is  the  more  aggressive  and  isshown  in  Figure  7.8.  If  you  wait  for  price  to  return  to  thetrend high or low (now one side of the range), you’ll just havefewer ranges to handle. One way or the other, you must definethe  retracement   from  the  reaction  level  in  order  to  define  thereaction side of the range.
4.  Prices  recross  the  average.  A  range  is  declared.
Now we can trade into the range at these two levels with an exitat (1) the opposite side of the range (the hope), (2) after six days ofrange  breakout6   (the  worst  result),  or  (3)  when  trend  is  reestab-lished  (that  is,  ranging  is  finished).
6  This probably seems  arbitrary, and it is. We just need to  chit off  trades directedinto  the  range  when,  instead  of  moving  into  the  range,  price  breaks  out.  All  such
ESTABLISHING A RANGE.  Prices  crossing  the  trend-FIGURE  7.8defining average define range boundaries at points 2 and 4. Later, asprices decline at point 6, they accord with a declining long average for 12days, reestablishing a downtrend and forcing an exit from range mode.
As you can see from Figures  7.7-7.9,
 seemingly simple rules be-come  complex  faced  with  actual  market  action.  Faced  with  all  theweird sequences of prices the market can throw at you, there’s thetemptation  to  add  other  conditions  (minimum  range  size,  time  inrange,  minimum  changes  in  the  average,  volatility  above  or  belowcertain  values,  you  name  it).  However,  add  other  conditions  spar-ingly.  This  example  probably  has  too  many  cute  rules  already  and,even so, didn’t generate enough trades in 11 years to have statisti-cally reliable results.
RESULTS
Looking at the experience trading Crude with these rules generatesthe  graph  in  Figure  7.10.  As  usual,  the  distinction  between  the  ad-
trades  go  into  our  losers  column  and  generally  have  huge  MAEs.   They  are  alsogood  candidates  for  reversals.
164
Switching  Modes:  Trading  Ranges
Results  165
RANGING EXAMPLE.  Carefully  note  the  sequence  of
FIGURE  7.9decision  rules.  A  classic  range,  this  pricing  generates  a  win  across  therange, a loser going back into the range and a winner reversing out ofthe range. Traders’eyes  will see a broader range around  29.30-it justwasn’t  captured  by  our  rules.
verse  movement  of  winners  and  losers  is  present,  even  in  this,  thefourth mode of trading presented here. The  MAEs seem to be gen-erally  larger  than  those  seen  in  the  trending  mode,  too.  Finding  thestop is not as clear cut as some we’ve seen, and we need to make apractical choice between a stop at  .3  and one at  .6,  keeping in mindthat we’re likely to use the point we pick not only as a stop but as areversal  point.
First, let’s expand the scale between 0 and .6  to see if some moredetail helps. We should be cautious about this: there are not 30 ex-amples of winners or losers in ten years, so the reliability of this es-timate is low. Only if there is a perceptibly sharp cutoff will we findanything  meaningful.  Figure  7.11  shows  our  findings.
There  is  nothing  easy  here.  Past  .3   there  is  no  sharp  cutoff  and,moreover, there are relatively few instances in each bin, making anyjudgment  very  uncertain.  Faced  with  real-world  situations  like  this,we  should  take  a  look  at  the  profitability  curve  for  different  cutofflevels:  .3,   .4,   .5,   .6,   and  so  on.  Figure  7.12  shows  the  results  of  theimpact of stops.
Again, just as in the real world, we’re faced with difficult choices.Given  our  assumed  capital  constraint  of  .6,   there  are  apparently  anumber  of  places  we  could  put  the  stops  up  to  that  point.  Thesharp  distinction  between  .l and  .2   is  probably  artificial  as  is  the
1
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FIGURE  7.10RANGING  MAE.  Wins  and  losses  versus  MAE,  rangetrading, 1984-1994. Trading into ranges gives distinct distributions ofadverse  price  movement  forwinners  a~nd  losers  but  the  “tail”  of  thewinners’distribution  is  bigger  than  usual.
FIGURE  7.11versus MAE, range trading, 1984-1994.
