’s range, while excessive or unfair for today, ischeap to the longer term trader who believes that prices nextweek will be much higher (i.e., today’s price is below next week’santicipated value).Market Profile 483
Eg_eE ean aa
 
Figure B.5 = By combining daily consecutive profile graphics (upper) into alarger cumulative profile graphic (lower), an evolving picture of long termbalance or imbalance emerges. (See explanation on page 489.)
The longer term trader distinguishes between price andvalue by accepting or rejecting current prices away from his per-ception of fair value. Recall that rising prices advertise for sellerswhile falling prices advertise for buyers. When the longer term trad-er responds to an advertised price, this behavior is expected and isreferred to as responsive. On the other hand, if the longer term trad-er did the opposite (i.e., buy after prices rose or sell after pricesdeclined), then this unexpected activity is referred to as initiating.Classifying longer term activity as responsive or initiating relativeto yesterday's or today’s evolving value area provides anecdotal evi-dence of longer term trader confidence. The more confident thetrader becomes, the more likely he is to take initiating action.484 Appendix B
RANGE DEVELOPMENT ANDPROFILE PATTERNS
Since market activity is not arbitrary, it’s not surprising that overtime recognizable price patterns reveal themselves. A skillful trad-er able to anticipate such pattern development in its early stagemay be able to capitalize. Mr. Steidlmayer loosely identifies thefollowing daily range development patterns:
1. A normal day occurs when the longer term trader is rela-tively inactive. The day's range is established in the pioneerrange (defined as the first column of prices) during the ses-sion’s first half-hour period of trade. The short term traderestablishes the initial balance, the unfair high and low, andthen prices rotate between these parameters for balance ofthe day (see Figure B.6: Panel #1—Orange Juice).
2. Anormal variation day occurs when the longer term trad-er is more active and extends the range beyond the initialbalance. In this instance, the short term traders initial bal-ance parameters do not hold and there is some directionalmovement which extends the range and sets a new high ornew low parameter. As a rule, the range extension beyondthe initial balance can be anywhere from a couple of ticksto double the initial balance. This profile type is probablythe most common (see Figure B.6: Panel #2—Dow JonesIndustrial Average).
3. A trend day occurs when the longer term trader extendsthe range successively further. In this instance, the range isconsiderably more than double the initial balance with thelonger term trader controlling direction as the market con-tinues its search for a fair price. Here the market moves inone direction and closes at or near the directional extreme(see Figure B.6: Panel #3—Japanese Yen).
4. A neutral day occurs when the longer term trader extendsthe range after the initial balance in one direction, thenreverses and extends the range in the opposite direction.Neutral days indicate trader uncertainty and occur whenthe market probes or tests for price trend continuation orchange (see Figure B.6: Panel #4—Cattle).Sifters ae
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Figure B.6486 Appendix B
TRACKING LONGER TERMMARKET ACTIVITY
With the exception of option sellers who profit when pricesremain static, the profit strategy of most traders requires direc-tional price movement. The trader wins when he gets the direc-tion right and loses when he is incorrect. Because the longer termtrader is responsible for determining the market’s directionalmovement, we monitor this activity to help detect evidence of aprice trend. After identifying and evaluating longer term traderactivity, an educated conclusion regarding price direction can bereached. We begin the process by identifying the longer term trad-er’s influence in today’s session and then considering how thatinfluence extends into the future.
e Influence in day’s range development: The profile graph-ic helps identify longer term trader behavior during dailyrange development. By monitoring longer term activitythroughout the range, particularly at the extremes, at rangeextension, and after value area completion, we can deter-mine whether longer term buyers or sellers are more activeand hence control market direction. Activity at theextremes provides the clearest indication of longer termtrader influence, followed by range extension and thenvalue area buying and selling.
1. Extremes are formed when the longer term trader com-petes with the short term trader for opportunities at a par-ticular price level (which later becomes either the sessionhigh or low). A minimum of two single prints is requiredto establish an extreme. The more eager the longer termtrader is in this price competition, the more the singleprints and the longer the single print extreme. Anythingless than two prints suggests that the longer term trader isNot very interested in competing at that price. A local topor bottom is formed when only one single print definesthe top or bottom of the range. This condition impliesthat the market offered a price opportunity which no onereally wanted (i.e., no evidence of competition [see FigureB.7: Panel #1—Intel Corporation].Panel #1Intel Corporation
Extreme: formationrequires at least twoTPOs
(a) Selling Extremefrom 77 11/32 to77 5/32
Buying Extremefrom 73 31/32 to75 reveals spiritedcompetitionbetween short termand longer termtraders.
