12138965234
1745
9899952995289527952695259524952395229521952095199518951795169515
602 1,90 Sell 344
W145
 
 
 
 
9514
19974229961.3
Total volume 9528-9518
15% of total
374792
Total
56219
15%
Value area (70%) from 9525 to 9520 (inclusive)
R7-10 3429765963
R34-29 SISSS.R71
459 
|
 
)460 PRICE DISTRIBUTION SYSTEMS.
 
ure 18-5 combines CTI 1 with CTI 2 and CTI 3 with CTI 4 to simplify the patterns attrib-uted to each group. During the period shown in the figure, the combined categories 3and 4 cause the market to move when their participation was greater than’ 30%. Obser-vation shows that these trading points occur as prices move out of a previous area of sus-tained trading.
Steidlmayer was said to have first developed this information for his own trading. Hetaught a course on how to apply his evaluation technique, and there were a number ofbooks written on the subject by himself and others.‘ He spent considerable time studyingand classifying formations and separating days into three primary categories: normal,trending, and nontrending. A normal day forms a standard bell-shaped curve with thewidest point, positioned near the center, called the value area. On a trending day, thevalue area is not as wide and appears closer to one end of the distribution. A nontrendingday has neither of the two recognizable patterns.
‘There is an important philosophic basis for Steidimayer’s work. It is a very credibleattempt to explain how the market functions. He says, “The market probes high prices toattract sellers and low prices to attract buyers.” This creates a value area. By observing thepatterns of intraday price distribution, you can know whether there are countertrendOpportunities, when prices reach the extremes of perceived value on a normal day, ortrend positions in the direction of current price movement.
Construction of Market Profile
The Market Profile is created in a manner very similar to a point-and-figure chart. You canlist every price on the left scale or create boxes that represent a price range. This lattertechnique will make the distribution look more uniform by clustering the price activity inexactly the same way as a frequency distribution.
The most common way of plotting intraday data is to begin by placing the letter A inthe boxes alongside the price at which the market traded. If we use half-hour intervals,called time/price opportunities (TPOs), then all prices that were traded during the first halfhour are marked with the letter A. The letter B is used for the second half-hour period, theletter C for the third period, and so on. At the end of the day we have a chart that looks sim-ilar to Figure 18-5. -
Market Profile is also intended to be used over many days, identifying long-term pat-terns as congestion areas or trending markets. To the extent that it accomplishes this dis-tinction it can be very valuable. The ability to determine whether the market is directionalor not is the greatest problem of the trader. In Figure 18-6, the Market Profile is con-structed by using numbers instead of letters to represent the range of prices traded overeach day. The entire chart covers a period of 9 days. Other than the substitution of days forhalf-hour periods, the chart is created in the same way.
‘Time/Price Opportunities
Time/Price Opportunities (TPOs) are the 30-minute blocks assigned letters on the MarketProfite diagram. It is worth noting that the largest occurrence of TPOs at a single price does
“Three books on Market Profile appeared in 1989: J. Peter Steidimayer, Steidimayer on Markets (John Wiley &Sons); Kevin Koy, Markets 101 (MLS Publishing, 401 S. LaSalle St., Chicago, If 60605); and Donald Jones, appli-cations of the Market Projile (CISCO, 32 S. LaSalle St., Chicago, IL 60604). The most complete material, however,comes from the original course taught by SteidImayer, called the Market Logic School. Readers may also want tostudy the original publication, CBOT Market Profile (1984, available from the Chicago Board of Trade); alsoJ. Peter Steidlmayer and Shera Buyer, Taking The Data Forward (Market Logic Inc., Chicago, IL, 1986), andJ. Peter Steidimayer and Kevin Koy, Markets & Market Logic (The Porcupine Press, Chicago, IL, 1986).
 