DETAILED  MAE  BREAKDOWN.  Winners  and  losers
166
Switching  Modes:  Trading  Ranges
Results  167
t
FIGURE  7.12PROFlTABlLlTY   VS.  MAE  STOPS.  Range  trading,1984-1994.  Although  profitability  generally  declines  as  stops  arewidened,  the  information  is  vague  given  the  low  number  of  trades  (52)
sharp  change  between  .5  and  .6,   an  artifact  of  the  low  number  oftrades  (64).  Furthermore,  this  is  just  the  final  distribution  of  profitversus  stop  level.  Over  time,  that  distribution  changed  quite  a  bit,as  seen  in  Figures  7.13  and  7.14.
As a result, making an operating decision comes down to the an-alyst’s art, restricted by the capital constraints. Looking at the finalprofitability  (Figure  7.12)  after  11  years  of  experience  and  keepingin  mind  the  variability  just  discussed,  I’ve  eyeballed  a  steadilydownward  sloping  line  from  left  to  right,  ignoring  the  peaks  andvalleys.  Given  that  approximation,  I  don’t  see  a  clean  cutoff  fromthis  data.  Because  we’ve  used  .3   for  all  our  trading  examples  todate and though there’s no reason this set of rules couldn’t have an-other level,  .3  is a reasonable choice here as well. It’s also the levelthat  lets  us  double  our  contracts  within  our  capital  constraints.  It’sthe one I’ll use for this campaign.
PROFIT  OVER 
TIME.  Cumulative  profitability, 
FIGURE  7.1  3out  of  ranges,  1984-l  994.  I  plotted  profitability  for  various  MAE  stopsover  time.  Although  the  detail  is  impossible  to  read,  the  message  is  thatincreases  over  time  and  (2)  profitability (1)   profitability variable. Figure 7.12 shows the final points end-on.
is  extremely
reversing
Descriptive  Behavior
Analyzing markets from the point of entry of a specific set of trad-ing  rules  is  usually  only  done  for  profitability  purposes.  It  can  also
FIGURE  7.14 RANGE TRADING AT .3  STOP LEVEL. Profit or loss,1984-1994.  To  provide  more  detail  than  the  graphs  above,  this  chartshows  the  equity  line  when  the  MAE  stop  level  is  set  just  above  .3.Although  the  trend  is  upward,  notice  the  strong  variability.
168
Switching  Modes:  Trading  Ranges
Results  169
be  interesting  and  profitable  simply  to  learn  of  typical  market  be-havior.  That  there  might  exist  “typical”  market  behavior  is  contro-versial,  and  I  certainly  don’t  have  proof  that  anything  like  it  exists,just  observations,
Crude’s  trading  ranges  were  defined  by  the  rules  earlier  in  thechapter,  and  anyone  else  could  come  up  with  other  rules.  It  stillstruck  me  that  range  sizes  were  generally  consistent.  If  you  graphfrequency  versus  range  size,  you  don’t  come  up  with  a  randomsmear.  Instead  you  get  the  distribution  shown  in  Figure  7.15.  Inthis  graph,  the  outliers’   are  for  a  wild  series  of  trades  around  the1990-1991 New Year as the market reacted to having reached theastounding price of $40 a barrel for oil that had a marginal cost of$3%$5.  This  series  of  trades  met  the  definition  of  a  trading  range,and the results must be included in the analysis. Trading today, I’dbe  inclined  to  ignore  them  if  today’s  prices  were  ranging  200&400points  per  day.
TRADING  RANGES.  Range  width,  1984-l  994.  Crude
FIGURE  7.15trading  ranges  are  about  100  trading  points  wide,  unadjusted  forvolatility. This observation gives the trader some targets when he or sheis fading a reaction or calling the limits oi a range.
’ An ourlier is a data point noticeably far from  the bulk of the data, in this ca%range widths of 300 to 400  trading points~
The rest of the ranges were clustered between  .43  and 1.8, whichmay  seem  an  unmanageable  range.  That  depends  on  the  depth  ofyour pockets. At least it gives you some idea of where to start prob-ing  reactions  that  may  turn  into  ranges.  There  aren’t  enough  ofthese  situations  to  generate  good  observations,  let  alone  good  sta-tistics, so for now, fading a reaction repeatedly until you end up en-tering at the right level can’t be more rigorously defined.
