weekly and weekend pat-terns. It is most common to find that the price movements from Thursday to Friday (close-to-close) are in the direction of the major trend and that the movement on Monday is acontinuation of that trend: By Tuesday (or. sometimes Wednesday), the strength of newbuyers or sellers has faded, and the market reverses due to lack of activity and some profittaking, It often stays in this state through Wednesday or early Thursday when it againresumes the trend. In a sideways market, the Friday and Monday directions differ from thedirection during the prior week and often differ from each other.
Support and Resistance .
Support and resistance levels are important to the short-term. trader. If prices start to movehigher, slow down, and finally reverse, it is natural to consider the top price as a resistancepoint. Prices are thought to have been stretched to their extreme at that level. Any subse-Quent attempt to approach the previous high price will be met with professional selling inanticipation of prices stopping again at the same point, In addition, it is common for thesame traders and others to place orders above the previous high prices to take new longpositions or close out shorts in the event of a breakout.
‘This method, very popular among floor traders and active speculators, tends to createand emphasize the support and resistance price levels until they define a clear tradingrange. Within a 1- to 3-day period, these ranges can be narrow and yet effectively containprice movement. During the life of the trading range, it will continue to narrow as the lev-els become clear to more traders and the anticipation ofa reversal at those levels becomesimminent.
‘To take advantage of the smaller ranges caused in this manner, it is necessary to ent?positions during the middie of a trading session, frequently holding that trade until thea uddle of the next session. An example using the Chicago Board of ‘Trade December 75 Sil-ver contract, during August 1975, will help to illustrate this. Prices on 4 consecutive daysare seen in Table 16-4. The opening and closing prices for the first 3 days do not indicate
MARKET PATTERNS429
 
TABLE [6-4 December 75 CBT Silver
 
 
Open High Low CloseAugust 21 500.50 505.00 493.00 498.202 501.00 504.00 494,50 500,0025 501.00 594.50 496.00 503.8026 502.50 504,00 483.80 483.80
 
any opportunity for trading. Prices were generally in the middle of the daily range. By usinge high and low of the previous day, this situation can be traded either of two ways.ae purs lay, August 21, forms a range of 505 to 493, closing near the center of the range.After the next open, buy just above 493 and sell just below 505 to be certain of enteringa enue the position. For protection, a stop can be entered at about 506 and 492 toreverse the position on a breakout. Had this procedure been followed, entering 2¢ (200thepoints ounds of the range, Table.16-5 shows how trades would have been exe-the cach oe the entry) was 200 points before the level at which prices had reversed on. The Stop-Loss order was placed to limit losses to a 100-poi iThe S DSS OF -point penetration.Although this is an ideal situation, professional traders frequently use this tnethod. tteanPe een that the support levels did actually rise from 493.00 to 494.50, and then to 496.00.en support was penetrated, prices rapidly broke to new lows of 483.80, down to theermissib le Leni Similarly, the resistance level remained intact going from 505.00 to.00, .50, and finally, 504.00. It is generally accepted that the resis' ‘; , tance Le -sents amore volatile area that must be watched closely for false breakouts. vet epeesupport and resistance levels gain importance the more time th main i: 2 ey remain intact. Thehigh and low of the prior day are not as significant as the weekly or the monthly range.Each can be traded using the same technique. The major support and resistance levels arentract highs and lows, which rarely allow breakouts with less than one attempt. Longer-term price objectives can be identified using a continuation chart. This chart plots only thenearest (spot) futures contract of a specific market to allow the location of support andresistance levels when the current contracts are in a new high-or low area.be Before 1990 there were very few published day-trading systems. The more recent onesave had the benefit of sophisticated computer programs and large historical databases.
The following method pre i i ioe fom Ig precedes this era and remains unique and a valuable part of our lit-
 
TABLE 16-5 Trading December 75 Silver Using Support and Resistance
 
 
ProfitiLoss ~August 22 Sold at 503.00Closed-out short and bought at 495.00 -August 25 Closed-our long and sold 502.00 yooClosed-out short and bought at 496.50 45.50August 26 Closed-our long and sold at 502.00 45.50Closed-out short and bought at 498.00 +4.00Closed-out long and sold at 495.00 ore 3.00Open position +11.20
en 
vst
 