STEIDLMAYER'S MA:, -T PROFILE 46t
SSFFIGURE 18-6 Daily Market Profile.Value Area Using Daily Data
Price Day Traded
 
 
 
10228}
10224 1210220 12010216 {12010212 -} 12010208 | 24579010204 | 2456790) 36 day counts10200 | 24567910228 | 2345679}10224 | 2345679)10220 2358910216 58910212 58
UESre 2,"Locating value with auction market data,” Technical Analysis of Stocks & Commodities
 
Source: Jones,uly 1989)
not necessarily correspond to the price at which the highest volume occurred, as seen byreferring back to Figure 18-5. This distinction is at the root of Market Profile, because itemphasizes the amount of time that traders accepted a price, rather than the volumetraded at that price, which could have occurred during a single period. In the bond exam-ple given in Figure 18-5, the greatest volume was transacted at 9520, although the centerof the value area, where there is the largest record of TPOs, is at 9523, three points higher.
Clearly, the Market Profile analysis is seeking out a different way of observing the actionsof traders. In the formation of a value area, if the market moves between two prices, suchas 9520 and 9523, because those values bracket the current trading range, each traversewill cause the prices in between to be marked with the same TPO letter, regardless ofwhether any volume occurred at those prices.
‘TPOs allow us to judge the potential direction for a move out of the current value area.This can tell a trader to buy strength or sell weakness. The market is said to favor the direc-tion indicated by the upper or lower part of the value area that has the highest TPO count.‘When performing the TPO count, you must have a well-defined value area and limit thecount to within that range. Using Figure 18-5, with the mode at 9523, count the TPOs priorto the interval that begins J. There were 16 TPOs above 9523 and 21 below (not including8§ and 3Z). During time intervalJ, the balance shifted to the upside when it touched 9529,at which point there was a large increase in volume. This could be attributed to CTI 1 andCTI 2 exiting shorts and, to a lesser degree, going long. The locals were finally joined bygroups 3 and 4, taking a long position at 9600. An imbalance in the TPO count expresses awillingness for the market to favor the direction given by the largest count, but applies toa normally distributed value area only.
Typical Patterns
It is generally accepted that the ma:ket spends the greatest time in a sideways, or conges-tion area, and a relatively small amount of time trending. The sideways period may bedefined as an extended timelprice relationship and the trending period as a brieftimelprice relationship. The extended period creates a value area where traders are wi
  
 
 
462 PRIVE DISTRIBUTION SYSTEMS.
ing to buy and sell, and this activity is reflected in higher volume. According to MarketProfile,
Value = price x time = volume
In this analysis, called auction theory, the value area is the place that the market is willingto trade, and is seen in the time value. The value area represents about 70% of the marketvolume. The center of this time value area is the price at which there are the most TPOs.Because market activity spends at least 80% of the time in this value area, prices tend torotate about the center. Rotation is the term given to price action that moves back andforth above and below this central value, building the pattern of normal distribution simi-lar to a bell-shaped curve.
What Are the Buyers and Sellers Doing?
‘The interpretation of the Market Profile is based on the concept that, under normal marketconditions, prices rise to attract sellers and fall to attract buyers. There is a very active area oftrading at 2 point called equilibrium where commercial buyers and sellers exchange freely,because they consider the price at value (Figure 18-7, panel a). If there are more buyers thansellers, the price rises to attract additional sellers who feel as though they are getting a pricethat is above value. However, as prices continue to rise there are fewer buyers, bécause theyperceive the market as overpriced. In Figure 18-7, Day 1 (panel 6) shows a buyer's curve anda seller's curve drawn on the frequency distribution of a normal trading day
In this way the market is said to facilitate trade. When there are not enough buyers,the price falls; when the sellers are scarce, prices rise. Constructing the buyer's and seller'scurves for a sequence of days can help understand the dynamics of trading in terms of bothprice expectations and volume. For convenience, the curves will be shown as straight lines,similar to supply and demand lines, in the following examples.
On Day 2 in Figure 18-7 (panel c), the buyérs disappear faster than the sellers; therefore,the buyer's curve is more horizontal and the seller's curve more vertical. On Day 2 (panel ¢),the sellers have held their position and the buyers are willing to move higher, retreating fromtheir previous objective. This results in higher volume. Had the buyers moved lower and the
__ sellers remained steady, the volume would be expected to decline. lf on Day 2 (panel 4) the
volume increased while prices traded in the same-range and at about the same peak priceevel (value level), the buyer's and seller's curves would have become more horizontal, indi-cating that both sides of the trade were holding firmly at the current level.
Quantifying the Value Area
The idea of a value area that is shaped as a bell curve, or an extended formation to repre-sent a trending day, seems clear; unfortunately, patterns are rarely as clear as these exam-ples. To help this process, Jones has applied overlays to these patterns, using a standarddeviation to measure them. In Chapter 2, we explained that, for a normal distribution, thevalue of 1 standard deviation represents a clustering of 68% of all values around the mean;therefore, 34% are on either side. Similarly, 2 standard deviations contain 95% of all activ-ity, 42.5% on either side of center. In his analysis, Jones has defined a value area as one con-tained within 2 standard deviations of the center using the TPO count to isolate the range.For example, if the entire chart contains-100 filled boxes, the price range is from 6615 to6655, the center is right at 6635 and contains 10 filled boxes, then 2 standard deviationscontain 90 x .425 = 38 boxes on each.side of the center. This defines the value area.
5 Donald L-Jones, “Locating value with auction market data,” Technical Analysis of Stocks & Commodities (uly1989).
6 The following discussion is based on Robert Pisani, “How market structure helps you analyze price behavior,”Futures (October 1987).
 
