 a  great  shot  out  of  nowhere  time  after  time.  (As  atrader, which mode would you prefer?)
Neither  is  the  young  player  aware  of  the  substitution  pattern,game  pace,  or  matchups   except  as  he  faces  them  momentarily  onthe  court  or  while  sitting  on  the  bench.  The  game  plan  is  com-pletely  subordinate  to  hitting  the  shot  and  not  getting  beaten  to  thehoop.
It is the same in trading: There are some basics and there are tac-tical  engagements  within  the  endless  campaign.  To  start  with  thebasics, let’s talk about time and loss.
Time  Horizon
This  clumsy  term  refers  to  the  period  of  time  you  consider  whentrading,  time  past  (for  analysis)  and  the  future  (for  projections).You need to know if your horizon is thirty seconds, thirty days, orthirty  months.  Many  analytical  techniques  need  to  be  given  thenumber  of  days  (or  minutes  or  months)  they  should  include  intheir  calculations,  Charts  inevitably  select  a  certain  time  period.  Isit just the past ten days that are relevant to tomorrow’s price, or thepast six weeks or ten years? Technical analysts argue that the mar-ket  in  some  sense  remembers  past  prices,  that  past  prices  have  animpact on today’s price and tomorrow’s, Well, then, what’s the rele-vant memory span?
To  answer  this.  there  are  both  theory  and  practice.  In  true  the-ory,  that  rigorously  maintained  by  academics,  the  market  has  littlememory.  Studies  of  autocorrelation  of  returns  have  almost  allshown  little  evidence  of  today’s  return  being  significantly  related  toyesterday’s,  let  alone  that  of  several  weeks,  months,  or  years  ago.2Although  the  distribution  of  returns  isn’t  quite  normal,  the  differ-ence  from  normal  is  of  interest  only  to  academicians,  options  play-ers,  and  arbitrageurs  with  very  sophisticated  analytical  and  exe-cution  capabilities.  As  for  the  question  of  market  memory,  theefficient markets school didn’t find evidence of it.
Nevertheless,  it’s  hard  to  think  of  a  market  that  trades  indepen-dently of previous prices, that is, at $25 one day, $84 the next, $2the  next,  and  $5,000  the  next.  If  returns  are  statistically  random,what order is it that we see in charts? How are prices related to eachother  over  time?  Despite  our  abysmal  ignorance  of  how  marketstruly work, there have been some suggestions that have merit.
Evidence  of  order  in  the  markets  came  from  Cliff  Sherry!  in  the198Os,   when  he  pointed  out  that  our  conventional  statistical  analy-sis  might  be  misleading  us.  In  his  first  book,  Dr.  Sherry  askedwhether  financial  time  series  were  truly  random,  independent,  andstationary.  He  provided  techniques  for  determining  first  stationar-ity  (whether  the  rules  for  creating  prices  were  changing  or  not);then  dependence  (whether  prior  prices  have  any  impact  on  currentprices);  and  then  randomness  (whether  today’s  price  or  the  changein  price  is  a  coin  toss).  In  applying  the  techniques  to  real-worlddata such as the S&P 500, he found data that were indeed station-ary,  contained  serial  dependencies,  but  evidenced  random  pricechanges.  In  most  trading  within  a  certain  temporal  window,  pastprices have an impact on future prices,  but  within that range of de-pendence, price changes occur randomly.
2 Paul Cootner,
 The Random Character of Stock Prices (Cambridge: MIT Press 1964).
3 Clifford J. Sherry, The M~rhemarics
 of Techtiicol  Afzalysb  (Chicago: Probus  1992).
Basics 7
I  mention  all  this  because  the  idea  of  a  temporal  window  popsup  again  and  again  in  trading.  The  market’s  “memory”  is  not  in-definite, but it exists and is worth studying. Hence, the study of cy-cles,  the  use  of  averages,  and  the  setting  of  parameters  for  time  inindicators  all  have  some  substantive  basis.  You  could  legitimatelyuse  the  evidence  of  dependence  when  characterizing  the  marketyou’re  trading.  If  you  found  that  21  days  was  about  right  for  theS&P (or 200 days), you’d include that much data in your data files(at  a  minimum)  and  construct  your  indicators,  cycles,  and  chartswith  that  number  in  mind.
