forming on a weekly chart, while Figure 9.30 shows fl ags and pennants on an intraday chart.
 Pennants may appear to be similar to triangles, but they diff er in terms of time: the triangle has a
longer duration. Similarly, the diff erence between a horizontal fl ag and a trading range is a matter of
duration. Among the many fl ags and pennants in Figure 9.27 , for example, there are two congestion
patterns (in August–September 2011 and January–February 2012) that could be classifi ed as either
long fl ags or pennants or short trading ranges or triangles. Regardless of which name these patterns
are given, their implication is the same: fl ags and pennants typically represent pauses in a major trend.
In other words, these patterns are usually followed by price swings in the same direction as the price
swings that preceded their formation.
 A breakout from a fl ag or pennant can be viewed as a confi rmation the trend is continuing and a
trading signal in the direction of the trend. Since breakouts are usually in the direction of the main
trend, however, I prefer to enter positions during the formation of the fl ag or pennant, anticipating
the probable direction of the breakout. This approach allows for more advantageous trade entries,
without a signifi cant deterioration in the percentage of correct trades, since reversals following
breakouts from fl ags and pennants are about as common as breakouts in the counter-to-anticipated
direction. Following a breakout from a fl ag or pennant, the opposite extreme of the formation can be
used as an approximate stop-loss point.
 FIGURE  9.27 Flags and Pennants: Natural Gas Continuous Futures
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129
CHART PATTERNS
 FIGURE  9.28 Flags and Pennants: March 2015 Wheat
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 FIGURE  9.29 Flags and Pennants: Soymeal Continuous Futures
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130A


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129
CHART PATTERNS
 FIGURE  9.28 Flags and Pennants: March 2015 Wheat
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 FIGURE  9.29 Flags and Pennants: Soymeal Continuous Futures
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130A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.30 Flags and Pennants: September E-Mini Nasdaq 100
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 FIGURE  9.31 Flags and Pennants: Euro Schatz Continuous Futures
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131
CHART PATTERNS
 A signifi cant penetration of a fl ag or pennant in the opposite-to-anticipated direction—that is,
counter to the main trend—can be viewed as a signal of a potential trend reversal. For example, in
Figure 9.31 note that after a strong rally that included pennant breakouts in the direction of the main
trend, downside breakouts from the two fl ags that formed in June and August–September marked
short-term and longer-term highs.
 Flags and pennants typically point in the opposite direction of the main trend. This characteristic
is exhibited by the majority of fl ags and pennants illustrated in Figures 9.27 through 9.31 . The direc-
tion in which a fl ag or pennant points, however, is not an important consideration. In my experience,
I have not found any signifi cant diff erence in reliability between fl ags and pennants that point in the
same direction as the main trend as opposed to the more usual opposite slope.
 Flags or pennants that form near the top or just above a trading range can be particularly potent
bullish signals. In the case where a fl ag or pennant forms near the top of a trading range, it indicates
that the market is not backing off despite having reached a major resistance area—the top of the
range. Such price action has bullish implications and suggests that the market is gathering strength
for an eventual upside breakout. In the case where the fl ag or pennant forms above the trading range,
it indicates that prices are holding above a breakout point, thereby lending strong confi rmation to
the breakout. Generally speaking, the more extended the trading range, the greater the potential
signifi cance of a fl ag or pennant that forms near or above its top. Figures 9.32 through 9.34 provide
examples of fl ags or pennants that materialized near the top or above trading ranges and proved to be
precursors of price advances.
 FIGURE  9.32 Flag Near T op of Trading Range as Bullish Signal: U.S. Dollar Index
Continuous Futures
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132A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.33 Flag Above T op of Trading Range as Bullish Signal: Live Cattle
 Continuous Futures
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 FIGURE  9.34 Flag Near T op of Trading Range as Bullish Signal: June 2011 Heating Oil
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133
CHART PATTERNS
 For similar reasons, fl ags or pennants that form near the bottom or just below trading ranges are
particularly bearish patterns. Figures 9.35 through 9.37 provide examples of fl ags or pennants that
materialized near the bottom or below trading ranges and proved to be harbingers of price declines.
 FIGURE  9.35 Flag Near Bottom of Trading Range as Bearish Signal: October 2015
WTI Crude Oil
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 FIGURE  9.36 Flag Near Bottom of Trading Range as Bearish Signal: Japanese Y en
Continuous Futures
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134A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.37 Flag Near Bottom of Trading Range as Bearish Signal: Copper Continuous
Futures
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 ■ Top and Bottom Formations
 V tops and Bottoms
 The “V” formation is a turn-on-a-dime type of top (see Figure 9.38 ) or bottom (see Figure 9.39 ).
One problem with a V top or bottom is that it is frequently diﬃ cult to distinguish from a sharp
correction unless accompanied by other technical indicators (e.g., prominent spike, signifi cant
reversal day, wide gap, wide-ranging day). The V top in Figure 9.38 did contain such a clue—a
spike day—whereas the V bottom in Figure 9.39 was unaccompanied by any other evidence of a
trend reversal.
 Double tops and Bottoms
 Double tops and bottoms are exactly what their names imply. Of course, the two tops (or bottoms)
that make up the pattern need not be exactly the same, only in the same general price vicinity. Double
tops and bottoms that materialize after large price moves should be viewed as strong indicators of a
major trend reversal. Figure 9.40 illustrates a major double top in weekly Euro Bobl futures, while
Figure 9.41 shows a double top on the daily chart for Canadian dollar futures. (Continuous futures
are used for most of the charts illustrating double tops and bottoms because the liquid trading period
for most individual contracts is usually not long enough to display the time span encompassing these
135
CHART PATTERNS
patterns and the preceding and succeeding trends.) Figure 9.42 shows a major double bottom in the
E-mini Nasdaq 100 futures. Figure 9.43 depicts a double bottom on a two-minute chart: In this case
the pattern preceded an explosive upmove (nearly 1 percent in less than an hour) in the June 2015
Mini Russell 2000 futures.
 FIGURE  9.38 “V” T op: Wheat Continuous Futures
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 FIGURE  9.39 “V” Bottom: Euro Stoxx 50 Continuou