 
STEIDLMAYER'S MARncT PROFILE 463
 
 
FIGURE 18-7 Buyer's and seller’s curves for a sequence of days.
(No buyers) 63
         
    
 
          
Buyer's curve1S Buyer's curve608 Point of equilibrium 59a (at value)5857 ‘Seller's curve56(No sellers) 65(a) Theoretical buyer's and seller's curve (b) Day 163 63 ‘eat 6261 ~S 6 Seller's day 160 ~ Buyer's day 2 60 _Solers day 259 59 S3ecVotume day 2
- ~ Buyer's day 2
Buyer's day 1 /Buyer's day 1
58
 
57 8756 5655 55(¢) Day2 (d) Day 2Volume shifts, Both buyers and sellers hold firm,
sellers remain firm, buyers retreat volume increases at same point
 
Trending Markets
‘Trends spread volume out over price and are relatively easy to see. In the previous discus-sions, there is an early warning of a trerid when prices move out of the value area or whenthere is a larger number of TPOs on one side of the center of the value area. Trends developwhen the market attempts to probe a new price level causing the current price to divergefrom the value area. The participants may reject this divergence and the price will return tothe previous area causing a broadening formation, or they may accepé the new price as fairvalue and generate a new value area by attracting volume (see Figure 18-8). The initial movethat fails to find a new value area is called price trend; it usually begins and ends within a sin-gle time period (one TPO, which could be a half hour or a day). A price move that attracts vol-ume over a longer time period is called a value trend. Daily charts, or a sequence of intraday30-minute charts, are easier to use than a single 30-minute chart when looking fora trend. -
When comparing the Market Profile of successive days, it is helpful to watch the activ-ity of the recent day compared with the value area of the previous day. When trading within 
 
464 PRICE DISTRIBUTION SYSTEMSFIGURE 18-8 Market Profite for a trending market.Beginning of a TrendPrice Day Traded
 
1022810224 1210220 120A10216 120A10212 120AB
10208 245790AB10204 2456790ABC.10200 245679ABC10228 2345679ABC10224 234567910220 23589C
10216 589C
10212 58C
10208 CD Breakout at 10208
10204 CD
10200 DEH .
10128 DEGH Consolidation or new10124 DEGH) value area being formed10120 DEGI, around center of 1012410116 DEF
fo2 Fl
1olo8Fee ULE EEE!
the previous value area, both buyers and sellers are considered equal. A move above thevalue area is considered as motivated by the buyer and reactive by the seller, and tradingbelow the prior value is initiated by the seller and reactive by the buyer.
Trends do not move in a fast, straight line to their correct new level, instead, they movein steps, pausing to test whether a new value area can be formed that facilitates price. Thetrend continues in this way until prices retrace to the previous consolidation area, wherethe TPO volume is expanded and the area is broadened, resulting in a value area.
Some Points to Remember about Market Profile
One great advantage of using the TPO count, rather than traditional volume, is that theMarket Profile can be created at any time on any market. All the-necessary information isavailable. The method is very different from traditional trending approaches and offersinsight into the current status of price action, whether it is in a consolidation phase ortrending. Although the evaluation of Market Profile has been very interpretive, there have.been important steps toward defining value areas and trends in a more objective way.Using the overlay method proposed by Jones, a very simple trend filter could be con-structed so that new trend trades, based on traditional Moving averages, are not set untilprices move out of the value area. During the past few years, there seems to be less inter-est in this technique; however, its underlying simplicity and clear distinction betweenother methods of analysis should keep its standing as a tool worth studying.
 