Cycles
One  approach  to  estimating  a  specific  time  horizon  is  to  pick  outcyclic  behavior  in  prices.  Anyone  familiar  with  trading  literaturewill have seen analyses based on astrological cycles: Gann precepts,seasonal  factors,  and  so  forth.  I  propose  we  give  these  techniquestheir  due  without  indulging  in  them.  The  inability  to  objectivelydefine  and  test  their  precepts  makes  them  unsuitable  for  broad  us-age whatever their validity.
However,  beginning  with  Hurst4   in  1970  and  continuing  fitfullyin  trading  literature  since,  a  line  of  thought  has  developed  that  at-tempts  to  define  mathematically  the  cyclic  content,  if  any,  in  mar-ket  price  streams  (“streams”  as  in  streams  of  data).  Engineers,  inparticular,  have  been  energetic  in  this  regard,  and  two  techniques,transforms5  and  maximum  entropy  spectral  analysisFourier (MESA)6  have proven consistently applicable.
*  J.  M.  Hurst,  Thr  Profit  Magic  of  Stock  Trmsrrcrion  Timing  (Englewood   Cliffs:Prentice-Hall.  1970).5 Anthony  W Warren  and  Jack  K.  Hutson,  “Fast  Fourier  Transform,”  TechniculAnalysis of Stocks and Commodities, vol. 1 (Seattle: Technical Analysis, In%1981).  I  don’t  recommend  this  technique:  MESA  is  much  better  at  extractingshort-term cycles using short data lengths.6  Anthony  W.  Warren,  “An  Introduction  to  Maximum  Entropy  Method  (MEM)Technical Analysis,”  Technical Analysis of Stocks and Commodities, vol. 2  (Seattle:Technical Analysis, Inc., 1982). See also John Ehlers’s work based on a Ph.D.  the-
8  Campaigning
The result has been that cyclic content, at least insofar as we cancapture  it  mathematically,  is  episodic.  John  Ehlers,  easily  the  lead-ing  analyst  in  this  area,  reports  realistically  that  depending  on  theitem being traded and, probably, many other factors we don’t knowabout,  sharply  defined  cyclic  content  pops  up  between  20%  and30% of the time. The good news from my experience is that when itdoes  pop  upI   it  usually  centers  around  consistent  values-numbersof days being the most common measure (see Figure 1.2).
Practically speaking, this means that it is possible to make an ed-ucated  guess  about  the  relevant  time  frame  for  your  analysis.  ForTreasury  bonds,  this  value  has  almost  imperceptibly  expandedfrom eight days in 1982 to around ten days in the past 13 years. If Imust  make  a  guess  or  supply  a  parameter  for  bonds  (say,  for  amoving  average  or  an  RSI),  I’d  use  ten  with  great  comfort.  Otherfutures  contracts  show  similar  phenomena.  1  rarely  trade  stocks,but  my  cursory  experience  is  that  stocks  exhibit  stable  cyclic  con-tent in about the same proportions. After surveying the Dow 30 onMay  9,  1995,  using  Ehlers’s  software  MESA,  I  found  that  aboutone-third  showed  a  consistent  level  of  cyclic  content  during  theprevious  four  months.
The  value  you  use  will  change  and  MESA  makes  estimatingthese values visually easy. At the same time, you will also be able tojudge  from  the  smearing  of  the  spectrum  how  reliable  the  estimateis.  Plus,  the  lack  of  cyclic  content  may  be  an  important  clue  thattrending  behavior  has  set  in.  Figure  1.3  shows  an  even  clearer  ex-ample from the Commodity Research Bureau’s index.