00 futures. Figure 9.43 depicts a double bottom on a two-minute chart: In this case
the pattern preceded an explosive upmove (nearly 1 percent in less than an hour) in the June 2015
Mini Russell 2000 futures.
 FIGURE  9.38 “V” T op: Wheat Continuous Futures
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 FIGURE  9.39 “V” Bottom: Euro Stoxx 50 Continuous Futures
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136A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.40 Double T op: Euro Bobl W eekly Continuous Futures
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 FIGURE  9.41 Double T op: Canadian Dollar Continuous Futures
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137
CHART PATTERNS
 FIGURE  9.42 Double Bottom: E-Mini Nasdaq 100 Continuous Futures
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 FIGURE  9.43 Double Bottom: June 2015 Mini Russell 2000 Futures
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138A COMPLETE GUIDE TO THE FUTURES MARKET
 As illustrated in Figures 9.40 through 9.43 , a double top (bottom) is considered completed when
prices move below (above) the reaction low (high) between the two tops (bottoms) of the forma-
tion. When the intervening reaction is relatively deep, as for example in Figure 9.44 , it is impractical
to wait for such an “oﬃ cial” confi rmation, and a trader may have to anticipate that the pattern has
formed based on other evidence. For example, in Figure 9.44 , the confi rmation of the double top
did not occur until the market had dropped nearly 20 percent from the May 2008 high (the second
peak of the double top). However, the pennant pattern that formed after the initial downswing from
that high implied the next price swing would also be down. Based on this clue, a trader could have
reasonably concluded a double top was in place, even though the pattern had not yet been completed
according to the standard defi nition. T op and bottom formations with more repetitions (e.g., triple
top or bottom) occur rather infrequently but would be interpreted in the same fashion. Figure 9.45
shows a triple top in weekly DAX futures.
 head and Shoulders
 The head-and-shoulders pattern is one of the best-known chart formations. The head-and-shoulders
top is a three-part formation in which the middle high is above the high points on either side (see
Figure 9.46 ). Similarly, the head-and-shoulders bottom is a three-part formation in which the mid-
dle low is below the low point on either side (see Figures 9.47 and 9.48 ). Perhaps one of the most
common mistakes made by novice chartists is the premature anticipation of the head-and-shoulders
formation. The head-and-shoulders pattern is not considered complete until the neckline—a line
 FIGURE  9.44 Double T op: Platinum Continuous Futures
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139
CHART PATTERNS
 FIGURE  9.45 Triple T op: DAX Continuous Futures
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 FIGURE  9.46 Head-and-Shoulders T op: Sugar Continuous Futures
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connecting the reaction lows or highs separating the shoulders from the head—is penetrated, as
illustrated in these charts. Furthermore, a valid head-and-shoulders pattern is formed only after a
major price move has occurred. Patterns that bear the shape of a head-and-shoulders formation but
lack this requirement can be misleading.
140A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.47 Head-and-Shoulders Bottom: Euro Stoxx 50 Continuous Futures
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 FIGURE  9.48 Head-and-Shoulders Bottom: November 2012 Soybeans
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141
CHART PATTERNS
 Figure 9.48 is noteworthy in that the “head” of the head-and-shoulders bottom consists of twin
lows that constitute a double bottom, a pattern that would have been confi rmed when price traded
above the early December high (short dashed line), as discussed in the previous section. The penetra-
tion of the head-and-shoulders neckline occurred approximately six weeks later.
 Sometimes the distinction between a head-and-shoulders pattern and a triple top (or bottom)
pattern is not clear-cut. For example, Figure 9.49 shows a major long-term top in the U.S. Dol-
lar Index futures in which the ultimate high has slightly lower highs on either side. This formation
could reasonably be categorized as either pattern—regardless, its implication as a top pattern is
the same.
 rounding tops and Bottoms
 Rounding tops and bottoms (also called saucers ) occur somewhat infrequently, but are among the most
reliable top and bottom formations. Figure 9.50 shows a Nikkei 225 continuous futures chart with a
rounding top that formed at the apex of a multiyear high and was followed by a sharp sell-off . Ideally,
the pattern would not contain any “jags,” as this chart does (e.g., the sharply lower low in late June);
however, I consider the main criterion to be whether the outer perimeter conforms to a rounding
shape. Figure 9.51 depicts a rounding top pattern that formed a major peak in soybean continuous
futures in 2014. Although the late-April to early-May price dip prevented a perfect rounding top
pattern, the outer boundary of the March–May price action conformed well to a rounding pattern.
 FIGURE  9.49 Head-and-Shoulders or Triple T op? Dollar Index Continuous Futures
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142A COMPLETE GUIDE TO THE FUTURES MARKET
 Figure 9.5


hough the late-April to early-May price dip prevented a perfect rounding top
pattern, the outer boundary of the March–May price action conformed well to a rounding pattern.
 FIGURE  9.49 Head-and-Shoulders or Triple T op? Dollar Index Continuous Futures
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142A COMPLETE GUIDE TO THE FUTURES MARKET
 Figure 9.52 provides a textbook instance of a rounding bottom pattern in lean hog continuous futures.
Notice that in this example the price action during the bottoming process was relatively smooth and
mostly free of the occasional jagged moves that were present in the previous examples. This rounding bot-
tom was followed by an explosive upmove that began in mid-February 2014. Figure 9.53 shows a briefer
rounding bottom in the Swiss franc that marked the transition from a downturn to an uptrend.
 FIGURE  9.50 Rounding T op: Nikkei 225 Continuous Futures
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 FIGURE  9.51 Rounding T op: Soybean Continuous Futures
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143
CHART PATTERNS
 FIGURE  9.52 Rounding Bottom: Lean Hog Continuous Futures
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 FIGURE  9.53 Rounding Bottom: Swiss Franc Continuous Futures
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 triangles
 Triangles, which are among the most common continuation patterns, can be top and bottom forma-
tions as well. Figures 9.54 through 9.57 illustrate triangle tops and bottoms. As in the case of the
continuation pattern, the key consideration is the direction of the breakout from the triangle.
144A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE  9.54 Triangle T op: Platinum Continuous Futures
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 FIGURE  9.55 Triangle T op: Orange Juice Continuous Futures
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145
CHART PATTERNS
 FIGURE  9.56 Triangle Bottom: DAX Continuous Futures
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 FIGURE  9.57 Triangle Bottom: Copper Continuous Futures
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146A COMPLETE GUIDE TO THE FUTURES MARKET
 The tops in Figures 9.54 and 9.55 took the form of large descending triangles. The downside
breakouts out of both patterns were followed by energetic sell-off s. (Notice also in Figure 9.55 the
two fl ags that formed during the March–May downtrend that followed the penetration of the tri-
angle’s lower boundary. Each would have given traders who missed the initial breakout a chance to
capture at least some of the downmove.) Figure 9.56 shows a triangle bottom in DAX continuous
futures that was followed by a major uptrend. The symmetrical triangle bottom that formed on the
daily copper chart in 2010 (Figure 9.57 ) is shown in the weekly inset to be part of a correction in the
market’s longer-term uptrend.
 Major tops and bottoms may often be consistent with more than one type of pattern. For example,
a case could have been made for defi ning the preceding triangular tops and bottoms as head-and-
shoulders formations with, generally speaking, similar pattern confi rmation points.
 W edge
 In a rising wedge, prices edge steadily higher in a converging pattern (see Figure 9.58 ). In instances
when the successive highs form in a relative tight band, as they do here, the inability of prices to
accelerate on the upside, despite continued probes into new high ground, suggests the existence
of strong scale-up selling pressure. A sell signal occurs when prices break below the lower wedge
line. Figure 9.59 provides an example of a declining wedge. W edge patterns can sometimes take an
extremely long time to complete. The wedge in Figure 9.59 formed over the course of a year, and
even longer-term wedges have been known to occur.
 FIGURE  9.58 Rising W edge: Euro Continuous Futures
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147
CHART PATTERNS
 FIGURE  9.59 Declining W edge: Sugar Continuous Futures
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 Spikes and reversal Days
 These one-day patterns, which often mark relative highs and relative lows, and sometimes major
peaks and bottoms, were discussed in an earlier section of this chapter.