430 DAY TRADING
The Taylor Trading Technique
In 1950, George Douglass Taylorheen using for many years in both the stock and grain mithe experience of discipline and timing, but is carefully set down and can be implementedin either a sophisticated or simplified state. The system is intrinsically cyclic, anticipating 3-day movements in the grains. These 3 days can °0y in pattern when they are within anuptrend or downtrend. Taylor's explanation Of his method is thorough and includes manyUP tuable thoughts for traders interested in working with the market full-time. The sum-mary and analysis presented here cannot teplace a reading of the original material.‘Taylor developed his approach to trading through experience and a belief that there isabasic rhythm in the market. The dominant pattem is seen to be a 3-day repetition withSceasional, although regular, intervals of 4- to S-day patterns. Taylor's cycles are based oncontinuous trading days without regard to weekends and holidays. The 3-day cycle variesslightly if prices are in an uptrend oF downtrend. The uptrend is defined as having highertops and bottoms over some selected time period such as a week, month, or season. A:downtrend is the reverse.
During an uptrend the following sequence can be expected:1. A buying day objective,
before a rally begins2. A selling day objective,3, A sbort sale day objective,reversal.
published his book method of day trading, which he hadarkets.? The method is based on
where prices stop declining and a purchase can be made
losed out '
at which the long position is cl.-e and can be sold prior to 2
where prices meet resistanct
Following the third day, after a short position is entered, the cycle begins again with abuying day objective. Because an Uptrend is identified, Taylor has given ere latitude tothe long position with part of the day between the liquidation of the long (2), and entering a new short (3) reserved to allow the upward momentum to exhaust itself, Downtrends
,wnward move to finish before the
are the opposite, expecting some added time for the do
rally begins. ,Tee rctial objectives are extremely short-term suppor and resistance levels, usually
only the prior day’s high and low prices or se ccasionally the high and low of the 3-day cycle,
which may be the same prices. Ona buying day, the objective is a test OF penetration of theprior day’s low price, but only if it occurs first, before a test of the prior ‘highs. Taylor’smethod is then a short-term countertrend technique, which looks for prices to reversedirection continuously. His belief was that speculation caused these erratic, sometimeslarge, cyclic variations above ‘and below the long-term trend.
‘Taylor placed great emphasis on the order of occurrence of the high and low on eachday. To buy, the low must occur first. If thisis-a buying day in an uptrend, a long position isentered after any lower opening w!
nether or not the prior low is reached. Taylor reasoned
that because an uptrend is generally stronger toward the close, the first opportunity mustbe taken on a buying day. However, ifa high occurs first and prices then decline nearing theTows toward the end of the trading day, no long position is entered. This pattern indicates alower open the following day, which ‘will provide a better opportunity to buy. During adowntrend, the violations of the lows, or penetrations toward the close, are more common.
By waiting until the next day to purchase, the 3-day cycle is shifted to favor the short sale.
Consider the same problems with regard to closing out a long and entering a newshort during an uptrend. If on the same day that the long was entered prices ralliedsharply, touching or penetrating prior highs, a higher opening would be expected the nextday, at which time the long position would be closed out. Because of the uptrend, a small
2 The Taylor Trading Technique, by George Douglass ‘Taylor (1950) (reprinted by Traders Press, PO- Box 6206,
Greenville, SC 29606, in 1994).
 
MARKET PATTERNS431
 
setback and another test iof the highs might bsetback and anothe e expected. It would then iSpen ofthe sbort ‘Surength was exhausted. If the highs of the selling Sapce wnedon idopen of the shor sale iy, a new short would be entered immediately. If edayned lower and finished higher, no position would be taken. ly. the short sale dayactions to price move: ,buy ee s are expected when a long po:buy da or onthe next open, when a downtrend exis Tr prices silly sharply om the sameday, the position is clo sed out at a Profit ‘This is important to remember, becaus tr cing: tat a Prof y 7 se tradin;saanetinee the onion latitude of waiting for the best moment; time is workTaylor called this his bookte hod befor ais boo. metl ecause he recorded all the i ifor tradin 8 in ame x 5” spiral notebook that he carried. The eganeatione ‘the bookin tales e 6S, an example that uses the November 75 soybean eee Ocoee,in ‘Taylor book, ly 1 month per page di its si h vecontain the date and day followed by the open, high foo and closing prices The, high, tow, g prices. The
 