Economic  Cycles
More difficult to apply while  seaching for time horizons in specula-tive trading are the economic cycles that I, among many, find rela-tively  consistent,  Whole  foundations’  are  devoted  to  chronicling
sis  by  John  Parker  Burg.  Stanford  University,  1975.  John  F.  Ehlers,  MESA  andTrading Marker  Cycles   (New  York:  John  Wiley  &  Sons,  Inc.,  1992).’ Foundation  fbr the Study of Cycles, 900 W. Valley Road,  Suiie  502,  Wayne,  PA19087. Phone (610) 995.2120, FAX (610) 995.2130. Columbia  Center  for  Interna-
9 5
B A N DPASS
PNASt
CfCLE
EXEMPLARY  MESA  ANALYSIS.  During  early  1995,  the
FIGURE  1.2Treasury bond  futures’dominant   cycle  (the  bottom  panel  in  the  display)oscillates between 8 and 15 days. The cursor shows a day with asubpeak  at  12  days.  Cyclic  content  is  high  during  periods  when  the  linein  the  bottom  panel  has  no  (or   little)  color  smeared  above  and  below  it.A sharply defined peak in the spectral display to the left is the result.
the  components  of  economic  expansion  and  contraction.  Manybusiness  folk  have  a  ground-level  view  of  this  through  their  dailyinteractions  and  are  especially  aware  of  it  after  they’ve  beenthrough it once or twice. Local banks are usually in the business of
tional  Business  Cycle  Research,  Columbia  University,  645  Madison  Axnenue;  19thflooz  New  York,  NY  10022.  Phone  (212)  688-2222.  National  Bureau  of  EconomicResearch,  1050  Massachusetts  Avenue,  Cambridge,  MA  02138.  Phone  (617)   868.3900.
10  Campaigning
Basics  11
231
BANDPASS
PHASI
FIGURE  1.3 CRB MESA SPECTRUM. CRB futures show a rock-steadycyclic  content  of  20  days  during  early  1995  in  the  cycle  bar  at  thebottom  of  the  display.  Note  the  sharply  defined  spectral  curve  peakingat 20 days with a subpeak
 at half-cycle length around  9 days.
today’s  economic 
structuring  themselves  for  an  interest  rate  outlook  that  ebbs  andflows with the economy. Either of these sources is better than gen-eral journalistic coverage, which usually comes after the fact and isreports.focused  on For a trader’s purposes, business cycles are primarily setups forshort-term  trades.  It  helps,  for  example,  to  know  when  cyclicalstocks are likely to respond to expansions and, generally, to knowwhich way interest rates are likely to go as the economy moves. Ro-tation  into  and  out  of  industry  groups  is  a  full-time  practice  forsome  portfolio  managers,  and  even  futures  traders  can  exploit  the
differing  performances  of  grand  sectors  (equities,  debt,  currencies,and commodities) with all the vehicles now available.*
Finding  a  trading  horizon  with  economic  cycles  requires  pocketsdeep  enough  for  a  one-  to  two-year  swing.  An  active  speculativetrader  will  likely  have  more  immediate  opportunities  come  up  dur-ing  that  length  of  time  than  he  or  she  can  ignore,  opportunitiesthat  won’t  require  committing  a  lot  of  margin  money  to  accumulat-ing a position that won’t be disbursed for four years. For example,the usual result is that a speculative trader may be aware of copperbasing at low values for a year or so, but won’t take positions untilshort-term factors indicate a break upward.
Charting  Averages
Every  investor,  trader,  or  speculator  knows  that  at  some  point  thetrade he or she has in mind will be ready to go. The only question iswhat  action  will  cause  the  trader  to  take  action.  Waiting  for  abreakout  in  an  undervalued  stock  is  simply  waiting  for  the  otherpeople at the market to recognize what you see. Assuming you can’tbuy  all  the  stock  and  realize  its  true  value  by  selling  it  or  grabbingthe  cash  flow  from  it  (i.e.,  a  takeover),  you  must  to  have  publicopinion  on  your  side  to  realize  the  value  of  the  company,  or  thecommodity,  or  the  instrument.  Since  cash  talks,  nothing  indicatesthe  concurrence  of  opinion  better  than  other  people  paying  up  fora tradable and thereby causing the price to move.