149
I always laugh at people who say, “I’ve never met a rich technician. ” I love that! It is such an
arrogant, nonsensical response. I used fundamentals for nine years and got rich as a technician.
—Marty Schwartz
M
ost traders who have never used chart analysis (and even some who have) are quite skeptical
about this approach. Some of the commonly raised objections include: “How can such a simple
analytical approach work?” “Since key chart points are hardly a secret, won’t large professional traders
sometimes push the market enough to trigger chart stops artificially?” “Even if chart analysis worked
before it was detailed in scores of websites, books, and magazines, isn’t the method too well publi-
cized to still be effective?”
Although the points raised by these questions are basically valid, a number of factors explain why
chart analysis remains an effective trading approach:
 1. Trading success does not depend on being right more than half the time—or, for that matter,
even half the time—as long as losses are rigidly controlled and profitable trades are permitted
to run their course. For example, consider a trader who in March 1991 assumed that September
1992 eurodollars had entered another trading range (see Figure 10.1) and decided to trade in the
direction of any subsequent closin


does not depend on being right more than half the time—or, for that matter,
even half the time—as long as losses are rigidly controlled and profitable trades are permitted
to run their course. For example, consider a trader who in March 1991 assumed that September
1992 eurodollars had entered another trading range (see Figure 10.1) and decided to trade in the
direction of any subsequent closing breakout. Figure 10.2 shows the initial trade signals and liqui-
dation points that would have been realized as a result of this strategy. The implicit assumption is
that stops are placed at the midpoint of the trading range. (The relevant considerations in choos-
ing a stop point are discussed in detail in Chapter 13.) As can be seen in Figure 10.2, the first two
trades would have resulted in immediate losses. Figure 10.3, however, shows the third signal was
the real thing—a long position that would have occurred in time to benefit from a major price
advance that far exceeded the combined price swings on the prior two adverse trades. (Note the
relevant trading range is redefined— that is, widened—after each of the false breakouts.)
Is Chart Analysis
Still Valid?
Chapter 10
150A COMPLETE GUIDE TO THE FUTURES MARKET
 It is noteworthy that although two out of three trades were losers, on balance the trader
would have realized a large net profi t. The key point is that a disciplined adherence to money
management principles is an essential ingredient in the successful application of chart analysis.
 2. Chart analysis can be made much more eff ective by requiring confi rmation conditions for trade
entry, rather than blindly following all technical signals. There is a natural trade-off in the choice
of confi rmation rules: the less restrictive the conditions, the greater the number of false signals;
the more restrictive the conditions, the greater the potential surrendered profi t due to late
entry. Some of the key methods that can be used to construct confi rmation conditions might
include the following: time delays, minimum percent penetration, and specifi c chart patterns
(e.g., the trade must be confi rmed by two subsequent thrust days in the direction of the signal).
 There is no such thing as a best set of confi rmation conditions. In any list of tested alterna-
tives, the indicated best strategy will vary from market to market as well as over time. Thus,
the ultimate choice of confi rmation rules will depend on the trader’s analysis and experience.
In fact, the specifi c choice of confi rmation conditions is one of the pivotal ways in which chart
analysis is individualized.
 As an illustration of how confi rmation conditions might be used, consider the following set
of rules:
 a. Wait three days after signal is received.
 b. For a buy signal, enter trade if the close is above the high since signal was received, or on
the fi rst subsequent day fulfi lling this condition. An analogous condition would apply to
sell signals.
 FIGURE /uni00A010.1 Trading Range Market: September 1992 Eurodollar
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151
IS CHART ANALYSIS STILL VALID?
As can be seen in Figure 10.2 , these rules would have fi ltered out the losing March and May
signals while only modestly delaying the entry point for the subsequent highly profi table buy
signal. Of course, one could also construct examples in which the use of confi rmation condi-
tions is detrimental to the trading results. However, the key point is that the use of confi rmation
rules is one of the primary means of transforming classical chart concepts into a more powerful
trading approach.
 3. Chart analysis is more than just the recognition and interpretation of individual patterns. One
of the earmarks of the successful chart trader is an ability to synthesize the various components
of the overall picture. For example, the trader who recognizes just a trading range in September
1992 Eurodollars (see Figure 10.1 ) would treat upside and downside breakouts equivalently.
However, the more experienced chartist will also consider the broader picture. For example,
by examining the long-term weekly continuous futures chart in early 1991 (see Figure 10.4 ),
the analyst could have noted that the market had just formed a fl ag pattern near the top of a
fi ve-year trading range. This extremely bullish long-term chart picture would have strongly cau-
tioned against accepting any apparent sell signals on the daily chart. Such a more comprehensive
chart analysis could therefore have helped the analyst avert the false sell signal in March (see
Figure 10.2 ) and adopt a much more aggressive trading stance from the long side than would
have been warranted if the situation were viewed as just another trading range.
 Figures 10.5 and 10.6 illustrate a similar example in June 2012 natural gas futures. In ear-
ly 2011 a trader who decided to trade in the direction of a breakout of the October 2010–
January 2011 trading range (again, assuming a stop point in the middle of the range) would have
 FIGURE /uni00A010.2 False Breakout Signals: September 1992 Eurodollar
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152A COMPLETE GUIDE TO THE FUTURES MARKET
 FIGURE /uni00A010.3 Winning Breakout Signal after Two False Signals: September 1992 Eurodollar
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 FIGURE /uni00A010.4 Long- T erm Chart as Part of Comprehensive Analysis: Eurodollar Continuous Futures
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153
IS CHART ANALYSIS STILL VALID?
experienced fi ve losing trades (three buys and two sells) before the August 2011 sell signal that
was followed by an extended downmove. The context provided by the weekly chart (Figure 10.6 ),
however, suggests a trader who was aware of the longer-term downtre


us Futures
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153
IS CHART ANALYSIS STILL VALID?
experienced fi ve losing trades (three buys and two sells) before the August 2011 sell signal that
was followed by an extended downmove. The context provided by the weekly chart (Figure 10.6 ),
however, suggests a trader who was aware of the longer-term downtrend that preceded the
consolidation could have reasonably chosen to ignore upside breakouts and focus exclusively on
downside breakouts in expectation of a continuation of that trend.
 Of course, the preceding examples benefi t from hindsight. However, the point is not to
prove the application of chart analysis would have conclusively indicated the probable continua-
tion of a long-term bull market in eurodollar futures in early 1991 or the likely perpetuation of
the extended downtrend in natural gas futures in 2011, but rather to illustrate the multifaceted
analytical process of the experienced chart trader. It should be clear that the skill and subjectiv-
ity implied in this approach place chart analysis in the realm of an art that cannot be mimicked
by merely following a set of textbook rules. This is a crucial point in understanding how the
chartist approach can remain valid despite widespread publicity.
 4. Assuming some skill in fundamental forecasting (i.e., a better than 50/50 accuracy rate), chart
analysis can be combined with fundamental projections to provide a more eﬀ ective approach. Spe-
cifi cally, if the long-term fundamental forecast indicates the probability of much higher (lower)
prices, only bullish (bearish) chart signals would be accepted. If the fundamental projection
was neutral, both buy and sell signals would be accepted. Thus, the chart analyst who is also a
competent fundamental analyst would have a decided edge over the majority of traders basing
their trading decisions solely on chart-oriented input.
 FIGURE /uni00A010.5 False and Winning Breakout Signals: June 2012 Natural Gas Futures
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154A COMPLETE GUIDE TO THE FUTURES MARKET
 5. The failure of a market to follow through in the direction of a key chart signal is a crucial item
of information often overlooked by novice chartists. Recognizing and acting on these situations
can greatly enhance the eff ectiveness of the chartist approach. This subject is discussed in detail
in Chapter 15 .
 In conclusion, the skeptics are probably correct in claiming that a Pavlovian response to chart sig-
nals will not lead to trading success. However, this assertion in no way contradicts the contention that
a more sophisticated utilization of charts, as suggested by the cited factors, can indeed provide the
core of an eff ective trading plan. In any case, chart analysis remains a highly individualistic approach,
with success or failure critically dependent on the trader’s skill and experience. It would be unreason-
able to expect to play the violin well without some degree of practice and innate talent. Chart analysis
is no diff erent—the sour notes of novice practitioners notwithstanding.
 FIGURE /uni00A010.6 Long- T erm Chart as Part of Comprehensive Analysis: June 2012 W eekly Natural
Gas Futures
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155
Any intelligent fool can make things bigger, more complex, and more violent. It takes a
touch of genius—and a lot of courage to move in the opposite direction.
— Ernst F. Schumacher
 ■ What Is an Indicator?
T echnical indicators are mathematical formulas based on market data—most often prices, but also
occasionally volume and open interest. (In the equity market, other data, such as the number of
advancing or declining issues, are sometimes incorporated in these calculations.) The implicit goal of
most technical indicators is to signal potential changes in market direction that might not be apparent
through direct price analysis or fundamental analysis. The implicit assumption underlying this approach
is that indicators extract or distill useful forecasting information from market data.
Most indicators attempt to translate price action into directional signals in one of two ways:
 1. Comparing current price levels to past price levels to determine the prevailing direction and
magnitude of price change.
 2. Using a smoothing function, such as a moving average, to filter out what are deemed to be ran-
dom fluctuations (“noise”), thus revealing a market’s prevailing trend.
There are any number of ways to accomplish either of these goals, or to combine them. Consider
the simple case of comparing today’s closing price with the most recent 20 days of price action to
determine how much price has changed and whether the close is relatively strong or weak. The fol-
lowing are only some of the possible approaches:
 1. Calculate the difference between the current close and the close 20 days ago.
 2. Calculate the percentage change (ratio) of the current close and the close 20 days ago.
T echnical Indicators
Chapter 11
156
A Complete Guide to the Futures mArket
 3. Determine the current closing price’s position within the 20-day high-low range, or its position
within the range of the highest and lowest closing prices of the past 20 days.
 4. Measure how much the current closing price varies from the “typical” price of the past 20 days
by comparing it (as either a difference or a ratio) to the average (or median) of the other closing
prices during this period.
 5. Alternatively, a shorter-term moving average (or median) value could be substituted for the
closing price in the previous calculation, in which case the indicator would become the differ-
ence between (or ratio of), say, a 3-day moving average and the 20-day moving average.
 6. Use a statistical measurement, such as percentile rank, to determine where the current close
pla


