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Learning
to trade is a largely an effort to solve specific trading problems. Here
are nine classic problems and the types of trading solutions you'll learn
to execute.
Introduction:
Having a comprehensive
view of how markets work has a profound impact on both our confidence
and our ability to extend and evolve the trading process. In creating
the Trend Dynamics courses, we've set out a comprehensive trading
method that works well under widely varying market conditions— and in
different markets—over long periods of time. In the course of doing
so we've identified many of the classic problems of technical analysis—the
most pressing problems that all traders encounter.
In the text that
follows we summarize and review nine classic trading problems and the
solutions found in various Trend Dynamics Course modules:
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Problem:1
Reducing Noise
In Market
Structure 101, we described price
action as "a reflection of energy that is in a continual transition
from a state of instability (trend) to a state of instability
(congestion or trading range) and back again." Isolating these
transitions amidst all the cacophony of the markets, the noise and
news and rumors, and doing so with sufficient clarity and enough vision
to stay one step ahead of the crowd, is an intellectual and a psychological
problem and a considerable challenge. It is, of course, at the heart
of successful trading.
What makes that
challenge formidable is that these transitions do not take place in
a single, discrete dimension of time nor with any consistent periodicity.
Instead they are distributed across a shifting, nearly infinite variety
of timeframes. In any given market at
any point in time, trend changes, running line movements, congestions,
and trading ranges can be occurring over
a variety of timeframes simultaneously. Sometimes these timeframes
are fractal, making our task a bit easier; but at other times, as
when control of price is wrested from one timeframe
to another in what appears to be random fashion, they are disjointed
and disconnected. Every trader, every trading system, is confronted
with this problem. Many a trader has been bankrupted by it.
Only an omnipresent
mind, surely no merely human one, could encompass even for one still
moment the complexity of price action as it moves simultaneously across
all timeframes, and find within it a
replete pattern of accord and harmony. Lacking such omnipresence,
we see order in one layer, or at best two or three, within a galaxy
of chaos. We simply cannot know precisely what speculative
power and force are grasped
in the hands of a market's innumerable participants at any given point
in time.
Owing to this
instability, swings in supply and demand will at times be wholly inexplicable.
Is there any wonder that the markets remain an unfathomable mystery
to so many, including long-time observers?
Noise is price
action that falls outside the range of one's threshold of perception.
It is relative to the timeframe we're attuned to. But what is mere
static on one dimension of time and price, may well have meaning on
another. The Catch-22 is that the more timeframes we can simultaneously
(and skillfully) interpret, the more order we will perceive; but the
more timeframes we monitor, the more prone we become to bouts of confusion
and indecision—and the more difficult and complex good execution becomes.
The problem is
that in order to see, to make
valid and useful observations of price action we need to find ways
to reduce the noise so that we can detect underlying directional biases
in the timeframes we're monitoring.
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Solution
to the Noise Problem: Time Filters
Solutions to the
noise problem lie in analysis or synthesis—or in a combination of
the two. In analysis, we break something complex down into simple
elements. The solution taught in Trend Dynamics is
primarily an analytical one. As first explained in
Market Structure 101, we use 5-day (5D) and 18-day(18D) time filters
to segregate price action into two encompassable components, and in
doing so filter out the noise of other timeframes.
Richard
Donchian's (and later Richard Dennis's) line breakout methods and
Peter Steidlmayer's Market Logic approach reach for similar analytical
solutions to the problem of noise, of diffusion of price action over
many timeframes. In Trend Dynamic terms, all these analytical approaches
are essentially based on measuring line pressure, which is a direct
expression of the imbalance between supply and demand. The concept
of line pressure is defined and developed at length through several
Course modules.
Another
valid solution is to synthesize the noise of price action. This is
typically done by reducing the noise to a baseline, a moving average
of prices. In Developing A Trading
Plan 301 we teach a unique
method of using mean price levels and regressions to the mean in combination
with market structure.. The moving average has a number of successful
adherents, including such trading legends as Ed Seykota and Marty
Schwartz.'
Both
methods of noise reduction use time as a filtering mechanism because,
as the First Law states, "Time affects
the potency of any price swing."
Both
methods have long been used with great efficacy to extract profits
from the futures markets. In fact, virtually every effective trading
plan I know of uses one or the other of these methods to help solve,
or, at least to dampen, the noise problem to a level that makes analysis
practical.
