Post on 04-Jun-2018
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
6.14. Oscillators and Indicators.
What is Momentum?
The word momentum has two meanings to market technicians, one of them is a generic concept about how
prices move, and the second one is a specific indicator. So, we are using the expression momentum indicators
to refer to the first definition, and momentum indicator for the second one. We are referring to the first
concept in this section. As defined by Charles Kirkpatrick “momentum measures how quickly the prices are
rising, or how steeply the trendline is sloping”. In other word, momentum is just the rate at which prices are
changing, or the second derivative of price movement.
From a mathematical point of view, the first derivative of price movement is the slope, and we can measure
this with a straightforward trendline. The second derivative refers to how the slope is changing, and that is
what momentum measures. Therefore, from a mathematical point of view, momentum refers to the second
derivative, or the acceleration/deceleration of price action.
Chartism is basically focused on determining the slope of the trend (first derivative), while indicators and
oscillators have been designed to measure whether the trend slope is changing or not (second derivative). To
detect this change in trend slope, market technicians apply the concept of divergence, according to the
following rule: when momentum is confirming the price trend, a “convergence” or “confirmation” occurs;
when momentum is failing to confirm the price trend slope by giving a warning signal, a “divergence”
occurs.
Additionally to the convergence/divergence concept, momentum is also used to identify overbought/oversold
conditions. This concept is quite simple. If we introduce a regression line and consider it as the trend, prices
will always move up and down this line. When prices deviate considerably above and below this imaginary
regression line, they will come back. Therefore, price action will be constantly crossing the trend from above
and from below. When prices deviate considerably above the trend, we use the term “overbought”.
Overbought in this definition is the same as expensive. On the contrary, if prices deviate considerably below
the trend, we call this an “oversold” market, and oversold is the same as a cheap or a low-priced market.
Market technicians have designed a lot of counter-trend indicators or oscillators to identify whether a market
is oversold or overbought. The idea is buying an oversold market and selling an overbought market. These
anti-trend indicators (oscillators) have been devised to eliminate the trend and show only the oscillations of
price around the trend.
This idea is expressed in one of the major technical principles of Martin Pring “the use of momentum
indicators can warn of latent strength or weakness in the indicator or price being monitored, often well ahead
of the final turning point.”
However, market technicians should be careful when using these oscillators, because they must be used to
confirm the existing trend. We must always be able to determine the trend, and once the trend is properly
defined, we could apply oscillators as secondary evidence to confirm the trend. At least, this is how Charles
Kirkpatrick recommends using technical oscillators. This idea is also expressed by Martin Pring in one of his
major technical principles “it is of paramount importance to use momentum analysis in conjunction with
some kind of trend-reversal signal in the price series itself.”
How successful are Momentum Indicators?
Academic research is not very useful for market technicians because these studies are focused on determining
whether price movement is random or not. Besides, academic studies are almost exclusively focused on
moving averages, forgetting about the rest of the indicators.
An example of how practitioners and academics diverge is in the risk concept. The academic concept of risk
is based on the standard deviation (volatility), while traders, technical analysts, and money managers rely on
maximum drawdown (MaxDD) to measure the risk of their strategy. Another example is how volatility is
defined, academics employ standard deviation to measure volatility, while traders, technical analysts, and
money managers use also the bar range or some similar concepts as the true ranges (ATR) to measure
volatility.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
However, Charles Kirkpatrick states that academic research can be useful to market technicians in order to
determine the direction in which to look for means of profiting from technical analysis, “if a particular
indicator shows no advantage over the random hypothesis, it should be treated with considerably more
skepticism than one that does show some statistically relevant results.” In the next section we are describing
the most common price momentum oscillators.
6.14.1. Indicators vs. Oscillators.
Although the meaning is the same regardless of the author, there are some differences in the relationship
between oscillators and indicators. In this course we will use both words interchangeably.
Martin Pring.
He makes no difference, so the terms are used as synonymous.
John Murphy.
He considers that oscillators are anti-trend or counter-trend indicators which oscillate between 0 and 100
showing phases of overbought and oversold conditions, so the RSI or the Stochastics are oscillators, while a
moving average is an indicator.
Charles Kirkpatrick.
In his book, he also embraces the same consideration as John Murphy.