TABLE 16-6 November 1975 Soybeans
 
 
 
 
 
 
 
1975 oOpen High Low cklose 2 R BHO> U Net= March10" '0 bao > 535 540%v 435 580% 560) 7 18% ©552 S71% :a 3 568: 559 560% ”553 589 Tst s49% 28™ " 548 548 548 n ° ° ™q is 55s 538 5384w 8 5 546 S45 2 0" x» 43 540 S474 26 °t 2 sa” 4% G5e7% S474 S674sei 561) -" 573 6K y‘ ia 573 564 574 1 m °w * 377 7594 574 594 ‘8 » 57 590 (579) 585 Is 02 589 5954 244 ° a- April1 : 599 584 591%» 2 ses 591% 575% 24 °9565 566%Foe 4 570 567 576% °m 7 377 S77 ~ (S82) 865% 16 o 3‘ 8 566 563 568% 74 .” Be 65 STA) 5614 S734‘ ro a 575 (7555) 581% Ig 1 yF u 60 | GbE) 558 5634 84 ”" 4 sel Gs68) 55% 561% ~q 's 58S 5694 5634 ThA 1A» ie 362 586) 553 559% y . °' 560 558 563% “A18 563 563 559
        
  
 
 
 
seeceaes ened ate meae shiite:
a DAY TRADING
first 10 days are used to determine where the cycle begins. Scanning the daily lows, circlethe lowest of the first 10 days, in this case March 19. Then work backward and forward, cir-cling every third low price. These are buying days. The sequences of two in-between daysare circled in the high column and indicate the selling day and the short sale day, respec-tively. This example is especially simple because it assumes a consistent uptrend and showsno variation from the 3-day cycle.
‘To judge the opportunities for buying and selling, the next columns, marked D and R,indicate the number of points in the decline from the short sale to the buying day, and thenumber of points in the rally from the buying day to the selling day. In both columins, the differences are taken using the highs and lows only. These values represent the maximum num-ber of points that could have been made in those trades, provided the highs and lowscceurred in the proper order. An “x” or a *¥” in the circle next to the high or low means thatthe opportunity to buy or sell occurred first Gf an x) or last (if a /). In the case of the first,the trade would have been entered that day and in the other case, Taylor would have waited.
The next two columns, BH and BU, show the adversity and opportunity of that day’sprices to the buying objective, BH means a buying day high and is entered with the num-ber of points that the day traded above the prior day’s high (the short sale day); BU showsthe opportunity to buy under, by recording the number of points by which the day soldunder the low of the prior day—the area to buy if the low occurred first. If neither situa-tion occurred, zeros were entered.
‘A wide column on the right is used to indicate the net weekly change in direction bytaking the difference between the prior Friday’s closing price and the current Friday'sprice. This should be used to compare with the trading performance.
By observing columns D and R in Table 16-6, it can be seen that there was ampleopportunity for profits on both the long positions and short sales, with only one case of agero entry on April 3. The trades that would have been entered or liquidated can beapproximated using the BH and BU columns and the x and / notations. For consistency, itmight be assumed that the V¥ indicates that a position was taken on the next open. In eithercase, the results would have been good.
Yaylor’s daily method requires care in monitoring the market, which only a full-timetrader can provide. The order of the highs and lows must be observed, as well as whetherthe new low is going to penetrate or fail to penetrate the prior lows. The trades must betimed carefully for maximum profit. In addition; it would be helpful to combine thismethod with a good trend identification technique as well as observe seasonal patterns toimprove the choice of the overriding market direction.
For those who cannot watch the market constantly, Taylor offers a rigid 3-Day TradingMethod, which is a modification of his overall daily method. The cycles remain the same,but the buying and selling objectives are entered into the market in advance. This methodis expected to work on balance, as are other well-defined systems. ‘What is primarily lost bythis approach is the order of occurrence of the highs and lows; otherwise, the concept ofthe system remains intact.
It is interesting that this technique profits fron penetration of support and resistanceJevels. Most other methods consider a breakout of prior Nighs and lows as a major trendchange indication, but Taylor views it as a better opportunity to do the opposite. It is oneof the few examples of such an approach and coutd only succeed in the short term, wherethe behavioral aspects of trading are dominant
Intraday Breakout Systems -
‘As discussed earlier in this chapter, there are unique intraday price patterns caused by antneven distribution of volume throughout the day. By far, the most popular systematic
 