(b)
Figure B.7
Extension
(a)
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(b)
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Range Extension:occurs when longerterm traders upset theinitial balance
(a) Initial Balanceestablished in peri-ods: A & B.
(b) Range extensiondown in periods C,H, andI
: TPO Buying
 
Panel #3S&P S00 Index
Value Area/TPOBuying or Selling:assessment of whetherlonger term buyers orsellers control] the cur-rent session in thevalue area
(a) Modal or FairestPrice at 1039.20
(b) TPO selling countequals 59
(©) TPO buying countequals 100
(d) Imbalance to thebuy side impliesthat prices need togo higher for marketbalance.488
Appendix B
2. Range Extension occurs when the longer term trader
enters the market with enough volume to tip the initialbalance and extend the range up or down. Range exten-sion up indicates longer term buying while range exten-sion down indicates longer term selling. However, thereare occasions when both the longer term buyer and sell-er are active at a range extreme, but not at the same priceand time (recall that longer term buyers and sellers gen-erally do not trade with each other). For example, if anextreme is formed after a range extension up, the marketmoves up first to shut off buying and then moves downto shut off selling. This is an example of both longerterm buyers and sellers trading in the same price areabut at different times. Both kinds of activity at theextremes are identified to evaluate the impact of longerterm buying and selling (see Figure B.7: Panel #2—Coffee).
. The Value Area is determined each trading session by
price rotations around the modal price (i.e., the pricewith the highest TPO count or the fairest price). Thevalue area is computed by counting 70% of all TPOs sur-rounding the fairest price. In other words, the value areais an estimate of fair value which is approximated byone standard deviation of the session’s trading volume(recall the student example earlier). When a longer termtrader makes a trade in the value area, he is buying lowor selling high in relation to a longer term view, not inrelation to today’s value. This behavior creates an imbal-ance in today’s value area. Loriger term trader activity ismeasured by counting TPOs. The following procedurecan be used to determine which side contains the longerterm imbalance, 1) a line is drawn through the fairestprice, and 2) TPOs are counted on either side of thefairest price until a single print is encountered. Theimbalance is assigned to the side with the smaller num-ber of TPOs because the longer term trader activity rep-resents the smaller percentage of total trade in the valuearea. For example, if the TPO count was 22 above and 12Market Profile 489
below the fairest price, that would indicate net TPO sell-ing with a mild bias toward lower prices (see Figure B.7:Panel #3—S&P 500 Index). Note that TPO buying andselling in the value area is not applicable on trend days, asthe market is still in search of a fair value area.
After identifying and evaluating longer term trader activi-ty correctly in today’s profile graphic, the user can readily deter-mine whether longer term buyers or sellers were in control of thecurrent trading session.
e Influence beyond today: The profile graphic also helpsidentify longer term trader behavior beyond today’s rangedevelopment. A key goal of the trader is to determinewhether the current market price trend will continue or islikely to change. A change in market direction is a reversal ofthe current price trend. The standard technical approach totrend assessment, without Market Profile, is to draw anappropriate trendline and monitor subsequent price actionagainst it. Unless the trendline is violated, the current pricetrend is expected to continue. Trendline analysis is the mostimportant of basic technical tools, particularly given its uni-versal usage and applicability to different time intervals (i.e.,hourly, daily, weekly, monthly, etc.).
Market Profile, on the other hand, offers an alternativeapproach to traditional trend analysis by evaluating marketactivity over different time periods. In its simplest form, anevaluation of the profile graphic on consecutive days canhelp define the start or continuation of the short term pricetrend. For example, if today’s value area is higher than yes-terday’s value area, then the current market price trend isup. Moreover, if tomorrow’s value area is higher thantoday’s, then the current market uptrend has continued. Bymonitoring market activity in this fashion, the trader isable to readily identify trend continuation or change.Similarly by combining daily consecutive profile graphicsinto a larger cumulative profile graphic, an evolving pictureof longer term balance or imbalance emerges. The profilegraphic in Figure B.S (Sugar) on page 483 illustrate this490 Appendix B
point. A cursory review of the individual sessions (2/10—2/13) in the upper panel suggest an uptrending marketwithout a hint of reversal. When these four (4) consecutivesessions are combined (lower panel), however, a cumulativebalanced picture springs forth. Once balanced, a marketmoves to a state of imbalance which, more often than not,begins after a final test at the fairest price.