According to these definitions and my own experience, I think the best way to describe the difference between
indicators and oscillators is the following: Indicators are divided into trend-following indicators, counter-trend
indicators and volatility indicators, and oscillators are just the counter-trend indicators. Therefore, all oscillators
are indicators, but not all indicators are oscillators. Note that this is not the only way to classify indicators and
oscillators.
6.14.2. Momentum Principles (Martin Pring).
Momentum is a generic term that can be applied to many different indicators: ROC, RSI, MACD, etc. There are
two broad ways of looking at momentum, the first one uses price data for an individual time series; it is then
manipulated in a statistical form that is plotted as an oscillator. We call this “price momentum”. The second is
also plotted as an oscillator, but is based on statistical manipulation of a number of market components, such as
the percentage of NYSE stocks above a 30-week moving average. This measure is referred to as “breadth
momentum”. It is an accepted practice to use daily data for identifying short-term trends, weekly data for
intermediate trends, and monthly data for primary trends.
The following description of the principles and use of momentum indicators applies to all forms of oscillators.
These principles can roughly be divided into two broad categories. First, those that deal with overbought and
oversold conditions, divergences, and the like, these are called momentum characteristics. Second, the
identification of trend reversals in the momentum indicator itself, these are called momentum trend-reversal
techniques. In this case, we are making the assumption that when a trend in momentum is reversed, prices will
sooner or later follow. Momentum typically reverses along with price, often with a small lag, but just because
oscillators change direction doesn’t always mean that prices will too. Actual buy and sell signals can only come
from a reversal in trend of the actual price, not the momentum series.
Interpreting Momentum Characteristics.
Overbought and oversold levels.
Oscillator characteristics in primary bull and bear markets.
Overbought and oversold crossovers.
Mega-overbought and mega-oversold.
Divergences.
Complex divergences.
Failure swings.
Momentum Trend-reversal techniques.
Trendline violations.
Momentum price patterns.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
Equilibrium
Overbought
Oversold
A
B
Equilibrium crossovers.
Momentum and moving averages.
Smoothed momentum indicators.
Once we have listed the ways to interpret momentum and the techniques employed to determine momentum
reversion, we proceed to explain them in more detail.
Overbought and oversold levels.
Perhaps the most widely used method of momentum interpretation is the evaluation of overbought and
oversold levels. These areas are drawn on a chart at some distance above and below the equilibrium level.
The actual boundaries will depend on the volatility of the price being monitored and the time period over
which the momentum indicator has been constructed and, these boundaries can be determined only by
studying the history and characteristics of the security being monitored.
When a price reaches an overbought or oversold level, the probabilities favor but by no means guarantee a
reversal. An overbought reading is a time to be thinking about selling, and an oversold one warns that the
current technical position may warrant a purchase.
When a particularly sharp price movement takes place, these boundaries will become totally ineffective.
Unfortunately, this is a fact of life, but by and large it is usually possible to construct overbought and
oversold benchmarks that are price-sensitive. In figure 6-161, the oscillator is drawn under the price and the
dotted lines represent the overbought and oversold levels (e.g. 70 and 30 for RSI and 80 and 20 for
Stochastics). Points A and B are, respectively, overbought and oversold lectures of the oscillators.
Oscillator Characteristics in Primary Bull and Bear Markets.
In a bull market, oscillators tend to move into an overbought condition very quickly and stay there a long
time. In a bear market, they can do remain in an oversold condition for considerable periods. In a bull market,
the price is extremely sensitive to an oversold condition. That means that when you are lucky enough to see
one, look around for some confirming signals that the price is about to rally. An example might be the
violation of a down trendline and so on. Looking at it from another perspective, during a bull market the
price will be far less sensitive to an overbought condition. This idea is reflected in one the major technical
principles by Martin Pring “oscillators behave in different ways, depending on the direction of the primary
trend.”
In a bear market, on the other hand, a market or stock is far less sensitive to an oversold reading, often failing
to signal a rally or possibly being followed by a trading range. The maturity of the trend, whether primary or
intermediate, often has an effect on the limits that an oscillator might reach.
Overbought and oversold crossovers.
In most cases, excellent buy and sell alerts are generated when the momentum indicator exceeds its extended
overbought or oversold boundary and then crosses back through the boundary on its way to zero. This
approach filters out many premature “buy and sell” signals generated as the indicator just reaches its
overextended boundary, but one should still wait for a trend reversal in the price itself before taking action.
Figure 6-161 Source: Martin Pring.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
Equilibrium
Overbought
Oversold
Equilibrium
Overbought
Oversold
Mega-overboughts and mega-oversolds.