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Problem
2: Determining A Directional Bias
"I try to determine
what the bias is for the market; then I go from there." says Marty
Schwartz. Most effective traders walk into their offices with a bias;
they've done their homework the night before. If not, they establish
one shortly after observing price action when the markets open. Directional
bias is nothing more than the trend controlling the direction of prices
over whatever timeframe one is sensitized to.
Understanding directional
bias simplifies a trader's decision-making. A bias allows us to choose
one script over another. If measured skillfully, the prevailing directional
bias can provide an edge in win-ratio and probability. How we deal with
a trading range, how we determine when a trading-range is terminating,
becomes problematic unless we have a directional bias. Simply stated,
the problem is this: How do we determine and deal with directional bias
in price action?
- Solution:
Identify the Influence of a Higher Order Trend
The analytical
approach we use in Trend Dynamics trading courses, essentially breaks
price action down into period and swing components to look at precisely
how price ranges expand and contract to form trends. There are twelve
underlying market principles, that govern all trend and price
action. They are derived from studies of market
structure (period and swing relationships) and designed to let
us predict the likely directional resolution of any given market's
price movement based on the recognition of the influence and limitations
imposed on lower-order price relationships by higher-order ones.
An alternate or
additional solution is the synthetic approach; which mainly examines
a time series as it moves in relationship to a synthesized price level
(the mean), and looks to the slope or relationship of moving averages
to determine likely directional resolution. In simple terms, trend,
whether determined by swings and price structure or by using sloping
moving averages tell us whether price is moving and may be expected
to continue moving, up or down.
Both solutions to the problem of determining directional bias have
made fortunes for many traders. Each
has proven itself valid over many decades of price action. In order
to make good, reliable use of trend, defined by period and swing relationships,
we need to solve two additional problems: 1.) How to normalize and
segregate swings that represent similar price-energy efforts; and
2.) How to differentiate between lasting trend changes, on the one
hand, and abortive ones on the other.
- Problem
3: Overlooked Swings, Missed Opportunity
A problem that plagues
technical analysis based on swing relationships (swing trading), as
typified by the weakness evident in Elliot Wave, Gann, Wyckoff methods,
is failure to explicitly define or normalize swings and to classify
swings according to whether they represent similar price-energy efforts
or at least reach minimum threshold levels of price-energy.
Solution:
Define Swings Dynamically
In Trend Dynamics,
we use the concepts of a dynamic range (floating line-change levels)
and a range penetration of a fixed percentage amount to allow us to
measure price efforts of like value and not overlook important price
swings. The omission of price swings handicaps our capacity to see the
real import of the price structure we are analysing. The First Law (see
Twelve Laws) suggests that time provides the
conditioning element with which we solve the problem of identifying
and measuring swings of like potency. I call this process "normalizing"
swings.
The time periods weuse are intervals of 5 and 18 days, which capture
and highlight the weekly and monthly swings. To measure price action,
I use price penetrations: that is, thrusts in price that penetrate a
range by 10% or more (see Market Structure
101) allowing for dynamic adjustment of the amount of penetration
relative to the height of the price range. The concepts of floating
line changes, maximum threshold, and measured line values allow us to
normalize swings consistently. analytical approach we use in Trend Dynamics
trading courses, essentially breaks price action down into period and
swing.
- Problem
4:
Trends That Don't Last
Differentiating
between valid trend changes and short, meaningless range expansions
is a classic trading problem that must be solved by every trend-based
trader in all markets. In fact, to recognize this as a pivotal problem
is to begin to attain a realistic understanding of trend tenacity and
how markets work. Success starts here.
In Trading Strategies 101A , I
wrote that the trend we'd like to see unfold and the reality of trend
evolution are two different matters. Normal price action is interspersed
with many false trend changes; and many a trading range is terminated
by an upthrust or spring. This is simply the way that markets balance
supply and demand. In order to thrive in this normal market environment,
we need clear ways to differentiate lasting trend changes from false
ones.
Solution:
Using Whole Period and Line Continuation Counts
To confirm a trend
change can completely alter our bias. Thus, it is a serious matter.
As a rule, correct identification of a trend change requires close and
careful observation. I introduced the whole period count (the WPC) in
Market Structure 101, as a tool
with which to differentiate trend changes from up-thrusts and springs.
Later, in Tactical Entries 202,
I characterized the WPC as an indication of defensive demand when price
holds above a point of change (POC) in a potential upwards movement.