 
MARKET PATTERNS:433
approach to day trading is the N-day breakout applied to intraday data; this transforms itino the ar breakout, Entry and exit signals occur during the trading session instead of; in addition, there m: i ionly af the close; in ad ay be more than one buy or sell during the day ifwhi a variation of this technique intended for intraday data is the opening range breakout,?¢ underlying entry and exit signals based on how far pri .open of the day. The trader is then buyi: i eiettne oeen bn foxday. e ying when prices move up from the open by, foBake below the open th in the same manner as a trend follower. If prices then dechne toen, the long position would be reversed to a short. This approai i 0 . ich usesthe opening price as the pivot point for the day, claiming that price direction relative topoint, is important. Tests exited all trades on the close of the day. ,waren edav'e orcs en to use the close of the previous day as the pivot point. Most traders's prices to see if they are higher or lower than the prior cl himensch roday’s pices to se if a . , prior close, which connectsprevious day. In its basic form, the openin,treats one day as independent to previous pri , ee ee ensSO inde| vious price movements. This seems unnecessarilrestrictive. Crabel, in his extensive study of i nationstric . ly of intraday patterns, has found that combination:of inside days, low volatility, bull and bear hooks, and other patterns that precede the car.rent ays contribute to a selection process that improves trading. Table 16-7 shows acomparison of an opening range breakout with and without a preceding inside day.‘ Thtimprovement due to selection is significant. “meIf you consider that intraday tradi i iy trading may give one new signal each day, any methodthat) helps select the better trades is welcome. The intraday trading profile ws mary smallpr ofits an losses allows you to be more selective without fear of missing the one big trade¢ year, which is a problem typical of a long-term trend-following system. Skipping as
> See Toby Crabel, Day Trading With 55 Short Term Pri. dGreenville, Se 29603), 8 ‘hort ice Patterns and Opening Range Breakout (Traders Press,
7% “Openiroby Crabel, “Opening Range Breakout, Part 4,” Technical Analysts of Stocks & Commodities (February 1989)
 
TABLE 16-7 Opening Range Breakout, % Profitable Trades*
 
 
Any Day (%) Inside Day (%)Bonds Open plus 6 ticks 60 76Open plus 8 ticks 55 74Open minus 8 ticks 56 62Open minus 16 ticks 56 66S&P 500 ‘Open plus 160 points 68 et”Open plus 80 points 55 s7Open minus 80 points 49 48Open minus 160 points 49 45Soybeans ‘Open plus 10 cents 60 70‘Open plus 5 cents 56 67Open minus 5 cents 58 6Open minus 10 cencs 63 7%Cattle Open plus 50 points 65 55Open plus 25 points 58 55_ Open minus 25 points 58 “60Open minus 50 points 63 - B
  
 
 