Breakouts
Another characteristic of Crude ranges that caught my eye was thefrequency  with  which  they  broke  out  in  continuations  of  theirlong-term  (12-week)  trend  (see  Figure  7.16).  Using  these  tradingrules, the initial extreme was the low or high for the trend (point 2);the  reaction  defining  the  range  went  to  a  reaction  high  or  low(point 4); and you trade the range when prices recross the averageand  then  return  to  the  initial  extreme  low  or  high  (point  5)-atwhich  point  you  find  yourself  trading  against  the  long-term  trend.In 18 out of 26 cases, trading into the range at point 5 resulted inan  immediate  loss  that  reversed  into  a  trend  trade.  Eighteen  of  the
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Prices  f  2  ”  -
5-  -  -  -  -  -  -  -
P
ce
t
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I
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t
FIGURE  7.16
BREAKING  OUT  OF  RANGES.
170
Switching  Modes:  Trading  Ranges
Summarv
  171
12  trades  had  no  favorable  price  movement  at  all.  That  is,  theybroke  through  the  range  very  sharply,  making  implementation  ofstops difficult. This may be a point at which using an option wouldbe better than a stop, a topic explored in Chapter 10.
To  me,  this  behavior  is  an  evocation  of  the  concepts  of  “sup-port”  and  “resistance,”  as  well  as  the  idea  of  breaking  through  ei-ther  one.  Evidently,  in  Crude  oil,  these  levels  can  be  roughlydefined by ranging rules, and breaking through them can serve as aguide for trend direction, So dramatic is this effect that it forms thebasis for Chapter 8.
It  won’t  surprise  Crude  oil  traders,  I  suppose:  to  find  that  tradingranges didn’t last long (see Figure 7.17). Of the 26 trading ranges,only 10 lasted long enough for more than 1 trade and only 4 lastedlong enough for 4 trades. From entry to exit ranged from 18 to 73days, and most (12 of 26) were 20 to 30 days long, this after taking6  to  12  days  to  get  into  and  define  a  range.  I  know  of  no  reasontrading  ranges  should  be  of  any  specific  length  but  I  now  suspectthat any Crude ranges over 30 days are long of tooth.
,*  -
10 
.
SUMMARY
One  idea  that  doesn’t  work  out  in  Crude  as  well  as  hoped  is  thatthe small loss taken on breaking out would be offset by profits fromtrending  across  the  range.  Whereas  some  ranges  (1)  last  longenough  and  (2)  have  the  extremes  revisited  by  prices,  more  often,once the range is defined, prices tend toward the side of their even-tual  breakout,  On  a  chart,  you  get  a  triangle  toward  the  breakoutside rather than an even oscillation across the range.
Losses  from  trading  into  a  range  in  a  strongly  trending  marketlike Crude oil can be quite dramatic because your first trade may beagainst  the  trend.  This  emphasizes  the  importance  of  proper  losscontrol.  Nevertheless,  defining  ranges  roughly  and  trading  intothem did produce profits with limited risk of disaster.
Win size was limited by the automatic exit at the opposite side ofthe  trading  range  whereas  losing  trades  were  terminated  on  thesixth  day  after  entry  or  on  the  sixth  day  of  a  new  long-term  andshort-term  trend.  The  effect  was  to  heighten  losses  and  limitprofitability,  Indeed,  range  trading  is  probably  only  feasible  withMAE  stops.  Without  them,  wins  are  limited  and  losses  could  behuge.  Table  7.1  shows  the  198441994  profitability  for  New  YorkLight Crude.
TABLE  7.1
CAMPAIGN  TRADING  PROFITABILITY
NEW  YORK  LIGHT  CRUDE,  1984-1994
Mode
TrendTrendTrendTrendRange
Rule
stop  Level
Two moving averageday-tradesAdd-or- 
Add-on position tradesRWWsalTrade  into  range
.31.31.31.31.31
Profit/Loss(points)
3,6002,5006401,827550
8Reversing  Out  of  Ranges
By now, a campaign trader will have a full plate. Although the diff-erent  phases  of  the  campaign  tend  to  take  place  sequentially,  theconstant  alternation  from  trending  to  nontrending  with  its  overlap-ping  trades  keeps  you  busy  tracking  a  variety  of  positions  with  avariety  of  stops  and  margin  requirements.  We’re  still  not  finisheddeveloping  the  campaign,  though.