uring this period.
 5. Alternatively, a shorter-term moving average (or median) value could be substituted for the
closing price in the previous calculation, in which case the indicator would become the differ-
ence between (or ratio of), say, a 3-day moving average and the 20-day moving average.
 6. Use a statistical measurement, such as percentile rank, to determine where the current close
places among the 20 most recent closes, or within the 20-day range.
 7. Rather than using the most recent closing price as the reference point, the direction and pace of
price changes over the past 20 days could alternatively be measured by comparing the period’s
aggregate (or average) gains to its aggregate (or average) losses. One example: Divide the sum
(or average) of the positive close-to-close changes over the past 20 days by the sum (or average)
of the absolute negative close-to-close changes over the past 20 days.
All these calculations provide some gauge of how far, and in what direction, a market has moved
over the past 20 days. Moreover, any of the foregoing indicators could be based on values other than
20, expanding the list of possible indicators by another dimension. If this list of possible indicators
seems excessive (or redundant), peruse any trading website, app, or analysis platform, and you are
likely to be confronted by dozens—sometimes in excess of 100—technical indicators, all purport-
edly designed to help interpret and forecast market activity. Grappling with the sheer number of
indicators, and their often cryptic formulas and names, can be a daunting prospect for the new trader
or analyst, who might understandably assume each of these tools has unique properties and specific
purposes.
The truth, however, is that despite the wide array of indicators and the properties ascribed to
them by various proponents and followers, the majority of these tools are based on a handful of basic
mathematical formulas. In fact, variations and combinations of the previously listed seven calculations
provide the basis for a surprisingly large percentage of the most widely referenced technical tools.
One critical consequence of this observation is that there is a high degree of correlation among tech-
nical indicators, even if they might seem to be unrelated at a glance.
Rather than risking a descent down the rabbit hole of comparing the supposed applications and
idiosyncrasies of dozens of technical indicators, the following discussion instead focuses on the basic
types of calculations underlying these indicators and what they can and cannot convey about market
behavior. The goal is to provide the reader with a logical foundation for objectively interpreting and
analyzing technical indicators. In short, readers looking for answers to questions such as “What’s
the best technical indicator?” or “What are the best settings for indicator xyz?” or “Which indicators
are best for trading currency (or grain, or stock index) futures?” should look elsewhere. These are,
in fact, meaningless questions because they presuppose a degree of differentiation among indicators
that does not exist and assume a stability in the performance of individual indicators that is unsup-
ported by empirical evidence.
157
TEChnICAl InDICATORS
 ■ The Basic Indicator Calculations
Most technical indicators incorporate one or more of the following five calculations:
 1. A smoothing function, such as a moving average or moving median.
 2. A comparison of the current data point to a specific past data point, as either a difference (e.g.,
today’s close minus the close 10 days ago) or a ratio (today’s close divided by the close 10 days ago).
 3. A comparison of the current data point to an average (e.g., today’s close minus the average close
of the past 10 days).
 4. A comparison of an average to another average of a different length (e.g., the 10-day moving
average minus the 30-day moving average).
 5. A comparison of the current data point to a past range (e.g., the difference between today’s
close and the lowest low of the past 10 days divided by the difference between the highest high
of the past 10 days and the lowest low of the past 10 days).
Beyond the number of price bars used (the “look-back period”), these calculations allow for a great
deal of variation without altering the basic characteristics of the indicator. For example, a smoothing
function could take the form of a simple moving average, a weighted moving average, an exponen-
tial moving average, or an “adaptive average” that adjusts its length according to changes in market
volatility. Moreover, any of these averages could be based on a bar’s closing price, high, low , open, or
midpoint.
 ■ Comparing Indicators
Figures 11.1 through 11.5 illustrate the five types of indicator calculations defined in the previous sec-
tion and highlight the relationships between them. For reference, we’ll use the following shorthand
to identify these formulas:
Indicator 1: M
a (moving average).
Indicator 2: Close – Close (difference) or Close/Close (ratio).
Indicator 3: Close – M
a (difference between close and moving average) or Close/Ma (ratio
of close and moving average).
Indicator 4: Ma – Ma (difference between two moving averages) or Ma/Ma (ratio of two
moving averages).
Indicator 5: CS (closing strength).
In all cases, subscripts are used to denote the look-back period—for example, “MA 30” refers to a
30-bar moving average, “Close – Close10” refers to the difference between the current close and the
close 10 bars ago, and so on.
In Figure 11.1, a daily price chart of WTI crude oil from August 2015 to May 2016 is overlaid with
10- and 30-day simple moving averages (thin and thick lines, respectively). The lower portion of the
chart contains two indicators. The first is the difference between the most recent close and the close
158A COMPlETE GUIDE TO ThE FUTURES MARKET
10 days earlier (Close – Close 10 ), while the second is the diff erenc