DAYTRADING
434FIGURE 16-3 (2) OmegaTradeStation code for first-hour breakout indicator:
TradeStation code for first-hour breakout system. (b) Omega
{ System: lst hour Breakout (adapted from M. McNutt, 1994) }(10) MaxBarsBack
[*] Generate Realtime Orders
[*] Do not allow multiple entries in the same direction
system uses ten minute bars of gap futures for data 1 and 60 minute bars for data2 tdaily data is held in date 33 1
yars: SessiFirstBarbAte (9, data2), sessiFirst8arHigh(O, data2).SessiFirstBarlow(0, data2), avedayrange(0,data3) +
input: Ranin(10)5avedayrange = @average(high of data3 = low of a
Gf (time of data2 = SesslFirstBarTine of data2) or(date of data2 > date(l) of data2) then beginSessifirstBarDate = Date of data2;SeselFirstBarHigh = high of data;SesslFirstBarLow = Low of data2;end;If (SesslFirst8ardate ~ Date of data2) and(time of data2 < SesslEndtime of dataz) then beginTf closetl] < SessiFirst@arHigh then buy atSessiFirstBarHigh + 20 point stopsif closef1] > SessiFirstBarLow then sell atSessiFirstBarlow - 20 point stop;
ata3, Rann) of data;
end;
Gf low <= SessifirstBarHigh ~ avedaytf high d= SessiFirstBarLow(1] + evedayrenge then exitlong(a)
from M. McNutt, 1994) 1
range then exitshort at market;at market;
{indicator: ist hour Breakout (adapted
vars: SessiFirstBarDAte (9, data2), sessiFirstBartigh(0, data2),SessiFirstBarlow(0, dataz). ‘avedayrange(0,data3); .
avedayrange = @average(high of data3 - low of data3, 10) of data3;
if (time of data2 = SessiFicstBarTime of data2) or(pate of data2 > datefl] of data2) then beginSeeslFirstBardate = date of dataz;SeselFirstBarhigh = high of dava2;SesslfirstBarLow = Yow of dataz;end;
jf (SegslFirstBarbate = date of date2) and‘tine of data? < SesslindTime of dataz) then beginpioti(SesslFirstBarHigh, “ist Buy"); .
— plot2(SessiFirstBarLow, “1st sell")3 .
plota(sesslFirstBartow + avedayrange, "Buy stop");plota(SessiFirst8arHigh ~ avedayrange, "Sell stop”):
end;()
a
|
 
MARKET PATTERNS”435
many as 50% of the trades should n iot limit your profit potentialstand aside and start again without much concern about eoatine you should be able to
 
Breakout Ranges Based on Time
InsteacInstes se ofa breakout that occurs when prices move a fixed number of points away fromthe opening pecs, you can establish an opening range based on the first 60 minutes oftrading” After this time, a new high o: tow ‘would be a signal to enter a long or short posi-Fd ee a eae Cary and continue in the same direction.the beginning continue in the same direction.ne ined with the irthour breakout i calculation of the day's trading range to beused for reversing your postion or taking profits. The projected range high is calculated asthe average daily range added to roday's low price after the first hour of trading; the low isthar same range calculation subtracted from the high of the first hour. The Omega Ea:Language code for this sytem inuclves the use of multiple time frame data and can befound inne re laeal an indicator that shows the signal on a chart page is given in Figure36-3, In the practical application ofthis method, the frs-hour range must be penetratedby at leas 20 points forse S&P. If the first-hour range is nearly as large as the average 10-day range (used fo the exit targets), use the anticipated high and low for buy and sell si, ‘an a breakout of the first-hour range. Other risk controls, such as a trailing
stop (in addition to a reversal if th i is gistop in ada ifthe opposite signal is given) and a fixed stop, are also rec-
5 Malcolm McNutt, “FirstcNutt, “First-Hour Breakout System,” Technical Analysis of Stocks & Commodities Quly 1994) 
 