Its counterpart on the offensive side is the pressing through the point
of change of the line continuation count. (LCC)
The chief solution provided in the Trend Dynamics course material to
the problem of identifying important trend changes is to use the whole
period count and line pressure as measured by the LCC to mark valid
major changes in supply and demand. Upthrusts and springs are then easily
identified as price offensives that fail to present the requisite WPC
or LCC pressures sufficient to change the trend.
- Problem
5:
Go With the Move, or Wait for the Retracement?
Identifying one's
own directional bias, or the direction in which we want to trade, can
be strategically useful. But, tactically we need more information, for
the simple reason that as a market's probable direction becomes obvious
to enough other traders, the risk on entry rises to intolerable levels.
Thus, we need to identify spots where risk on a relative basis is more
or less attractive-spots where we can make safer entries even in the
face of large-scale, sweeping, and well-understood market movements.
The problem is exacerbated by the fact that it is often psychologically
hard to take these positions.
Furthermore, there are times when a price thrust occurs and momentum
carries a market up and away without a retracement. Whether to enter
a trend on a breakout or on a retracement can be a vexing problem for
traders who use either daily or intraday timeframes. The recurring question
is: How does one know whether to buy the breakout or wait for a retracement?
.
Solution:
See Structure, but Feel the Pace & Rhythm
As a general rule,
I find it is better to wait for retracements. The optimal price level
at which to take a position is generally in the midst of a clear trend
but after a contratrend reaction or liquidation has taken place.
But identifying a contratrend reaction can be tricky. In
Developing Trading Plans 301, I presented a two-component typology
of trend segments that contain both a contratrend reaction and an offensive
line effort. Generally, I prefer waiting for contratrend reactions within
a clear ongoing trend. Those retracement entries include simple or complex
reactions or with-trend termination of trading ranges.
The 5D RePo first introduced in Trading
Strategies101A, and the straight-line reaction (SLR; (see Trading
Strategies 102), give us ways to identify the most important lower-risk
opportunities that commonly develop within an ongoing trend. Taking
a position after a contratrend reaction puts the trader in the advantageous
position of being able to calculate a near-term risk/ reward up to a
non-trend liquidation point that has at least a 50% to 70% probability
of being hit.
But there are also times when a breakout entry can be the tool of choice.
One occurs in an emerging trend change when the a wide-range breakout
(WRB; see Market Structure 201)
comes at an 18D point-of-change after a period of extensive liquidation
marked by several previous18D swings comprising a well-identified, well-understood
trend in the opposite direction.
The same problem confronts the trader using intraday entries to position
himself or herself in classic Trend Dynamics situations. Generally I
wait for retracement of some type even when using intraday data, but
I also know that not switching to a breakout entry at the right time
can cause lost opportunities, and this is something I constantly work
on. Generally, I switch to a breakout entry after price oscillation
has become narrow, such as following a NR7 day (when the price range
shrinks to the narrowest range of the past seven days). Other changes
in pace I note are when I see two or more inside periods, or a single
inside and narrow range, in a wide-range period. (To learn more about
this topic see Unorthoodox Trading
Tactics 301 and Formless Trading
505).
- Problem
6:
A Lack of Trending Markets
Underestimating
the probability or distribution of zero-trending environments is another
recurring problem with most trading methods. In fact, most trading methods
are far too dependent on catching high-plurality trends year after year.
For traders who depend upon such methods, the conse-quence is often
steeper-than-expected drawdowns. energy.
Solution:
Non-trend Liquidaiton Tactics
The Nontrend liquidation
(NTL), introduced in Trading Strategies
101B, has been a mainstay of Trend Dynamics because it functions
well in trending and non-trending environments both. It protects a trader
from being dependent on the continuity of trends. We teach Trend Dynamics
traders how to make profits in non-trending environments and not to
depend solely on catching the rare parabolic move.
- Problem
7:
Capturing Fleeting Windfall Profits
Whether one is a
day trader or a swing trader, on occasion a market will become seized
by emotion, and price will in consequence rally, or drop, precipitously
over the course of a few minutes or a few weeks. The result can be windfall
profits.
Capturing these profits is difficult; they often evaporate as quickly
as they appear because price has so outrun its time counterpart that
a wide price trading range forms. This in turn allows a latitude of
swing freedom that permits volatile trading range-like fluctuations.