aily price chart of WTI crude oil from August 2015 to May 2016 is overlaid with
10- and 30-day simple moving averages (thin and thick lines, respectively). The lower portion of the
chart contains two indicators. The first is the difference between the most recent close and the close
158A COMPlETE GUIDE TO ThE FUTURES MARKET
10 days earlier (Close – Close 10 ), while the second is the diff erence between the close and the 10-day
moving average (Close – MA 10 ). Both calculations provide a snapshot of the price movement over the
most recent 10 days—how much price has moved relative to each indicator’s respective reference
price. For the fi rst indicator, positive values occur when the current close is above the close 10 days
ago; negative values occur when the current close is below the close 10 days ago. For the second indica-
tor, positive or negative values refl ect closing prices above or below the 10-day average price. notice
that although the two indicators have minor diff erences, their fl uctuations closely mirror each other.
 The indicators in Figure 11.2 are the ratio versions of the indicators in Figure 11.1 —that is, the
result of dividing the current close by the close 10 days ago (Close/Close
10 ), and dividing the cur-
rent close by the 10-day moving average (Close/MA 10 ). note that they appear to be the same as the
indicators in Figure 11.1 except for their scaling. In fact, the indicators in Figure 11.2 are perfectly
correlated to their counterparts in Figure 11.1 . In other words, in terms of trading signal generation,
there is absolutely no diff erence between the two sets of indicators.
 Figure 11.3 returns to the diff erence calculations used in Figure 11.1 , except the look-back
period for both is 30 days instead of 10 days. Again, the indicators appear very similar, although
each is signifi cantly diff erent from its counterpart in Figure 11.1 because of the longer look-back
period: The 30-day indicators in Figure 11.3 highlight far fewer of the shorter-term price highs and
lows and instead trace the contour of the intermediate-term price action. For example, during the
 FIGURE  11.1 Diff erence Indicators: Close – Close vs. Close – MA
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159
TEChnICAl InDICATORS
 FIGURE  11.2 Ratio V ersions of Diff erence Indicators
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 FIGURE  11.3 30-Day V ersions of Close – Close and Close – MA Indicators
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160A COMPlETE GUIDE TO ThE FUTURES MARKET
October–December 2015 period, both indicators are smoother and have a more pronounced down-
ward bias than their 10-day counterparts in Figure 11.1 .
 Figure 11.4 compares the Close – MA 30 indicator from Figure 11.3 with the MA 10 – MA 30 indica-
tor, which represents the diff erence between the 10-day moving average and 30-day moving average.
The use of two moving averages produces an indicator that is closely related to the Close − MA
indicator, but is smoother and a bit less timely (e.g., note the delay between the MA
10 – MA 30 and the
Close – MA 30 indicator in refl ecting the early-April price low).
 Finally, Figure 11.5 compares the Close/Close 10 indicator from Figure 11.2 with the CS 10 indicator,
which shows where the current close falls within the range (high–low) of the most recent 10 days (e.g.,
if the close is the highest price of the most recent 10 days, the indicator reading is 1.00, or 100 percent).
 The similarities between the indicators in Figures 11.1 through 11.5 are substantial and not specifi c to
the time window represented in these charts. Table 11.1 shows the correlation coeﬃ cients
1 for all six pair
combinations of the four 10-day indicator calculations (Close – Close, Close – MA, CS, and MA – MA 2 )
 FIGURE  11.4 Price – MA vs. MA – MA Indicators
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.
 1 The correlation coeﬃ cient, which measures the linear relationship between two data samples, ranges from
–1.00 to +1.00, with –1.00 representing a perfect negative correlation (values moving in exact opposition) and
+1.00 representing perfect positive correlation (values moving exactly in tandem).
 2 The MA – MA calculations in Table 11.1 use three days for the short-term moving average and 10 days for the
long-term moving average.
161
TEChnICAl InDICATORS
 FIGURE  11.5 Close/Close vs. Closing Strength Indicators
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.
 table 11.1 10-Day Indicator Correlations, Crude Oil
Close – Close vs.
Close – Ma
Close – Close vs.
Ma – Ma
Close – Close
vs. CS
Close – Ma vs.
Ma – Ma
Close – Ma
vs. CS
Ma – Ma
vs. CS
 aug. 2015–
May 2016
0.81 0.83 0.81 0.89 0.93 0.83
 May 2005–
May 2016
0.84 0.86 0.77 0.90 0.87 0.78
 during two periods: August 14, 2015 through May 5, 2016 (the period shown in Figures 11.1 through
 11.5 ); and a much longer period, May 5, 2005 through May 5, 2016. The lowest correlation between
any two indicators during the August 2015–May 2016 period was 0.81. The correlations for the 2005–
2016 period were similar, with some pairs registering modestly higher correlations and other pairs
modestly lower correlations. Even the lowest fi gure in Table 11.1 (0.77, for the May 2005–May 2016
Close – Close vs. CS indicator comparison) refl ects a signifi cant level of positive correlation.
162
A Complete Guide to the Futures mArket
Table 11.2 extends the same analysis to three additional markets—corn, E-mini S&P 500, and
euro futures—and from 6 to 10 indicator-pair combinations, based on adding a sixth calculation: the
Up/Down Average (“U/D Avg.”), which is defined as the average positive close-to-close change over
the past N days divided by the average (absolute) negative close-to-close