A mega-overbought is the initial thrust in a bull market following the final bear market low. It is a reading in
the momentum indicator well beyond the normal overbought and oversold condition witnessed in either the
previous bull or bear market and should represent a multiyear high. Martin Pring considers that a mega-
overbought is about the only instance when opening a long position from an overbought condition can be
justified. Even so, it can only be rationalized by someone with a longer-term time horizon. A highly
leveraged trader may not be able to withstand the financial pressure or the countertrend move, whereas the
long-term investor can.
Since mega-overbought condition is associated with the first rally in a bull market, it is good idea to check
and see if volume is also expanding. If it takes the form of record volume for that particular security, the
signal is far louder. The same concept also appears in reverse for oversold extremes.
Divergences.
A positive or bullish divergence occurs when price in a downtrend is marking lower lows, but the oscillator
diverges and marks higher lows. The implications of this pattern are bullish. A negative or bearish divergence
occurs when price in an uptrend is marking higher highs, but the oscillator diverges and marks lower highs.
The implications of this pattern are bearish. Martin Pring has three major technical principles about
divergences:
It is extremely important to note that divergences only warn of a weakening or strengthening technical
condition and do not represent actual buy and sell signals.
As a general rule, the greatest the number of negative divergences, the weaker the underlying structure
and vice versa.
A divergence that develops close to the equilibrium line is often followed by a sharp price move.
Overbought crossover
Oversold crossover
Mega-Overbought
Mega-Oversold
Figure 6-162
Figure 6-163
Source: Martin Pring.
Source: Martin Pring.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
Complex divergences.
It is widely recognized that price movements are simultaneously influenced by several cyclic phenomena.
Because a single momentum indicator can monitor only one of these cycles, it is always a good idea to
compare several different momentum indicators based on different time spans and look for divergences. For
example, not much could be gained from the comparison of 12-week and 13-week ROC, since they would
move very closely each other. On the other hand, comparing a 12-week and a 26-week span would clearly
reflect different cycles.
An example of this would be the following, when the longer-term indicator reaches a new peak and the
shorter one is at or close to the equilibrium line, they are clearly in disagreement or out of gear. This
normally, but not necessarily, indicates that a reversal in trend will take place, and it is usually a significant
one.
Failure swings.
A failure swing is a specific type of breakout from an overbought or oversold zone first describe by Welles
Wilder in 1978. A stronger version of the breakout, it often is the first sign of a potential reversal after a
lengthy trend in which an oscillator has remained within or close to a zone. A negative failure swing occurs
when the oscillator breaks down out of an overbought zone, creates a reversal point, pulls back but fails to
reenter the zone, and then breaks back down below the earlier reversal point. A positive failure swing is the
opposite at an oversold zone.
Bearish or Negative Divergence
Bullish or Positive Divergence
Figure 6-164 Source: Martin Pring.
Overbought level
Oversold level
Figure 6-165 Source: Charles Kirkpatrick.
Negative Failure Swing
Positive Failure Swing
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
Trendline violations.
Occasionally, it is possible to construct a trendline on the momentum indicator by connecting a series of
peaks or troughs, and the rules are the same as trendlines over prices. This type of momentum weakness must
be regarded as an alert, and action should be taken only when confirmed by a break in the price trend itself.
Note that when trendlines for the oscillator and price are violated simultaneously, the signal is usually
stronger.
Momentum price patterns.
Just as the trendline over indicators can add value, momentum indicators are also capable of tracing out price
patterns. Compare the patterns of price and Momentum and when there is a coincidence the probability is in
your favor.
Equilibrium crossovers.
Some technicians have devised indicators that offer buy and sell signals when the momentum indicator
crosses above and below its equilibrium or zero line. Martin Pring considers that this crossover can be
improved with the use of a moving average. For example, a 12-month ROC crossovers, used in conjunction
with a 12-month moving average crossovers, have consistently given reliable buy signals.
Momentum and moving averages.
By now, it is apparent that all the trend-determining techniques used for price are also applicable to
momentum. One of these methods is plotting a moving average over the indicator and follows the crossovers
between the indicator and its moving average. One of the problems associated with this approach is that the
momentum indicator is often much more jagged than the price that is trying to measure, causing an
unacceptable number of whipsaw signals. It is possible to filter out some of these whipsaws by using a
combination of two moving averages.
Smoothed Momentum Indicators.