| 19
Multiple Time Frames
 
decades, few professionals have talked about it. It is only since better quote equip-ment has allowed this technique to be accessed by a wider audience that thisapproach has begun to appear in the public domain, The combination of multiple time peri-ods allows the trader to time entries into the market using very short-term data, such as 10-minute bars, while watching the longer-term picture for the daily or weekly trend. Becauseit is agreed that most trends are best identified over a longer time period, while choosingthe entry point requires a much faster response, the combination of two, or even three timeintervals is very sensible. If the trend can be identified profitably, then the trader can filteror select short-term trades that have a better-than-average chance of becoming winners.For most traders, the use of any one time frame presents special problems. The veryshort term contains a high percentage of noise and obscures the market direction. Theattempt to isolate patterns within charts of 5-minute bars can divert your efforts away fromthe big picture. Use of only weekly charts, although they clearly show the direction ofprices, present higher risk and little opportunity for a good entry point. The obvious solu-tion is to combine both charts into a program that uses each to its best advantage.
A Ithough the use of multiple time periods for analyzing markets has been popular for
TUNING TWO TIME FRAMES TO WORK TOGETHER
Throughout most of this book, the individual systems and methods have been discussedfor their own merits. An analyst would look for the specific RSI or stochastic that somehowgenerated the most profits by showing a trend change or an overboughvoversold condi-tion. That is not the optimal use of an indicator when it is expected to tell you the best timeto enter a trend. Instead, you will want the time period for the indicator to be muchshorter than the time period used to calculate the trend. For example, if your trend systemhas a typical holding period of 1 month (about 23 business days), you may want your tim-ing oscillator to have a good chance of giving you a better entry point within the first 5 days(20%) of that trade.
To get an indicator to reach overbought and oversold levels an average of every 5 days,you will need to use less than 5 days to calculate the indicator value. It doesn’t matter if theindicator returns a loss when the results of all its buys and sells are totaled, because theprofitable part of the program comes from the longer-term trend component. It is mostlikely that the oscillator will generate five overbought or oversold conditions during thetypical holding period for the trend trade, but only one of them will be used—the first oneafter the new entry signal. It is-only important to see how the timing helps to improve over-all profits and risk.
Figure 19-1 gives a TradeStation program that uses two time frames, a shorter onecalled datal and a longer one, data2. These could be daily and weekly, hourly and daily, orany combination pf shorter and longer time frames. The shorter one is used to calculate a~fast stochastic (actually %K-slow); and the longer interval applies to the weekly data. Thisuse of multiple time frames is at the root of the techniques in this chapter. 
466 MULTIPLE TIME FRAMES
FIGURE 19-1 Program combining daily stochastic with weekly trend,
[Multiple time periods : Linear Regression Slope + Stochastic!
(period = length of exponential trenddatal = shorter time period of stochasticGata? - longer time period of linear regression slope!
input: fast(S), stow(50);vars: slope(0), overbot(80), oversold(20), stoch(0);
(calculate stochastic over shorter data period}stoch = @slowk(fast) of datal;
{Linear regression slope}slope = LinearRegSlope(close of data2,slow);
if slope > 0 then exitshort on close;yf slope < 0 then exitlong on close;
(Yong signal : slope must be up and stochastic below jow threshhold)jf slope > 0 and stoch < oversold then buy on close;
[short signal : slope must be down and stochastic above upper thresnhold)if slope <0 and stoch > overbot then sell on close:
i aa
ELDER’S TRIPLE-SCREEN TRADING SYSTEM!
The Triple-Screen method combines three time frames to remove the disadvantages of eachone. It combines indicators that are both trend-following with oscillators (normally associ-ated with a countertrend direction). Dr. Elder has observed that each time frame relates tothe next by a factor of 5. That is, if you are using daily data as the middle time period, thenthe shorter interval will be divided into five parts, and the longer period will be 5 days, or1 week.
To be practical, it is not necessary to divide a 6-hour trading day into five intervals of 1hour and 12 minutes. Rounding to 1 hour is close enough. If, for example,-you want tofocus on trading a 10-minute chart, then the middle interval is 10 minutes, the short-termis 2 minutes, and the long-term is 1 hour (not 50 minutes).
In the following description, screen 1 holds the longest time frame while screen 3
shows the shortest one.
Screen |: The Major Movement
‘The long-term view gives the market tide, a clear perspective of the major market trend,or sometimes lack of trend. Weekly data is used for this example, which is consistent withmost experience that less frequent data (i.e., weekly or monthly) smooths the pricetnovement by eliminating interim noise. Although there are many other choices for along-term trend, the Triple-Screen approach uses the slope of the weekly MACD, wherethe histogram that represents the MACD value is very smooth, equivalent to, for example,a 13-week exponential smoothing. The trend is up when the MACD bar, or 13-weekexponential value is higher than that of the previous week; the trend is down when this
week's value is lower.
+ From Dr, Alexander Elder, Trading for a Living Gohn Wiley & Sons, 1993).
 