plete Guide to the Futures mArket
Table 11.2 extends the same analysis to three additional markets—corn, E-mini S&P 500, and
euro futures—and from 6 to 10 indicator-pair combinations, based on adding a sixth calculation: the
Up/Down Average (“U/D Avg.”), which is defined as the average positive close-to-close change over
the past N days divided by the average (absolute) negative close-to-close change over the past N days,
normalized so that it fluctuates in a range from zero to 1.00.
3 Table 11.2 also differs from Table 11.1
in that it is based on 20-day look-back periods (instead of 10), except for the MA – MA indicator,
which uses a short-term moving average length of 10 days and a long-term moving average length
of 30 days.
Although Table 11.2 contains some readings well below the lowest correlation figure in Table 11.1
(mostly for pairs involving the Up/Down Average indicator), the average and median correlations
for the ten indicator combinations shown are still uniformly strong, ranging from a low of 0.54
to a high of 0.87. Table 11.3, which replicates the analysis of Table 11.2 using 60-day look-back
periods instead of 20 (and 20-day and 60-day moving average lengths for the MA – MA indicator),
demonstrates very similar results, with the average/median correlations ranging from a low of 0.49
to a high of 0.90.
The significance of the similarity between the indicator formulas discussed thus far is that they
are the building blocks of a host of popular indicators, especially those known as momentum
indicators, or “oscillators.”
 This group includes, but is by no means limited to, momentum, rate-
of-change (ROC), the stochastic oscillator, the relative strength index (RSI), %R, moving average
table 11.2 20-Day Indicator Correlations
Close
– Close
vs. Close
– Ma
Close
– Close
vs. Ma
– Ma
Close
– Close
vs. CS
Close
– Close
vs. U/D
avg.
Close – Ma
vs. Ma
– Ma
Close
– Ma
vs. CS
Close
– Ma
vs. U/D
avg.
Ma
– Ma
vs. CS
Ma
– Ma
vs. U/D
avg.
CS vs.
U/D
avg.
Crude oil Aug. ’15–May ’16 0.84 0.81 0.84 0.88 0.72 0.95 0.72 0.68 0.69 0.72
May ’05–May ’16 0.88 0.88 0.79 0.57 0.80 0.87 0.52 0.69 0.51 0.53
Corn Aug. ’15–May ’16 0.77 0.84 0.71 0.33 0.53 0.91 0.15 0.45 0.34 0.19
May ’05–May ’16 0.86 0.90 0.71 0.59 0.69 0.80 0.52 0.55 0.53 0.51
S&p 500 Aug. ’15–May ’16 0.90 0.84 0.81 0.81 0.71 0.68 0.79 0.90 0.64 0.66
May ’05–May ’16 0.88 0.84 0.74 0.51 0.67 0.57 0.44 0.86 0.43 0.48
euro Aug. ’15–May ’16 0.80 0.86 0.77 0.77 0.58 0.90 0.74 0.55 0.61 0.75
May ’05–May ’16 0.86 0.90 0.76 0.65 0.70 0.87 0.59 0.61 0.57 0.62
average: 0.85 0.86 0.77 0.64 0.68 0.82 0.56 0.66 0.54 0.56
Median: 0.86 0.85 0.77 0.62 0.69 0.87 0.55 0.64 0.55 0.58
3 The formula for normalizing the indicator values between 0 and 1.00 is: 1 – {1/[1 + (UA/DA)]}, where UA is
the average positive close-to-close change over the past n bars and DA is the absolute value of the average nega-
tive close-to-close change over the past n bars.
163
TEChnICAl InDICATORS
table 11.3 60-Day Indicator Correlations
Close
– Close
vs. Close
– Ma
Close
– Close
vs. Ma
– Ma
Close
– Close
vs. CS
Close
– Close
vs. U/D
avg
Close
– Ma
vs. Ma
– Ma
Close
– Ma
vs. CS
Close
– Ma
vs. U/D
avg
Ma
– Ma
vs. CS
Ma
– Ma vs.
U/D avg
CS vs.
U/D avg
Crude oil Aug. ’15–May ’16 0.85 0.90 0.82 0.60 0.88 0.95 0.83 0.83 0.67 0.75
May ’05–May ’16 0.91 0.92 0.76 0.27 0.90 0.86 0.43 0.74 0.26 0.50
Corn Aug. ’15–May ’16 0.23 0.05 0.42 0.53 0.56 0.90 0.07 0.46 0.22 0.22
May ’05–May ’16 0.87 0.85 0.76 0.68 0.84 0.82 0.61 0.66 0.59 0.58
S&p 500 Aug. ’15–May ’16 0.62 0.13 0.57 0.22 0.82 0.96 0.70 0.81 0.77 0.66
May ’05–May ’16 0.64 0.18 0.60 0.24 0.83 0.88 0.44 0.70 0.40 0.41
euro Aug. ’15–May ’16 0.80 0.74 0.78 0.79 0.70 0.93 0.90 0.60 0.73 0.85
May ’05–May ’16 0.85 0.86 0.78 0.62 0.84 0.88 0.59 0.72 0.53 0.64
average: 0.72 0.58 0.69 0.49 0.80 0.90 0.57 0.69 0.52 0.58
Median: 0.82 0.80 0.76 0.56 0.84 0.89 0.60 0.71 0.56 0.61
 convergence-divergence (MACD), the price (or moving average) oscillator, the commodity chan-
nel index (CCI), and the money flow index (MFI). (Note: There is little consistency in the technical
indicator lexicon, especially with regard to more generic indicators. T erms such as momentum, rate of
change, and price oscillator sometimes refer to different calculations in different sources. The names
used here are widely applied, but may conflict with other sources. The calculations, not the names,
are what are important.)
Figure 11.6 compares five popular indicators: momentum, the “fast” stochastic oscillator, CCI,
RSI, and the MFI. “Momentum” is simply the Close – Close indicator. The fast stochastic is a three-day
moving average of the CS indicator. (The second, thinner line in the stochastic plot in Figure 11.6 is
a three-day moving average of the primary indicator line.) The CCI divides the difference between
price and a moving average (similar to the Close – MA indicator) by a measure of the absolute total
price deviation during the look-back period. The RSI is essentially the U/D Average indicator, except
it uses an exponential smoothing function instead of a simple moving average and is scaled from zero
to 100 instead of zero to 1. The MFI is basically a volume-weighted version of the RSI that magnifies
indicator readings that are accompanied by high trade volume. The precise formulas for these indica-
tors (which are readily available online) are less important than the fact that they are all derived from
our basic indicator calculations and are all highly correlated to each other. Table 11.4 summarizes
the average correlations for 20-day versions of the 10 pair combinations of these five common indica-
tors for the same periods shown in Tables 11.2 and 11.3. As Table 11.4 clearly demonstrates, these
five popular indicators are all highly correlated, with correlations ranging from a low of 0.67 to a
high of 0.94.
The takeaway from this analysis is that all technical indicators that


summarizes
the average correlations for 20-day versions of the 10 pair combinations of these five common indica-
tors for the same periods shown in Tables 11.2 and 11.3. As Table 11.4 clearly demonstrates, these
five popular indicators are all highly correlated, with correlations ranging from a low of 0.67 to a
high of 0.94.
The takeaway from this analysis is that all technical indicators that measure the magnitude and
direction of prices over a given time period must inevitably compare at least two price points or
164A COMPlETE GUIDE TO ThE FUTURES MARKET
groups of prices, which means they must incorporate at least one of the indicator formulas we have
outlined, or a closely related calculation. Figures 11.1 through 11.6 and Tables 11.1 through 11.4
suggest the specifi c type of calculation used is far less important than the time period it surveys in
terms of diff erentiating one indicator from another. This characteristic of indicators is starkly illus-
trated in Figure 11.7 , which compares three indicator calculations (top to bottom): Close – Close
10 ,
MA 3 – MA 10 , and MA 20 – MA 100 . Although the upper and middle indicators use a diff erent type of
calculation, they are very similar. In contrast, the middle and lower indicators use the same type
of calculation but are radically diff erent. The key point is that the upper and middle indicators are
similar because they both track a similar trend length, while the middle and lower indicators are very
 diff erent because the time length surveyed by the lower indicator is much longer. In short, it’s the time
length, not the indicator, that matters.
 table 11.4 Correlations of Common Indicators, Daily Crude Oil
Mom vs.
Stoch
Mom
vs. CCI
Mom
vs. rSI
Mom
vs. MFI
Stoch
vs. CCI
Stoch
vs. rSI
Stoch
vs. MFI
CCI
vs. rSI
CCI
vs. MFI
rSI
vs. MFI
Aug. ’15–May ’16 0.81 0.77 0.87 0.82 0.94 0.87 0.68 0.86 0.69 0.82
May ’05–May ’16 0.78 0.71 0.84 0.82 0.93 0.87 0.72 0.83 0.67 0.81
 FIGURE  11.6 Popular Indicator Comparison
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.

165
TEChnICAl InDICATORS
 FIGURE  11.7 Indicator length vs. Calculation Type
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.
 ■ Moving Average Types
 Moving averages, which are incorporated in many indicators, can be calculated in diff erent ways.
Whereas a simple moving average (SMA) weights all prices equally (i.e., a 10-day average is the sum
of the closing prices of the past 10 days divided by 10), the weighted moving average (WMA) and
exponential moving average (EMA) use multipliers to increase the infl uence of more recent data in
the calculation (see Chapter 16 for details). The logic behind weighting a moving average is based
on an implicit assumption (not necessarily true) that recent price action is more important than
more distant price action when attempting to forecast future price direction. The intent of weight-
ing a moving average is to reduce lag by creating an indicator that is more responsive to directional
changes—a seemingly logical goal, but one that can have drawbacks as well as advantages.
 Table 11.5 shows the results of testing the same basic trading system using simple, weighted, and
exponential moving averages. The system goes long when prices close above the moving average and
goes short when prices close below the moving average. The system was tested on three markets: the
E-mini S&P 500 futures (ES), WTI crude oil futures (Cl), and euro futures (EC), using daily data
from January 30, 2006, through January 28, 2016. In all cases, one contract was traded per signal, and
the moving average length was set to 60 days.
 The results, while based on a small sample of markets, are illustrative. In each market, a diff erent
type of moving average produced the highest net profi t and highest profi t factor (gross profi t/ gross loss).
166A COMPlETE GUIDE TO ThE FUTURES MARKET
The implication is that the search for the “best” smoothing approach is likely to be a fruitless one.
Over time, applied across multiple markets and parameter values, a particular smoothing calculation
is unlikely to demonstrate a meaningful advantage over another. Figure 11.8 helps illustrate why. The
daily crude oil prices in this chart are overlaid with 60-day simple (dashed line), weighted (thick solid
line), and exponential (thin solid line) moving averages. In just a single roughly six-month period,
there are multiple instances of the varying degrees of lag among the three moving averages helping or
 FIGURE  11.8 Moving Average Comparison
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.
 table 11.5 Simple, W eighted, and exponential Moving average Signals
Net profit a No. trades Win % profit Factor b
 eS
Exponential $5,440 163 23.31% 0.98
Simple –$1,635 163 19.63% 0.92
W eighted –$30,860 209 23.44% 0.76
Cl
Simple $175,050 161 24.22% 1.87
Exponential $113,870 178 23.03% 1.42
W eighted $102,010 225 20.44% 1.3
eC
W eighted $59,763 186 24.19% 1.36
Exponential $46,350 202 21.78% 1.29
Simple $29,325 154 21.43% 1.18
a Closed trades plus open trade profit/loss (P/l) at end of test period.
b Reflects closed trades only.
167
TEChnICAl InDICATORS
hurting performance. For example, in March 2015, the market closed above both the WMA and SMA
(triggering long positions) before reversing to close below both averages the next day (triggering
short positions)—a classic example of a “whipsaw” loss that occurs in trend-following strategies dur-
ing congested or volatile market conditions. The EMA escaped this loss.
however, in other instances
of whipsaw trades evident in the chart, it was the WMA or SMA that avoided the losing trade, while
the other two averages did not. Also, note that after the WMA suffered a whipsaw loss in early June
while the SMA did not, in late June the WMA then provided a better short entry as t