Another way of incorporating moving averages into momentum studies is to smooth the momentum indicator
by a long-term moving average. If the momentum curve is found to be unduly volatile, it is always possible
to smooth out fluctuations by calculating an even longer-term moving average or by smoothing the moving
average itself with an additional calculation.
6.14.3. Moving Average Convergence Divergence (MACD).
MACD was developed by Gerald Appel and it is based on the concept of a moving average crossover. MACD
employs three exponential moving averages, so it has three parameters (the number of bars of each of these
moving averages). It also has three lines: MACD line, signal line, and zero line. The MACD line is just the
difference between two exponential moving averages. The default parameters are 12 and 26, so each point of the
MACD line comes from the following mathematical expression: EMA(12) – EMA(26). When the MACD line is
above zero, it signals that the faster moving average (shorter parameter) is above the slower moving average
(larger parameter), and when the MACD line is below zero, it signals that the slower moving average is above
the faster one. The name of this indicator comes from the fact that the two EMAs are continually converging and
diverging.
The signal line is an exponential moving average (EMA) of the MACD line, with a default parameter of 9.
Sometimes a difference between the signal and the MACD line is illustrated throughout a histogram. Finally, the
zero line needs no explanation because it is a line at zero level. Although the default parameters are 12, 26, and
9, Gerald Appel also recommends the following set of parameters: 8, 17, and 9.
MACD line.
It is the difference between two EMAs. The default parameters are 12 and 26.
Signal line.
It is an EMA of the MACD line. The default parameter is 9.
Zero line.
A positive MACD (above zero line) means the faster moving average is above the slower moving average
and vice versa.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
According to Charles Kirkpatrick, the MACD indicator can be used to determine both trending and anti-trending
trading signals. It can also be used to determine divergences between the price action and the indicator, although
this application is not as common as the trending and anti-trending market signals:
Trending market signals:
Buy signals occur with upward crossovers of the MACD line above its signal line, being both above zero
line. Sell signals occurs with downward crossovers of the MACD line below its signal line, being both below
zero line.
Anti-Trending market signals:
Buy signals occur with upward crossovers of the MACD line above its signal line, being both below zero
line. Sell signals occurs with downward crossovers of the MACD line below its signal line, being both above
zero line.
Although both types of entries are considered by technical analysis practitioners, Charles Kirkpatrick
recommends the trend-following method. In figure 6-166 we can see a daily bar chart of Apple Computers. The
MACD line is represented by the continuous line, while the Signal line is represented by the dashed line. The
first circle from the left shows an anti-trend buy signal, and the second circle shows a trend-following buy signal.
6.14.4. Rate of Change (ROC).
ROC is one of the simplest oscillators. It just measures the difference between the price of today (if daily bars
are considered) and the price of the bar of n days ago. If this difference is just computed through a subtraction,
the resulting indicator is called “Momentum”, while if the difference is computed as a percentage, the resulting
indicator is called “ROC”. The formula and the standard ways of use ROC are as follows (anyway, Kirkpatrick
considers that none of these four ways are very reliable).
1) The position of ROC relative to zero can indicate the underlying trend. In figure 6-167, the ROC indicator
is most of the time above the zero line because the price is in an uptrend.
2) It can be an overbought/oversold indicator, showing the points where ROC has reached an extreme and
prices are due for a correction.
3) It can generate a buy signal when it crosses over its zero line and a sell signal when it crosses below its zero
line. Bullish and bearish arrows show this kind of signals (figure 6-167).
4) It can be a divergence oscillator. In figure 6-167 a bearish divergence is shown (prices are doing new highs,
while ROC indicator is making lower highs at the same time).
Figure 6-166 Source: VisualChart.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
It suffers from the drop-off effect as simple moving averages, and because it employs only two prices form the
time series of the security, and both prices are equally weighted, some market technicians smooth the ROC
through a moving average. Martin Pring considers that a 12-month or 52-week time span is generally the most
reliable, although a 24-month or 18-month period can also prove useful.
6.14.5. Relative Strength Index (RSI).
This famous oscillator was developed by Welles Wilder in 1978. It was introduced in his book New Concepts of
Technical Trading Systems, with other great indicators as ATR, parabolic SAR, or ADX. It is an oscillator
(counter-trend indicator) with three parameters: the number of bars, which is 14 by default (Wilder justified this
number on the basis that it was half of the 28-day lunar cycle), the overbought level, which is 70 by default, and
the oversold level, which is 30 by default.