Similarly, every year a trend-based position in some market will enter
a running trend and trade in a very orderly manner only to be topped
off in a parabolic move that yields profits of 10- or 20-to-l. Since
these "outlying" profits are relatively rare and unstable, they can
be especially hard to capture.
Solution:
Calculating Kill Zones and Realized Objectives
The best solution
to the problem of capturing windfall profits is to look for unexpected,
out-of-character expansions of intraday ranges (if you are a day trader)
or average weekly or monthly ranges (if you are a swing trader); and
then apply the "kill-zone" rules of thumb taught in Trading
Strategies 101B. Using Realized Objectives (also see Trading
Strategies 101B) are another, but far more subjective way to be
alerted to windfall profits that tend to evaporate quickly.
The most objective solution is to watch for sudden range expansions,
not those that are clean breakouts of long term structures but rather
those that come out of nowhere in thin air, into areas of supply & demand.
Ironically, the odd solution to riding out the long-term huge winner
is to take a fraction of a position off at some NTL point. Doing so
places one in a admirable psychological position, namely being able
to ride out the high-plurality running markets with detachment. (A good
trader always needs detachment if he or she is consistently to deploy
the right tactics to take advantage of any market opportunity.)
- Problem
8:
Missing the Beginning of Big Moves
When we've identified
a high quality opportunity to take with-trend positions, we should trade
as many of them as possible so long as they make sense in terms of allowable
risk.
But if our entry patterns are too intricate, we risk missing out on
good trades: The market will not provide the precise pattern we are
looking for. In fact, markets fulfill more intricate entry patterns
than we ever realize. For example, we may be looking for a specific
sort of trend turn only to discover later, to our dismay, that a trend
turn of precisely that magnitude did occur- but it was only visible
on another timeframe.
Patterns presented in Tactical Entries
201 (such as Doji periods, 0-C switches, narrow periods, and the
like) often occur, but ephemerally. In looking for one particularly
pattern, perhaps in vain, we may overlook that precise pattern presenting
itself in another layer of time that lies just below, or perhaps above
our threshold of sensitivity.
Solution:
Generic, Non-intricate Entry Patterns
The solution is
to develop and use entries that are aren't so intricate--for example,
generic entries that virtually always occur when a market reverses.
The trick, of course, is to use simple, but not too simple, entries.
If an entry is too easily triggered, it will get us in too often, and
prematurely.
The line continuation concept (specifically LCC-Offsets and Reversals,
presented in Tactical Entries 202)
provides a generic entry technique that solves this problem. The 3D
10% close (recommended as an alternative entry technique in Tactical
Entries 202) provides another solution to this classic problem.
- Problem
9:
Lack of Diversification
In our review of
CTA (commodity trading advisor) statistics in Developing
Trading Plans 301, we presented a surprising conclusion--that non-diversified
CTAs did not seem to suffer from lack of diversification. Nevertheless,
interpreting CTA data can be problematic because of surviorship bias:
the possibility that the data itself is lacking because the experience
of failing CTA's is filtered out of the data as they go out of business.
Perhaps for a broader universe of traders (those at least equally likely
to fail as to succeed) confining one's trading to a single stock or
futures contract, or even to a single sector, forces one to reconsider
the diversification issue. The root of the problem often stems from
a change from trend continuity to discontinuity. (When trending markets
are in force, lack of diversification isn't usually a problem.)
Solution:
Typological Diversificaiton
As discussed in
Developing Trading Plans 301, the
solution to this problem is to diversify typologically within the sector
or contract. In Developing Trading
Plans 301, we explain why a trading plan that has somewhere between
6 and 14 typologically diversified types of trades yields the largest
reduction in standard deviation of return.
Of course, if our trading yields a high average percent win in a market
characterized by high trend continuity---the S&P or currency markets,
for example-we can get by with less diversification.
A good example of
a single-contract specialist in a market that goes through prolonged
periods of trend discontinuity can be found in Bonds. In an interview
published in Intermarket in March 1986, Tom Baldwin, perhaps the single
biggest individual floor trader in the Bond pit, said that though he
trades in a single market, he plies "about 10 different groups of trades."
The value of typological diversification for the non-diversified trader,
such as Baldwin, is that it allows him to prosper in a wide range of
market environments.
To
start solving your trading problems today simply enroll in a Trend Dynamics
course: See our complete
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