 
: 17
SEAdaptive Techniques
n adaptive technique is one that changes with market conditions. It could be as sim-A&: as using a percentage stop-loss; however, technicians have begun to associate the
idea of “adaptive” with a broader scope, although the purpose remains the same—tohandle more changing conditions without manual intervention ‘The trends and indicatorsthat are discussed in this chapter are able to change the calculation period. Under someConditions, such as sideways markets, it may be best to use 2 slow trend or momentum,and during explosive intervals those same methods are expected to work better if they
respond quickly.
ADAPTIVE TREND CALCULATIONS
ques that vary the length of the trend. These techniques arebased on a common premise that it is better to use a longer-term trend, one that is slowerto react to price change, when the market is either in a “sideways” pattern, has low volatil-ity of, in the case of Kaufman, has high relative noise. This may seem a reasonable assump-tion, but identifying a sideways market is very difficult. A price may be unchanged from aweek ago, yet during those 5 days it rose-quickly for 3 days, then reversed sharply and,coincidently, was at the same level on the Sth day, as it continued to plunge. In many waysthese adaptive techniques improve the basic performance of standard trend calculations,but they cannot solve all of the problems.
We begin by looking at techni
Kaufman's Adaptive Moving Average .
Kaufman's Adaptive Moving Average (KAMA),' which began taking form in 1972, is basedon the concept that a noisy market requires a slower trend than one with less noise. That is,the trendline must lag further behind in a relatively noisy market to avoid being penetratedby the price, which would cause a trend change. When prices move consistently in onedirection, any trend speed may be used because there are no false changes of direction. TheKAMA is intended to use the fastest trend possible, based on the smallest calculation periodfor the existing market conditions. It varies the speed of the trend by using an exponentialsmoothing formula, changing the smoothing constant each period. The use of a smoothingconstant was selected because it allows for a full range of trends, compared with the simplemoving average that uses integer values and is limited in the selection of the fast-end speeds(sce the discussion of exponential smoothing in Chapter 4, “Trend Calculations”)
KAMA, = KAMA, . , + Sc, X (Price — KAMA, -1)
where KAMA, is the new adaptive moving average value
KAMA, _., is the previous adaptive moving average value
Price is the current price (for period 1) -
so, is the smoothing constant, calculated each period as follows: .
« see Perry J. Kaufman, Smarter Trading (McGraw-Hill, New York, 1995, Pp. 129-153) for a complete discussion
of this method.
 
ADAPTIVE TREND CALCULATIONS437
sc, = [ER, x (fastest — slowest) + slowest]?andfastest = 2 / (fastest moving average period + 1)slowest = 2 / (slowest moving average period + 1)Iprice, ~ price;_.|
ER, = z=5> price, ~ price; - |
 
The fastest ang slowest values represent the range of periods over which KAMA can vary,erted to its exponential smoothing constant equi i $ca a -quivalent. Nominally, these valare set 9 Zand 30. by squaring the smoothing constant components, ‘the slow endig to stop the Po aval to an exuemely ungesponsive 900-period trend. The effect of thisje trendline when the market bi iother end, when the market i Torn days. the oped ofthe, goes up steadily, without a reversaltrend can reach a very fast 4-period equivalent. wersal for days, the speed of thevane he efficiency ratio, zR hhas more recently been called fractal efficiency. It has the1 e in the same direction for the full 7 periods, and a valwhen prices are unchanged over the » periods. When prices move in wide swings thinthe intews Soe sue OS denominator becomes very large compared with the numera.m: + . 7tos and ER app ler values of ER result in a smaller smoothing constant andIf you choose to use the default values for KAMA, where ER is calculated over 10 peri-
ods-and the smoothing constaious and the smooth ne con nt ranges from 2 to 30 (squared), its calculation can be
KAMA = Kamatt] + ((@absvalue(close-closef101)/summation (@absvalue(close-close[1]),.10)* .6022) + .0645)*2*(close-KAMAL1])
Time Period for ER
I " i
in} Katina s Adapave Moving average, the ume period only afer te caleulstion of te< . ‘0 keep that period, », as small as possibl
uation of a few days will allow the s ad eon thet fo slow and becki f peed of the trend to change fr
again. User's may begin testing in the range of 8to 10 days. fest fo Slow and Pack
Choice of Volatility
r ali -The use of the, volatility fonetion, @summation(@absvalue(close-closef1J,10)) in. ¢ individual price changes rather than looki the hi
low range. Noise is considered i an looking only at the high-1 - more active when prices jump up and di iimportant that prices moved from a particul nia high, but the pattern of, , ; n particular low to a certain high, but the patt
ow it was done. A market in which prices moved from low to high then back to the low
and high again is clearly more volatile and noisier than one that made a single move fromhatil isi fklow to high "
Small Moves in One Direction
Occasional wi i ioccas ons - ty there wil bea series of price moves that progress in very small increments inithout a revers