If we focus on a daily timeframe, the RSI measures the absolute (not the relative strength so its name is
misleading) strength of a security, comparing up days to down days. Up and down days are defined relative to
their previous day. When the close of today is higher than the close of yesterday, we have an up day, while a
down day is characterized by a close price lower than yesterday’s close. If we were using another timeframe,
instead of a daily one, we would have substituted the term “days” for “bars”.
The RSI is an oscillator so it is based on the overbought/oversold concept. Wilder considered that overbought or
expensive markets are those in which an excessive number of “up” days have taken place, while oversold or
bargain markets are those in which an excessive number of “down” days have occurred. This concept is
illustrated in the following mathematical equations:
In the following box we can see that both equations are equivalent:
Figure 6-167 Source: VisualChart.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
According to the mathematical equations, you can see that RSI oscillates between 0 (indicating no up days) and
100 (indicating no down days). Notice that in the “UPS” and “DOWNS” equation, the numerators refer to
points, Dollars, Euros, etc, and the denominator is just the number of bars (e.g., days). Once the first RSI is
calculated using the previous equations, the next RSI calculations are smoothed using a proprietary exponential
moving average called “Wilder Exponential Moving Average”. Welles Wilder uses this moving average in other
oscillators (e.g., ATR)
Wilder exponential moving average.
After calculating the RSI for the first 14 days, for day 15 and after:
The RSI has many characteristics that can generate signals. Let us introduce some of them:
Crossing the 50 line.
When the RSI crosses above the midpoint level (50 line) of the bounded range, we should buy the security,
while if the RSI crosses below the 50 line, we should sell it.
Crossing the Overbought and oversold levels.
This strategy considers buying when the RSI crosses above the overbought (30) level and selling when the
RSI crosses below the oversold (70) level, respectively. Other authors as Chuck LeBeau employ parameters
75 and 25 as overbought and oversold levels. Notice that when deciding the parameters for the oversold and
overbought lines, market technicians should know that the larger the parameter of the RSI (14 by default), the
shallower the swings, so the larger the parameter the narrower the RSI overbought and oversold lines should
be constructed and vice versa. This is a characteristic that differentiates RSI from other indicators.
This strategy represents the most common use of the RSI indicator and it is illustrated in figure 6-168, where
an RSI with parameters 14, 70, and 30 is represented below a daily bar chart of U.S. Company Starbucks. In
this chart, there are only two moments in which the RSI crosses its oversold and overbought lines, and both
are represented by ovals and both are great trading opportunities.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
RSI is wrong.
This interpretation is just the opposite of the previous one. The trader should buy when the RSI crosses above
the overbought level and sell when the RSI crosses below the oversold level. This a trend-following strategy.
RSI divergences.
Similar to other oscillators, a divergence between price and the oscillator can be used to generate trading
signals.
RSI Chartism.
The RSI also appears to have patterns similar to price charts. Triangles, pennants, flags, and even head and
shoulders patterns occur. The rules for breakouts from these formations are used for signals from the RSI.
Recall than one the major technical principles by Martin Pring states that “when the trendlines for the
oscillator and price are violated simultaneously, the signal is usually stronger.” Because the RSI show less
volatility as the number of bars used as parameter increase, a higher parameter will help to construct patterns
as trendlines or horizontal lines.
RSI failure swings.
A failure swing occurs when the oscillator exceeds a previous extreme, top or bottom, corrects, and then
heads for the old top or bottom but fails to exceed it. If prices did exceed their previous extreme after this
failure in the RSI, we would have a divergence, but a swing failure does not require a divergence. If the
second run fails to exceed the peak (or valley) of the first run and then breaks through the retracement high
(or low), it gives a swing failure signal. Although swing failure signals can occur in other oscillators, they
seem to be more common in the RSI.
The RSI is an indicator that cannot be interpreted mechanically (it shows poor results in backtesting), and
Charles Kirkpatrick considers this is due all the possible trading signals we have already discussed. It is probably
Figure 6-168 Source: StockCharts.com.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
the most famous indicator. As a final advice, if you are interested in including the RSI into your technical tools,
learn all the previous trading strategies, and always keep an eye on the underlying trend. The following two
indicators are variations of the RSI: the CMO (Chande Momentum Oscillator) and the RMI (Relative
Momentum Indicator).