CONCLUSION
The Market Profile method can be used to analyze any price dataseries for which continuous transaction activity is available. Thisincludes listed and unlisted equities, U.S. government notes andbonds (prices or yields), commodity futures and options, whereapplicable. The profile graphic presents the movement of prices,per unit of time, in two dimensions—vertically (i.e., directionally)and horizontally (i.e., frequency of occurrence). When priceaction is viewed in this way, a picture of price discovery unfoldswhich is unavailable in the traditional one dimensional (vertical)bar chart.
The profile graphic offers unique advantages over the stan-dard bar chart:
e The symmetry attribute of the profile graphic allows thetrader to assess the market’s state of balance (or imbalance)in any timeframe. When a market is symmetric, a condi-tion of balance or equilibrium exists between buyers andsellers. A market imbalance implies price trend continua-tion, as the market works toward a new equilibrium.Market balance, however, is fleeting and implies marketchange or a directional move (either up or down) is likely tooccur, a signal for traders to consider employing trend fol-lowing methodologies.
e Every trend change occurs at a single moment in time, notconveniently at the end of the hour, day, week or month.The profile graphic can be used to more accurately identifythat specific time where control changed hands betweenMarket Profile 491
buyers and sellers. By pinning down such control shifts, theprofile graphic allows the trader to identify key support andresistance levels.
In short, the profile graphic provides a substantial amountof price information per unit of time, allowing the trader to iden-tify patterns and dynamics which would not be readily apparentusing other methods.Appendix C: TheEssentials of Building a
cain ei
Trading system development is part art, part science, and partcommon sense. Our goal is not to develop a system that achievesthe highest returns using historical data, but to formulate asound concept that has performed reasonably well in the pastand can be expected to continue to perform reasonably well inthe future.
Ideally, we would prefer an approach that is 100% mechan-ical, increasing the odds that past performance can be replicated inthe future. Mechanical means objective: if 10 people follow thesame rules and achieve the same results, those rules are said to beobjective. It does not matter whether a mechanical system is writ-ten on paper or entered into a computer.
*This appendix was prepared by Fred G. Schutzman.
493494 Appendix C
Here, however, we’ll assume that we are using a comput-er and will use the terms “mechanical” and “computerized”interchangeably. This does not imply that a computer ismandatory for trading system development, although it cer-tainly helps.
The mechanical approach offers us three main benefits:
e We can back test ideas before trading them. A computerallows us to test ideas on historical data rather than on hardearned cash. By helping us see how a system would have per-formed in the past, it allows us to make better decisionswhen it really counts—in the present.
e We can be more objective and less emotional. Most peo-ple have trouble applying their objective analysis to actualtrading situations. Analysis (where we have no money atrisk) is easy, trading (where we have money at risk) is stress-ful. Therefore, why not let the computer pull the trigger forus? It is free of human emotion and will do exactly what wehad instructed it to do at the time when we developed oursystem.
« We can do more work, increasing our opportunities. Amechanical approach takes less time to apply than a sub-jective one, which allows us to cover more markets, trademore systems, and analyze more time frames each day. Thisis especially true for those of us who use a computer, sinceit can work faster and longer than we can, without losingits concentration.
§ STEP PLAN
. Start with a concept
. Turn it into a set of objective rules. Visually check it out on the charts. Formally test it with a computer
. Evaluate the results
aAr WNThe Essentials of Building a Trading System 495
STEP 1: START WITH A CONCEPT(AN IDEA)
Develop your own concepts of how markets work. You can beginby looking at as many charts as you can, trying to identify mov-ing average crossovers, oscillator configurations, price patterns orother pieces of objective evidence which precede major marketmoves. Also attempt to recognize clues that provide advancewarning on moves that are likely to fail. I studied chart after chartafter chart in the hope of finding such answers. This “visual”approach has worked for me, and I highly recommend it.