It’s at this point that technical analysis serves to define breakout,define  movement,  and  define  our  time  horizon.  The  most  venerableof the technical tools, moving averages, probably does the job best.Having  the  virtues  of  simplicity  and  an  inability  to  ignore  a  trend,averages  that  give  reasonable  crossings  of  price  channels  and  skimtops  and  bottoms  nicely  can  be  defined  visually  simply  by  plotting
*  To  home  in  on  these,  Martin  Pring’s  Intermarket   Review  serves   futures  traderswell  with  practically  rigorous  criteria  for  defining  different  points  in  economic  cy-cles  Martin  Pring,  “Intermarket   Review,”  P.0.  Box  624,  Gloucester,  VA  23061.0624. Phone (800) 221-7514.
12  Campaigning
Campaigning  13
the averages and adjusting them to fit. You’ll find an amazing con-currence  in  length  with  the  values  generated  through  analyticaltechniques  like  MESA.  We  will  examine  this  further  in  Chapter  2.
Summarizing 
Time
Having  an  idea  of  the  cycle  time  or  response  rate  of  a  tradablehelps  in  defining  indicators,  building  trading  strategies,  and  select-ing  trading  instruments.  Given  the  roughness  of  the  data,  the  toolsI  have  described  will  serve  well.
Loss-Not  Risk
The  second  basic  skill  is  losing  money  minimally.  An  aphorismstates the cardinal rules of trading as “First, don’t lose your money.Second,  see  rule  one.”  One  must  be  more  artful  to  avoid  losingmoney  than  to  make  money.  Not  losing  money  is  also  the  key  towinning  the  investment  game.  Especially  in  futures  where,  absentcommissions,  the  game  is  zero-sum,  you  must  minimize  the  sire  ofyour  largest  loss.  My  approach  to  success  is  not  on  good  tradingsignals  but  on  minimizing  losses.
So, let’s not use the word “risk” because, quantitatively, it refersto the variance of returns, and variance could be a gain as well as aloss. What we fear is loss. What we must minimize is loss.
Fine,  but  how?  You  need  to  know  what  kind  of  situation  yourtrading  rule  selects  and  the  usual  results.  Necessarily,  the  marketwill do one of three things with your position: advance it, ignore it,or  go  against  it.  Whatever  your  entry  rule,  you-like  all  traders-must know when to admit you’re wrong and turn around.
I take the approach of observational experience. Given a consis-tent  rule,  I  ask  how  winning  trades  behave  and  how  losing  tradesbehave. I’ll show by example that winning trades just don’t go veryfar bad. If a trade does go bad by a certain amount,  un amount youcan  nzeasurr,  it’s probably time to get out or reverse your position.This is how you avoid losing excessively and, thereby, how you win.
If  we  have  this  information-we  know  what  we  will  lose  on  alosing  trade-simulation  (another  form  of  experience)  or  histori-cal  testing  can  tell  us  what  our  odds  of  winning  and  losing  are,and  the  two  (probability  and  expected  outcome)  give  us  our  capi-tal  requirement9   Exercises  like  this  have  generated  the  rule  of  of  one’sthumb  that  any  given  loss  should  be  no  more  than  ~2%‘~total  capital,  though  active  traders  vary  that  number  as  low  as  1%and as high as 5%.
With  our  time  horizon  and  loss  level  in  hand,  we’re  ready  to
campaign.
CAMPAIGNING
Take it as a given that the market is either moving or it’s not. I useonly  two  modes,  trending  or  nontrending,  despite  entire  cataloguesof  chart  patterns that  encapsulate  differing  behaviors.”  Thissimplification leaves us to deal only with periods of quiet and peri-ods of trending (see Figure 1.4).