ELDER’S TRIPLE-SCREEN TRADING SYSTEMScreen 2: The Intermediate Movement ~
Sing an oscillator, the Screen 2 identifies the time which we /. . tifies i iUs the S Zid hi Period in which we would trade. Again,the specific oscillator is not as important as the time frame and the ability to identify varet waves in the major movement of Screen 1 Two oscillators are suggested, the Force, ,Index and Elder-ray, both described below. A stochastic can also be used.
Force Index =ex = volume (today) x [close(today) ~ close(yesterday)]using a 2-day exponential smoothing, which has
a smoothing constant of .333, and the resul ting value is used to determine the over-ine the over-
bought and oversold levels,
Entering a long position using the Force Index i
Elder-ray;ider-ray, however is not as clear as when using the
the following ste|ps-are necessary:sep 1. The trend in Screen 1 is up.tep 2. The 2-day ex i 1ponential of22. The Peday exponential o the Force Index falls below its centerline and
Force Index, bu: eek low. When usin ibuy when an low. Wh ig a stochastic inst2. Elders, e stochastic falls below 30. ‘ead of the
The Elder-ray is a technique for separating bullish and bearish movement.
Bull =tll power = high ~ 13-day exponential smoothing
Bear =Power = low — 13-day exponential smoothing
To determine when to buy using
are necessary: the Elder-ray and Screen 1, the following two steps
Step 1. The trend in Screen 1 is up.
Step 2. Bear power is negative but rising: bear ower must not be positive.gati «oe
2 ig; bear pe it
.
Two addi ional steps may be used to filt
er trades and improve performance, but areStep 3. The last ipeak in bull power is hiSep 3. The is higher than the previrecent power should not be significantly lower than the proners nent_ Step 4. Bear power is rising from a bullish divergence Prowse.€ opposite rules apply for sell signals. ,
Screen 3: Timing
The final screen is for fastest res)
improve the point of entry, Scre posse, primarily for identifying intraday breakouts. To
<a 3 can be used to set lon}ay’s high. There is no calculation involved,
 
Stop-Loss
Every system ni ieds risk control,Tripie-sereen ontrol, and that most often‘ep I. First, place the stop bel : HE Position,whichever is lower. P below the low of the day of entry, or the previous day’s low, 
 