rategies dur-
ing congested or volatile market conditions. The EMA escaped this loss.
however, in other instances
of whipsaw trades evident in the chart, it was the WMA or SMA that avoided the losing trade, while
the other two averages did not. Also, note that after the WMA suffered a whipsaw loss in early June
while the SMA did not, in late June the WMA then provided a better short entry as the market turned
sharply lower. Multiply the offsetting benefits and drawbacks illustrated in this chart by similar occur-
rences in multiple markets over many years, and it is easy to see why one smoothing approach is
unlikely to significantly outperform another, other than by chance.
Ultimately, the look-back period will be more important than the particular smoothing tech-
nique. Over time, the difference between using a 40-period EMA and a 40-period SMA will
be much less significant than the difference between using a 40-period EMA and an 80-period
EMA. Once again, it is the time length used in the calculation rather than the calculation type
that matters.
 ■ Oscillators and Trading Signals
The most common type of indicator by far is the one commonly referred to as the momentum
indicator or oscillator, which is a calculation designed to highlight shorter-term swing points and
so-called overbought and oversold levels. All the basic calculations and indicators in Figures
11.1 through 11.7 (using shorter-term look-back periods) could be placed in this category. The
popularity of oscillators is probably driven by the desire of many traders to capture as many of a
market’s twists and turns as possible. The popularity of oscillators, however, is arguably inversely
correlated to their usefulness. T o see why, let’s examine a few examples of applying oscillators
as trading tools.
Figure 11.9 depicts the 10-year T -note futures with a 10-day fast stochastic oscillator line (i.e.,
a three-day moving average of the CS calculation). The indicator’s two horizontal lines at 80 and 20
are default overbought and oversold levels that, according to oscillator conventional wisdom, are
used to indicate points at which price moves are overextended and likely to correct. Thus, over -
bought readings (above 80) signal selling opportunities, and oversold readings (below 20) signal
buying opportunities. Although the oscillator does seem to signal all the price turning points, it does
so prematurely.
The astute reader might argue that the simplistic use of the oscillator to signal trades whenever it
enters overbought/oversold zones may be a suboptimal application of the indicator. What if, instead,
we waited for the indicated reversal to be confirmed before generating a trade signal? For example, a
buy signal might be triggered by the following dual conditions:
 1. The oscillator declines into oversold territory (<20), suggesting an environment potentially
conducive to long positions.
 2. The oscillator then rises back above the oversold threshold (>20), confirming the anticipated
trend reversal from down to up.
168A COMPlETE GUIDE TO ThE FUTURES MARKET
 A trade would be signaled only after the second condition is met. An analogous set of dual condi-
tions would apply to sell signals. Figure 11.10 is the same chart as Figure 11.9 except it illustrates
signals based on adding the confi rmation condition. now , the oscillator seems to perform spectacu-
larly well as a trading tool, generating sells near relative highs and buys near relative lows! Many
novice traders will see a chart such as Figure 11.10 and think they have discovered the perfect trading
system. In fact, it is not uncommon for some vendors to market systems using similar approaches,
illustrating the purported wonderful performance of their system with charts that look very much
like Figure 11.10 .
 So what is wrong with such a dual-condition oscillator application for generating trading signals?
nothing, as long as you can predict that the market will stay in a trading range in the future . The
period shown in Figure 11.10 (late January to mid-June 2016) represents nearly ideal conditions for
short-term indicators such as oscillators to track price swings: the market moved sideways and the
price swings were relatively similar in magnitude. In such environments oscillators can appear to be
almost foolproof trading tools. If, however, the same approach is applied to a trending market—and
keep in mind it’s impossible to know whether a trending or trading range market will prevail in the
future—the results can be disastrous. Figure 11.11 shows the signals that would have resulted from
applying the same dual-condition trade rules in a trending market. In this case, during an eight-
month period when the euro futures declined approximately 16 percent, the same oscillator trig-
gered exactly one sell signal while issuing nine buy signals, including seven consecutive losing buys
from August 2014 to January 2015.
 FIGURE  11.9 Oscillator Signals: Initial Penetration
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.
 Oscillator Signals: Initial Penetration

169
TEChnICAl InDICATORS
 FIGURE  11.10 Oscillator Dual-Condition Signals
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.
 FIGURE  11.11 Oscillator Signals in Trending Market
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.

170
A Complete Guide to the Futures mArket
The bottom line is that oscillators will work well as contrarian trading tools if we can assume the
market will move in a trading range. If the market instead embarks on an extended trend, oscillator-
based signals can lead to huge losses. And while it is easy to identify past trading ranges for which
an oscillator-based trading strategy will produce magnificent hypothetical results, we don’t know
whether a trading range or trending market will prevail in the immediate future. In other