6.14.6. Chande Momentum Indicator (CMO).
The first variation of the RSI is called Chande Momentum Indicator (CMO) and it was developed by Tushar
Chande. When comparing RSI to CMO, there are some characteristics that we should remark:
The RSI is bounded from 0 to 100, while the CMO is bounded from -100 to +100. Therefore, the midpoint
level in the CMO indicator is zero, instead of 50 as it was in the RSI oscillator.
CMO is based on equations which do not smooth the data, so CMO reaches overbought or oversold levels
more often than the RSI.
Both CMO and RSI uses up and down bars (e.g., days) in their equations.
Both CMO and RSI show less volatility as the number of bars used as parameter increase.
One approach that Martin Pring found helpful is to plot a 20-day CMO and smooth it with a 10-day moving
average. Then the crossovers of both indicators are used to generate buy and sell signals. However, since there
are numerous crossovers, it is important to make an attempt at filtering out those that are not likely to work out
by only using those that develop at an extreme level in view of the fact that they tend to be more accurate.
6.14.7. Relative Momentum Index (RMI).
The second variation of the RSI is called Relative Momentum Indicator (RMI) and it was developed by Roger
Altman in 1993. When comparing RMI to RSI, there are some characteristics that we should remark:
RMI adds one more parameter to the number of bars, the oversold level, and the overbought level. This
new parameter is a momentum factor. When the momentum factor equals one, the RMI is equal to the RSI,
but when the momentum factor is higher than one, both indicators diverge.
RMI introduces and additional smoothing and it also accentuates the degree of the fluctuation, so it is less
jagged than RSI, and it also reach the overbought and oversold levels more often.
Both RMI and RSI show less volatility as the number of bars used as parameter increase.
6.14.8. Trend Deviation (Price Oscillator).
A trend-deviation indicator or a price oscillator is based on the ratio or the subtraction between a security’s price
and a trend-following indicator. From the two methods (division versus subtraction), division is usually preferred
because it shows better the relative moves. The subtraction reflects the absolute, not the relative moves.
Additionally, we can use any trend-following indicator in the denominator (e.g., moving averages or regression
lines), although Charles Kirkpatrick shows his preference for moving averages. If we use a moving average, the
trend-deviation indicator will reflect the relationship between the price action of the individual security and the
trend. In other words, it will show how fast the price is advancing or declining in relation to the trend expressed
by the moving average. A trend-deviation indicator or price oscillator can be considered as horizontal envelopes.
6.14.9. Stochastic Oscillator.
The Stochastic is a counter-trend indicator (oscillator) with the same three parameters as the RSI: the number of
bars, the overbought level, and the oversold level, plus an additional one from a simple moving average. The
default parameters are 14 for the number of bars, 80 for the overbought level, 20 for the oversold level, and 3 for
the simple moving average. Therefore, it has some similarities with the RSI, although it shows a more jagged
behavior. The Stochastic oscillator is based on determining where the recent closing price is within the range
(high minus low) of the previous n bars. We will see the exact calculation in the equations below. The idea
behind this oscillator is that prices tend to close near the upper side of a trading range during an uptrend, and to
close near the lower side of a trading range during a downtrend.
The name of this oscillator is as misleading as the name of RSI. Remember that RSI stands for Relative Strength
Index, but it measures absolute, not relative strength. The name of this oscillator has nothing to do with the
scientific term “stochastic”, which means random or nondeterministic.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
%K
One interesting thing about Stochastic is that we still do not know who really invented it. The following
paragraph comes from Charles Kirkpatrick and July Dahlquist’s book and it is a great example of the lack of
rigor in some areas of technical analysis:
“George Lane is known for promoting the concept since 1954, but others apparently preceded him (Ralph
Dystant and Richard Redmont). According to Gibbons Burke, Tim Slater, founder and president of
CompuTrac Inc., included this indicator in the company’s software analysis program in 1978. He needed a
name to attach to the indicator other than the %K and %D we will see in the indicator calculation. Slater saw
a notation of stochastic process hand written on the original Investment Educators literature he was using.
The name stuck.”
Regardless of its misleading name or who its inventor was, the Stochastic is one of the most popular oscillators,
probably the second one after the RSI.
As expressed in the previous equations, %K can be considered as the raw stochastic number. If we proceed to
smooth this raw stochastic number with a simple moving average, the resulting indicator is called “Fast
Stochastic”. Fast %D shows an extremely sensitive and jagged behavior, so a new smoothing can be performed.