The  point  of  campaign  thinking  is  to  exploit  the  full  range  ofmarket behavior for profit rather than to lock into a single mode oftrading,  whether  it  be  waiting  for  a  trend  to  assert  itself,  tradinginto  ranges,  or  trading  oscillators.  In  a  campaign,  as  contrasted  to
  Monq   Market  Strategies  for  Futures  Traders  (New  York:
9  Nauzer  J.  Balsara,John  Wiley  &  Sons,  Inc..  1992).  pp.  8-22.lo  I  picked  this  number  out  of  the  air  early  in  my  career,  and  I’m  now  at  a  loss  todefend  it  with  a.  reference  to  anything  back  then.  It  turns   out  to  be  in  the  ballparkfor  a  very  low  risk  of  ruin.  Balsam’s  book  doesn’t  check  below  10%.   but  see  test-ing  reported  by  Tom  Basso in  “The  Trader’s  Psyche:  Tom  Basso;”  Technical  Anrrl~~-sis of Stocks and Commodities, vol. 11. p. 451. Another practical reference is fromMonroe Trout at  1.5”L in Jack  Schwager,  The New  Marker  Wizards  (New  York:HarperCollinq 1992),  p. 167.‘I  Robert D. Edwards and John Magee, Technical Analysis of Stock Trends, 6th ed.(Boston:  John  Magce   Inc.,  1992).  For  candlestick  patterns,  refer  to,  Steve  Nison,Japanese Candlestick Charting Techniques (New  York: New York Institute of Fi-  (New  York:  John  Wileynance,  1991).  Also,  see  Steve  Nison,  Beyond  Candlesricks&Sons,  1994).
14  Campaigning
Price
T i m e
FIGURE  1.4TRENDING  OR  RANGING?  In  this  book,  I  use  a  simpletwo-mode description of market behavior. Although there are far morecomplex conceptions (for example, Elliott  waves  or cyclical models), tomake the point of analyzing market behavior using our experience, onlythis simple model is needed.
the  typical  single-mode  approach,  we  must  alter  our  stance  as  themarket  gives  us  clues,  make  entries,  lose  lightly  on  some  trades(maybe the majority), win on others, reverse into the proper mode,add positions as fortune favors us, and exit or reverse the entire po-sition as the chance occurs (see Figure 1 S).
Price
I
I
I 
1  
A
1
Time
c
FIGURE  1.5 CAMPAIGN  TRADING.  Don’t  take  these  idealized  entriestoo seriously--nothing ever goes like this. Instead, consider the greaternumber of opportunities to  build a position with an approach thatexploits all modes of market behavior.
Classic  Stages  15
Clearly,  a  single  trading  rule-the  usual  approach  in  publishedtrading  systems-is  inadequate  for  this  constant  thrust  and  parry.We’ll need several rules, several ways of looking at the market andjudging what mode we’re in and how to exploit it.
Whatever mode the market is in, the trader must have a positionin  order  to  profit  and  to  build  the  position  to  profit  more.  Manytrading strategies assume that a one-contract strategy can be scaledup  if  successful.  Were  all  the  opportunities  presented  by  marketmovement  exploited,  many  more  initial  entry  techniques  would  beseen to be valuable. For example, a trend entry by itself might hap-pen barely enough times to offset many small false entries. If, in ad-dition  to  the  initial  entry,  other  entries  could  be  made  profitably  inconcert  with  the  first,  a  barely  profitable  technique  would  be  seenas only the first step in a series of trades of much greater value.
Of course, achieving this is not easy, but the argument that a sin-gle trading strategy is the way to approach the market must be sus-pect-if  only  because  we  are  aware  of  all  the  amazing  behaviorsthe  market  shows  us  given  the  millions  of  actions  that  impinge  it.We cannot fathom all that, but we really have only two dimensionswith  which  we  must  deal:  up-down  and  time.  From  these  simplici-ties, we must insert an opportunistic series of trades that probe forwhat  the  market  will  give  us,  trades  with  the  overall  goal  of  creat-ing a profitable position from very comfortable levels.
CLASSIC  STAGES
Basing,  breakout,  trending,  topping,  and  retreat:  these  form  theclassic  stages  of  a  market  campaign.  The  crude  oil  market,  whilenot  as  clear  cut  as  the  bond  market  from  which  I  abstracted  thecampaign  image,  has  moments  of  drama  of  its  own  (see  Fig-ure  1.6).