In  Chapter  7  the  idea  of  trading  into  trading  ranges  was  dis-cussed  with  the  result  that  (1)  we  could  practically  identify  rangesand  (2)  we  could  trade  into  them  with  specific  distributions  of  ad-verse  price  movement  for  both  winning  and  losing  trades.  Thoseresults let us stop out our range trades at  .31  or $310 of risk on asingle-contract  basis.
Recall now that when trend trading was discussed, the idea cameup  that  an  MAE  stop  level  might  be  a  good  reversal  point.  Theidea  was  that,  if  good  trades  don’t  hit  the  MAE  stop,  a  trade  thatdoes  hit  the  MAE  stop  must  be  a  ‘bad’  trade  that  could  be  con-verted to a ‘good’ trade if it were reversed. Of course, not all tradesthat hit the MAE stop are destined to be losers, but as it happened,reversing bad trend trades at the MAE stop level was profitable.
Now it’s time to see if the same thing applies to range trades. Af-ter  all,  ranges  are  just  another  form  of  trend-persistently,  consis-tently flat. Plus a trade that hits the MAE stop is most likely ‘bad.’
173
174
Reversing  Out  of  Ranges
Realitv   1 7 5
The  tough  part  here  is  that  Figure  7.10  shows  that,  when  rangetrading,  more  winning  trades  than  usual  have  large  adverse  excur-sions.  If  a  range  trade  is  bad,  there’s  a  possibility  that  reversing  atthat  point  would  make  a  good  trade,  especially  since  our  underly-ing  hypothesis  is  that  a  breakout  of  the  range  must  occur  with  aloss on the range trade before getting into trending. Thus a reversalof  the  ‘bad’  range  trade  would  get  us  right  with  a  new  trend  rightout  of  the  blocks.  Figure  8.1  is  a  reprise  of  a  previous  figure  ex-plaining  this  idea.
REALITY
Does this sort of thing ever really happen? Even if it does, how canan  abstract  number  like  .31   be  the  ‘magic’  turnaround  point?  Fig-ure 8.2 shows an exemplary reverse trade, and Figure 8.3 shows adisastrous reversal.
Surprisingly,  good  things  happen  fairly  often.  Seen  in  the  light  ofranges defined by moving averages, not only do ranges occur fairly
Time
FIGURE 8.1REVERSING  OUT  OF  RANGE  TRADING.  Plan  on  takinga  loss  when  breaking  out  of  your  range.  Ideally,  that  will  be  somewhatoffset  by  the  profit  going  from  point  five  to  point  six,
FIGURE  8.2 EXEMPLARY REVERSE TRADE. Crude breaks out of atrading range for a sharp 200-point  drop. Reversing out of a tradingrange  is  a  relatively  high-percentage  trade  in  Crude,  but  the  MAE  stopsare wider than in other types of trades.
often  in  Crude,  but  breaking  out  of  them  by  as  much  as  .31   tendsto presage trending and sharp profitability. Only  5 of the 38 revers-ing  trades  had  no  favorable  movement  at  all  after  being  put  on  .31outside  the  range.  Of  the  trades  that  reversed  out  of  a  range,  30(whether eventual winners or losers) lasted more than five days, asshown in Figure 8.4.
This  may  be  tradable  information:  it  gives  one  time  to  put  intrailing  exits  to  minimize  losses.  In  contrast  are  trading  rules  gener-ating trades that, if they go sour, do so quickly. As it happens, re-versing  Crude  trades  don’t  tend  to  go  to  pot  rapidly.  These  tradespersist, and 33 of 35 had at least some favorable excursion. Slightlyless  than  half  had  a  favorable  excursion  greater  than  the  rangefrom  which  they  originated,  so  there’s  some  momentum  comingout of a range (see Figure 8.5).
176
Reversing  Out  of  Ranges
Reality 177
FIGURE  8.3 A  DISASTROUS  REVERSAL.  Although this range met themechanical  criteria,  price  action  made  reversing  out  of  it-at  both  topand  bottom--an  expensive  disaster.
/:c::::“:;:,
FIGURE  8.4 DAYS IN TRADE.  Of course, winning reversals lastedlonger than losers, but note that even losers often lasted more than fivedays  before  succumbing.