If we apply another simple moving average over the fast stochastic, the resulting indicator is called “Slow
Stochastic”. Evidently, Slow %D is a smooth version of the Fast %D, because it represents a double smoothing
over the raw stochastic number (%K). A good way to remember whether which one is the faster of the two is by
the following a mnemotechnic rule: K=Kwick and D=Dawdle.
The conventional parameter for the number of bars to determine the trading range is 14. However, other authors
as Larry Williams use a composite of different parameters and the True Range (Welles Wilder) instead of the
traditional range (High – Low) in his “Ultimate Oscillator”.
As in the RSI, the Stochastic Oscillator is useful in nontrending markets, and signals are generated when the
oscillator reaches the overbought or oversold levels, or when the fast stochastic crosses over the low stochastic.
Chart patterns can also be drawn on this oscillator, and according to Charles Kirkpatrick, academic testing of
standard stochastic signals has had the same mediocre results as with other oscillators. Martin Pring includes in
his book the following interpretation rules:
Crossovers.
Normally, the faster %K line changes direction sooner than the %D line. This means that the crossover will
occur before the %D line has reversed direction as in the left crossing. When the %D line reverses direction
first, a slow, stable change of direction as indicated in the right crossing, and the %D is regarded as a more
reliable signal.
Left crossing
%D
%K
Right crossing
%D
Figure 6-169 Figure 6-170 Source: Martin Pring. Source: Martin Pring.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
Falling bottoms in the indicator
Rising bottoms in price
Divergence Failure.
An important indication of a possible change in trend arises when the %K line crosses the %D line, moves
back to test its extreme levels, and fails to cross the %D line.
Reverse Divergence.
Occasionally, during an uptrend, the %D line will make a lower low, which is associated with a higher low in
price. This is bearish omen and referred as bear setup. A bull setup occurs at the end of a downtrend.
Extremes.
Occasionally, the %K value reaches the extreme of 100 or 0. This indicates that a very powerful move is
underway, since the price is consistently closing near its high or low.
Hinges.
When either the %K line or the %D line experiences a slowdown in velocity, indicated by a flattering line,
the indication is usually that a reverse will take place in the next period.
Divergence failure
%D
%K
Hinge
Hinge
Figure 6-171
Figure 6-172
Figure 6-173
Source: Martin Pring.
Source: Martin Pring.
Source: Martin Pring.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
%K
A
B
C
D
A
B
C
D
%D
Divergences.
The stochastic indicator often sets up positive and negative divergences in a similar manner to other
oscillators. Buy and sell alerts are triggered when the %K line crosses the %D after a divergence has taken
place.
Figure 6-174 Source: Martin Pring.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
6.14.10. Williams %R.
Williams %R is an inverted Stochastic. If we look at the equation, instead of subtracting the low from the close,
we subtract the close from the high. So, when a %R is between 80 and 100, it indicates an oversold market,
while a %R value between 20 and 0 indicates an overbought market. Recall that the Stochastics results are just
the exact opposite. This is illustrated in figure 6-175, where a daily bar chart of the U.S. Company Starbucks is
accompanied by a Stochastic and a Williams %R using the same parameters for both oscillators. As expressed by
Charles Kirkpatrick “Williams %R oscillator tells whether a stock is at a relatively high point in its trading
range, while the stochastic indicates whether a stock is at a relatively low point in its trading range.”
Figure 6-175 Source: StockCharts.com.
CMT I. 2015 Topic 6. Chart Pattern and Analysis.
6.14.11. Commodity Channel Index (CCI).
CCI was developed by Donald Lambert in 1980, and its name can be a little confusing because it can be applied
to any security, not just commodities. The calculation of the CCI is based on measuring the deviations of a
security’s price from a moving average.
CCI is very similar to Stochastic, although it is not bounded by +100 and 0. This lack of upper and lower bounds
confuse some market technicians. In order to introduce bounds into the CCI, some technicians apply a Stochastic
calculation on the CCI and this produce an indicator that is less jagged, and that has an upper (100) and a lower
bound (0).
In figure 6-176 we can compare the CCI with the Stochastics on a daily bar chart of U.S. Company Amazon. The
upper window shows the price action, the middle window shows the CCI and the lower window shows the
Stochastics. It is clear that peaks and troughs are very similar in both indicators. However, CCI is not bounded,
while Stochastics is.
Figure 6-176 Source: StockCharts.com.