My  sense  is  that  markets  trade  differently,  reacting  more  or  lessviolently  and  more  or  less  continuously  to  change.  Charts  capturethis  sense  of  distinction  by  showing  the  rapidity  of  advance  or  de-cline,  the  gaps,  the  range  about  points  of  value,  and  the  depen-dency  (or  lack  of  it)  on  past  pricing.  If  markets  trade  distinctly(though  interrelationships  obviously  exist),  our  general  approach
25
20
15
I
FIGURE  1.6 ACTION IN CRUDE. New York Light Crude hasn’t movedas  violently  as,  say,  Treasury  bonds  in  this  decade,  but  Crude  has  had  itsmoments.  The  huge  size  of  the  energy  markets  gives  prices  faircontinuity for trading purposes.
must  master  this  variety  rather  than  impose  a  spurious  consistencysuch  as  “a  good  trading  system  should  do  well  in  every  market.”I’m going to show you an analysis of New York Light  Crude,t2  butonly  the  analytics  will  carry  over  to  other  markets,  not  the  results.
Mode  1:  Trading  Range
The  ideal  setup  for  a  campaign  is  when  a  market  is  quiet,  goingnowhere. This is when it’s never mentioned in the market press, vol-ume is low and regular, and there’s not much activity at the special-ist’s desk or in the pit or on the phones. Everyone knows the  bid-
I2  I  rarely  trade  Crude.  I  selected  it  to  see  how  my  techmques   would  apply  tosomething  besides  rates  and  currencies
Classic  Stages  17
ask  spread  and  attempts  to  push  it,  just  to  earn  rolling  eyes  andsarcastic comments. On the screens, it doesn’t screen. It never setsoff  anyone’s  search  criteria,  usually  oscillating  about  some  centralvalue. Its regression is a flat line for any tradable horizon, its aver-ages  trundle  through  the  daily  range  bars,  and  daily  range  itself  ishistorically  small.
During this period, we’d like to trade into the trading range. Themajor  concern  is  whether  there  is  enough  of  a  trading  range  totrade. We need a range roughly twice the loss we‘re going to take onbreakout.
Loss?  On  breakout?  You  see,  the  plan  is  to  trade  into  (or“across,”  if  you  prefer)  the  range.  Therefore,  by  definition,  whenthe breakout comes, we’ll be going the wrong way, necessitating areverse. If the range we’ve just come across is  18 points and we’regoing  to  lose  18   points  on  the  breakout,  we’ll  just  be  even.  Betterwould be to get ahead by 18 to 36 points coming across the range,but  of  course  this  is  determined  by  the  market  you’re  in.”  Somemarkets will allow you more than others when they are in a range.We’ll  develop  the  specifics  of  this  strategy  later.  For  now,  thecampaign  begins  with  a  quiet  period.  As  we  oscillate  back  andforth  across  the  range,  we  gradually  build  up  our  position  andbuild  it  profitably.  We’ll  give  up  some  of  those  profits  when  webreak out-how much is unknown but, as we’ll see, experience maygive  us  some  guides.
We may not have a long time to exploit this quiet time. In stocks,it could be years; in agricultural commodities> it’s partially dictatedby the season and partly dictated by the reactive cycles of the pro-ducers; in the hard commodities, the economic cycles seem to dic-tate  what’s  moving  and  how  long  we  have  to  accumulate  whenthere’s  no  movement.  In  financials,   quiescent  periods  were  veryshort  during  the  1970s  and  198Os,   but  the  increasing  firmness  andconsistency  of  the  monetary  authorities  in  the  1990s  is  dampeningmarket  volatility  and  increasing  the  length  of  quiescence.  On  theother  hand,  the  huge  amounts  of  money  flogging  about  the  globefor  short-term  return  and  speculative  adventure  has  shortened  thewaiting  periods  in  currencies  dramatically.  Long  famous  for  their
I3  For Crude, the range will  be about 100 trading points and the loss  about  30
18  Campaigning
tendency  to  trend,  currencies  are  now  major  speculative  vehiclesfor  their  depth,  liquidity,  and  constant  movement.
Each  person  will  pick  the  time  frame  within  which  he  or  shespeculates.  Those  wishing  no  overnight  losses  will  trade  intraday.Those trading positions will be anywhere from two days to severalmonths. We can look at daily or weekly data.14  For the purposes ofthis book, we’ll use 