FIGURE  8.5 FAVORABLE  EXCURSION.  Although it’s unlikely arelationship could be quantified, reversals out of ranges in Crude tend tobe about the size of the range from which they came, or somewhatlarger.
God  forbid  anyone  would  use  this  information  for  targeting  aprice level on the breakout from a range, but it is striking that uponbreakout you can expect favorable movement about the size of theprevious  range,  with  some  tendency  toward  exceeding  the  rangesize.  Although  this  could  not  be  put  into  rigid  trading  rules  withoutmany more examples to generate statistical confidence, it is enoughto  get  my  attention.  Perhaps  price  excursion,  seen  relative  to  itsown prior behavior, may be somewhat ordered. Consider how un-likely it should be that there exists any relationship between break-out  price  movement,  both  long  and  short,  and  a  range  arbitrarilydefined by prices moving about an arbitrary average over 11 yearsof widely varying market movements, yet Figures 8.5 and 8.6 sug-gests just that.’
That  Crude  trades  off  support  and  resistance  levels  and  aroundvalue points probably isn’t a surprise to oil traders, and here’s con-crete evidence of it.
’  Curiosities  like  this  are  benefits  of  studying  price  behavior  in  terms   of  excursionfrom  points  defined  by  trading  rules.
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‘laqumu Jay40  auras
180
Reversing  Out  of  Ranges
Results  181
As  usual  by  now,  the  first  thing  to  look  at  is  the  adverse  pricemovement  that  trades  reversing  out  of  a  trading  range  experience.Looking  at  the  familiar  pattern  in  Figure  8.9,  we  see  that  in  re-versing  out of a range, winning trades just don’t go very far againstyou. The graph doesn’t give much detail between .3  (the level we’veused  elsewhere  for  a  stop)  and  .6   (our  capital  constraint),  so  weneed to elaborate the information and ask what happens to profita-bility as stops  run from  .3  on up. Figure 8.10 shows what we find.Interpreting  this  chart,  I’m  struck  by  the  consistent  rise  and  fallof the values. Not that the news is great: it looks as though my fa-vorite stop,  .31,  is not close to the optimum. Somewhere around  Sis  a  maximum  surrounded  by  other  high  levels  of  profitability.
Given  the  variability  in  profit  seen  in  the  last  chapter  (Figure7.13),   we  should  check  it  here.  Looking  at  the  cumulative  profita-bility over time, not only do stops increase profitability, they reducethe  variability  of  the  results  dramatically,  as  shown  in  Figure  8.11.Here,  again,  an  analyst’s  art  will  be  in  picking  the  right  cutoffpoint  for  his  or  her  program.  Ptirsonally,   not  trusting  these  valuesas being too explicit (only 35 trades in 11 years), I’d use an MAE
FIGURE  8.9 REVERSING  MAE.  WINNERS  AND  LOSERS  VS.  MAE.Reversing  out  of  a  range  shows  that  adverse  movement  can  behorrendous (as in 1990-l 991) but is generally concentrated in the firstsix bins while winning trades don’t go more than $600 against you.
stop  of  .5,   comfortably  into  the  profitable  range  and  also  com-fortably  below  my  capital  cutoff  point.  Others  might  cut  thingsfinely  at  .4,   taking  most  of  the  additional  profit  and  the  smallestadditional  losses.  Others  might  get  farther  into  the  profitable
FIGURE  8.10PROFIT  VS.  MAE  ON  REVERSING.  As  stops  are  raisedfrom  .l up, the significant jump in overall profits is between  .3 and .4,an extra $100 of loss per contract offset by overall profits rising from1 ,100 points to 2,130 points.
182
Reversing  Out  of  Ranges
Summary  183
SUMMARY
In  the  previous  chapter,  our  campaigning  trader  was  simply  look-ing  for  a  way  to  extract  some  capital  from  a  trendless  market.  Itwas  good  news  that  an  MAE  stop  could  be  defined  for  a  tradingrange,  as  well  as  for  a  trending  activity.  It  turned  out  that,  withoutMAE,  stops  would  have  been  quite  tough  to  set  and  trading  therange  problematic.  With  MAE  stops,  range  trading  was  feasiblebut  not  hugely  profitable.