e the
market will move in a trading range. If the market instead embarks on an extended trend, oscillator-
based signals can lead to huge losses. And while it is easy to identify past trading ranges for which
an oscillator-based trading strategy will produce magnificent hypothetical results, we don’t know
whether a trading range or trending market will prevail in the immediate future. In other words, we
don’t know whether the upcoming market environment will be conducive or adverse to the use of
oscillators. As a subjective observation, on balance, oscillators have probably harmed traders more
than helped them.
however, if a trader fully understands their limitations, these tools could still
provide reasonable trading signals. For example, if a trader has good reason to expect that a trading
range market is more likely to prevail—and uses rigorous risk management to control losses if this
projection proves wrong—then an oscillator could be used as a trading tool.
 ■ Indicator Myths
Through repetition over decades, certain bits of “common wisdom” regarding technical indicators
have become entrenched in trading literature, despite the ability of traders to disprove such mislead-
ing ideas through testing. The following list is far from exhaustive, but it touches upon some of the
most dangerously misleading, and easily refutable, examples of such myths.
the Confirmation Myth
Traders are often exhorted to consult multiple technical indicators to “confirm” a potential trade
signal. This advice may sound sensible, but given the high correlation among so many indicators, such
confirmation is often an illusion. Unless the indicators being consulted are uncorrelated—say, if they
use radically different look-back periods (which is usually not the case)—they are probably simply
repeating the same information, with any apparent variations between the indicators likely meaning-
less. The similarities between the indicators shown in Figures 11.1 through 11.7 illustrate how easy it
is to generate false “confirmation” from calculations that are, more or less, the same indicator.
the “Magic Number” Myth
This misconception revolves around the belief that a specific indicator parameter (typically, the look-
back period) provides universally optimal performance or otherwise possesses special properties.
Popular examples include the nearly ubiquitous use of a 14-day look-back period as the default setting
for short-term countertrend indicators and references in the financial media regarding the impor-
tance of the penetration of a 200-day moving average. The reality is that such parameter values will be
optimal only in isolated markets as a function of chance. The question of what values work best for a
specific portfolio over a specific time range can be answered only by computer testing. And even then,
the answer would apply only to past data and could not be presumed to be indicative of the optimal
values for the future. Chapter 19, which addresses the issue of optimization, provides a more in-depth
discussion of this point.
171
TEChnICAl InDICATORS
 the leading Indicator Myth
 Some technical tools are commonly referred to as “leading” indicators for their supposed ability to sig-
nal a market move before the price series itself gives any indication of a change in direction. Although
it might be fair to say that a price-based indicator could (to some eyes) highlight an aspect of price
action with predictive properties, the inescapable fact is that an indicator can never “lead” price action
because, by defi nition, it is based on historical prices. If a certain indicator reading or pattern proves
(through testing) to have predictive value, that information must be present in the price series itself.
 the Divergence Signal Myth
 This belief is a subset of the leading indicator myth. Divergence is most commonly used to describe
the phenomenon of an indicator (usually one designated as a “countertrend” tool) moving in opposition
to a price series, and thus supposedly giving advance warning of vulnerability in the prevailing price
trend. For example, prices might make a new high in an uptrend, while the countertrend indicator
makes a lower high, suggesting the new price peak has been established on weaker momentum, which
in turn implies that a correction or reversal is imminent. Such patterns are, in fact, quite common at
market turning points. Unfortunately, though, they are also quite common at other times as well, often
generating one false reversal signal after another during extended market trends. Figure 11.12 , which
depicts crude oil prices during the market’s extended sell-off in 2014 and into early 2015, highlights
 FIGURE  11.12 Price-Indicator Divergences
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.

172A COMPlETE GUIDE TO ThE FUTURES MARKET
a series of successive price lows that were accompanied by higher lows in the MA 5 – MA 20 and Close
– Close 20 indicators. These divergences between price and the indicators began signaling the potential
for a signifi cant correction or reversal as soon as the trend began—approximately six months and
$50/bl. before the market staged a modest bounce in late January 2015. The situation is even worse
than it looks because Figure 11.12 omits some smaller false divergences that were left unmarked to
avoid cluttering the chart.
 ■ Indicator “Types”
 Indicators are typically categorized according to whether they are intended to identify longer-term
trends or emphasize shorter-term price swings and countertrend moves. While it is true that smoothing
functions, such as moving averages, lend themselves to trend analysis because they simplify price action,
such classifi cations usually have more to do with an indicator’s look-back period than any inherent
characteristic of the calculation. For example, although moving average crossovers are “classic” trend-
following signals,


ice swings and countertrend moves. While it is true that smoothing
functions, such as moving averages, lend themselves to trend analysis because they simplify price action,
such classifi cations usually have more to do with an indicator’s look-back period than any inherent
characteristic of the calculation. For example, although moving average crossovers are “classic” trend-
following signals, an MA
3 – MA 10 calculation (three-day moving average minus 10-day moving aver-
age), which conforms to the standard moving-average crossover form, could hardly be described as
a long-term trend-following indicator (see Figure 11.13 ). By contrast, the basic C – C momentum
calculation, most often used to highlight short-term price swings, will nonetheless refl ect longer-term
trends as its look-back period increases, as evidenced by the C – C
100 calculation shown in Figure 11.13 .
 FIGURE  11.13 length vs. Indicator Type
Chart created using TradeStation. ©TradeStation T echnologies, Inc. All rights reserved.
173
TEChnICAl InDICATORS
 ■ Conclusion
Because they are derivatives of price, it can be argued that technical indicators—when used to gener-
ate trading signals—actually distance traders and analysts from the data they are attempting to under-
stand. Although indicators can, perhaps, highlight certain aspects of market action that might not be
immediately evident by looking at a chart or a spreadsheet, they cannot create information that is not
already present in the market data itself.
Simplicity is generally a virtue with regard to technical indicators. There are only so many ways to
measure the direction and magnitude of price changes, and the slight differences between approaches
are unlikely to produce meaningful differences in trading signals. The more inputs an indicator has (and
the more arcane those inputs are), the more likely that either it is obscuring, rather than clarifying, the
market action it is intended to interpret, or it is merely a more complex version of a simpler calculation.
Perhaps the most important insight the reader can take away from this chapter is that indicators
that tend to work well in nontrending conditions will unavoidably perform miserably in trending
conditions, whereas tools designed for trends will fare poorly in trendless markets. Unfortunately,
markets do not ring bells when they are switching from one phase to the other. As a result, no single
indicator or parameter input (such as the look-back period) can be expected to perform consistently
well across multiple markets and time frames.

APPlyiNg ChArt
ANAlysis to trAdiNg
Part III

177
Cha P ter 12
Nobody can catch all the fluctuations.
—Edwin lefèvre
F
or many reasons, you may find yourself considering whether to enter a new position after the
market has already made a substantial price move. Examples include: (1) you were not previously
following the market; (2) in an effort to get a better price, you futilely waited for a price correction
that never developed; (3) you were previously skeptical about the sustainability of the trend, but have
now changed your opinion.
Faced with such a situation, many traders will be extremely reluctant to trade the market.
this
attitude can be easily explained in psychological terms. the act of entering a new position after a
trend is already well underway in a sense represents an admission of failure. Even if the trade is prof-
itable, traders know their gains would have been much greater if they had acted earlier.
thus, even
when you have a strong sense of probable market direction, you might be tempted to think: “ i've
missed so much of the move, why bother?”
As an example, consider chart-oriented traders examining the coffee market in mid-February
2014 (see Figure 12.1) after not having participated in the sharp price advance prior to that time.
such traders would have noted the market had broken out above the resistance level defined by the
January 2014 and october 2013 highs, with prices remaining in new high ground for two weeks—a
very bullish chart configuration. in addition, prices had just formed a flag pattern after an upmove—
price action indicative of another imminent upswing. however, observing that prices had already
advanced more than 37 percent since the November 2013 low (and more than 25 percent in just
seven days in late January and early February), traders might have been reluctant to enter a new long
position belatedly, reasoning the market was overextended.
Midtrend Entry
and Pyramiding
178A CoMPlEtE gUidE to thE FUtUrEs MArKEt
 Figure 12.2 vividly illustrates the folly of this conclusion. incredibly, as of mid-February 2014,
coff ee prices had completed only about 35 percent of their ultimate advance to the March high. the
moral of this tale is provided by an observation in Reminiscences of a Stock Operator by Edwin lefèvre:
“[Prices] are never too high to begin buying or too low to begin selling.”
 the key question is how one enters the market in the midst of a major trend. Actually, the goals in
implementing a midtrend position are the same as those for initiating any position: favorable timing
 FIGURE /uni00A012.1 Missed Price Move? (May 2014 Coff ee)
Chart created using tradestation. ©tradestation t echnologies, inc. All rights reserved.
 FIGURE /uni00A012.2 how it turned out (May 2014 Coff ee)
Chart created using tradestation. ©tradestation t echnologies, inc. All rights reserved.

179
MidtrENd ENtry ANd PyrAMidiNg
of entry and risk control. the following are four key strategies that could be employed to achieve
these objectives:
 1. Percent retracement. this approach attempts to capitalize on the natural tendency of a
market to partially retrace prior price swings. generally speaking, one might initiate the
position anytime the market retraces a given percentage of the price swing from the last
relative low or relative high. A reasonable choice for this percentage would be a fi gure i