Step 2. Move the stop tO the break-even level as soon as pos ible. Naturally, there musthe some room between the stop-loss level and the current price; otherwise, the stopwill always be hit. .
Step 3. Move the stop to protect 50% of the highest profits. In addition, you may con-sider taking profits when the stochastic or Force Index moves above the 70% level.
ROBERT KRAUSZ’S MULTIPLE TIME FRAMES
Although multiple time frame techniques have become more visible, the most robustapproach has been taken by Robert Krausz. To understand the importance of first arriving,ape sound theory before implementing and testing a trading program, We need to brieflyreview the characteristics of performance that indicate a robust method.
‘When testing a trend-following system, we should expect that a trend of 100 days,compared with a trend of 50 days, will produce larger profits per trade, greater reliability,and proportionally fewer trades. As you increase the calculation period, this pattern con-tinues; when you reduce the calculation period this pattern reverses. You are preventedfrom using very short calculation intervals because slippage and commissions become toolarge; the longest periods are undesirable because of large equity swings: There must be aclear, profitable pattern when plotting returns per trade versus the average holding period.
THe sophistication in Krausz's work fies in his understanding of this pattern, and itsincorporation into the structure of his program, The Fibonacci Trader.* Krausz works inthree time frames rather than two. Each time frame has a logical purpose and is said to bemodeled after Gann’s concept that the markets are essentially geometric. The shortest timeframe is the one in which you will trade; in addition, there are two longer time frames toput each one into proper perspective. The patterns common to time frames are easily com-pared with fractals; within each time frame is ‘another time frame with very similar patterns,reacting in much the same way. You cannot have an hourly chart without a 15-minute chart,because the longer time period is composed of shorter periods; and, if the geometry holds,then characteristics that work in one time frame, such as support and resistance, shouldwork in shorter and longer time frames. ‘Within each time frame there are unique levelsof support and resistance; when they converge, the chance of success is increased. InKrausz’s work, the relationships between price levels and profit targets are woven withFibonacci ratios and the prin« iples of Gann. xX
‘One primary advantage of using multiple time frames is that you can see a patterndevelop sooner. A trend that appears on a weekly chart could have been seen first on the dailychart, The same logic follows for other chart formations. Similarly, the application of patterns,
such as support and resistance, is the same within each time frame. When a support lineappears at about the same price level in hourly, daily, and weekly charts, it gains importance.
‘As a well-known trader, Krausz brings more than just three time frames and someunique strategies to one display screen. He endows the program with six rules:
Laws of Multiple Time Frames*
1. Every time frame has its own structure. .
2. The higher time frames overrule the lower time frames.
3. Prices in the lower time frame structure tend to respect the energy points of thehigher time frame structure.
2 Robect Krausz, WD. Gann Treasure Discovered (Geometric Traders Instirurés ‘757 SE 17th Street, Suite 272, Fe.Lauderdale, FL 33316). Also sce references in the section “Fibonacci ‘and Human Behavior,” Chapter 14.
3 See Jack Schwager, The New Market Wizards ohn Wiley & Sons, New York, NY, 1992).4 Copyright, Robert Krausz.
 
ROBERT KRAUSZ’S MULTIPLE TIME FRAMES469
4. The energy points of su: iC pport/resistance created by the higher time frame’(prices) can be validated by the action of the lower ene periods frame's vibration
5. The trend created i imre by the next time period enables us to define the tradable
6. What appear: i ime period can bes to be chaos in one time peri i« i i order in another time
and See a aes frames of about the same ratio to one another (10-minute, 50-minute,and daily), w ally being the longest, Figure 19-2 shows the June 98 contract of U.S.number of techniques applied over multiple time frames. Figure 19:2a uses
a ile Figure 19-2 -only daily bars, while Figure 19-26 has 10-minute bars, both charts drawn on the samefacili ‘ fe bars,
 
FIGURE 19-2 Krausz’s multiple time frames, Jun 98 U.S. bonds. (a) Daily chart with Gann
swings and a stepped movin; iple tisevings and » ste pred g average. (b) Multiple time frame structure for the
 
 
    
 
 
 
 
 
 
 
 
 
 
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Source: Chart created usin iig The Fibonacci Trader. Used with permissi. i\ I permission from Fib. i757 SE \7th Street, Suite 272, Ft Lauderdale, FL 33316. nmwftbonacciradencom Taer Corporation 
 
470 MULTIPLE TIME FRAMES
To understand the application of these techniques, it is necessary to identify the fol-
lowing features: :
1. The Daily Hilo Activator (in this case, it is the moving average of the daily highs