In addition to studying price charts and reading bookssuch as this one, I suggest you read about trading systems andstudy what others have done. Although no one is going to revealthe “Holy Grail” to you, there is a great deal of useful informa-tion out there. Most importantly, think for yourself. I have foundthat the most profitable ideas are rarely original, but frequentlyour own.
Most of the successful trading systems are trend following.Counter trend systems should not be overlooked, however,because they bring a degree of negative correlation to the table.This means that when one system is making money, the other islosing money, resulting in a smoother equity curve for the twosystems combined, than for either one alone.
Principles of Good Concept Design
Good concepts usually make good sense. If a concept seems towork, but makes little sense, you may be sliding into the realm ofcoincidence, and the odds of this concept continuing to work inthe future diminishes considerably. Your concepts must fit yourpersonality in order to give you the discipline to follow them evenwhen they are losing money (i.e. during periods of drawdown).Your concepts should be straightforward and objective, and iftrend following, should trade with the major trend, let profits runand cut losses short. Most importantly, your concepts must makemoney in the long run (i.e. they must have a positive expectation).496 Appendix C
Designing entries is hard, but designing exits is harder andmore important. Entry logic is fairly straightforward, but exitshave to take various contingencies into account, such as how fastto cut losses or what to do with accumulated profits. I prefer sys-tems that do not reverse automatically—lI like to exit a trade first,before putting on another trade in the opposite direction. Workhard to improve your exits, and your returns will improve relativeto your risk.
Another suggestion—try to optimize as little as possible.Optimization using historical data often leads one to expect unre-alistic returns that cannot be replicated in real trading. Try to usefew parameters and apply the same technique across a number ofdifferent markets. This will improve your chances of long run suc-cess, by reducing the pitfalls of over optimization.
The three main categories of trading systems are:
¢ Trend following. These systems trade in the direction ofthe major trend, buying after the bottom and selling afterthe top. Moving averages and Donchian’s weekly rule arepopular methodologies among money managers.
e Counter trend
~ Support/Resistance. Buy a decline into support; sell arally into resistance.
~ Retracements. Here we buy pullbacks in a bull marketand sell rallies in a bear market. For example, buy a50% pullback of the last advance, but only if the majortrend remains up. The danger of such systems is thatyou never know how far a retracement will go and itbecomes difficult to implement an acceptable exittechnique.
- Oscillators. The idea is to buy when the oscillator isoversold and to sell when it is overbought. If divergencebetween the price series and the oscillator is also pre-sent, a much stronger signal is given. However, it is usu-ally best to wait for some sign of a price reversal beforebuying or selling.The Essentials of Building a Trading System 497
 
e Pattern recognition (visual and statistical). Examplesinclude the highly reliable head and shoulders formation(visual), and seasonal price patterns (statistical).
STEP 2: TURN YOUR IDEA INTO ASET OF OBJECTIVE RULES
This is the most difficult step in our 5 step plan, much more dif-ficult than many of us would at first expect! To complete this stepsuccessfully, we must express our idea in such objective terms that100 people following our rules will all arrive at exactly the sameconclusions.
Determine what our system is supposed to do and how itwill do it. It is with this step that we produce the details neededto accomplish the programming task. We need to take the overallproblem and break it down into more and more detail until wefinalize all the details.
STEP 3: VISUALLY CHECK IT OUTON THE CHARTS
Following the explicit rules we just determined in Step 2, let usvisually check the trading signals that are produced on a pricechart. This is an informal process, meant to achieve two results:first, we want to see whether our idea has been stated properly;and second, before writing complicated computer code, we wantsome proof that the idea is a potentially profitable one.
STEP 4: FORMALLY TEST ITWITH A COMPUTER
Now its time to convert our logic into computer code. For myown work, I use a program called TradeStation®, OmegaResearch, Inc. in Miami, FL. TradeStation is the most compre-498 Appendix C
 
hensive technical analysis software package available for formu-lating and testing trading systems. It brings together everythingfrom the visualization of your idea, to assistance in trading yoursystem in real time.
Writing code in any computer language is no easy task andTradeStation’s EasyLanguage™ is no exception. The job withEasyLanguage, however, is greatly simplified because of the pro-gram’s user friendly editor and the inclusion of many built infunctions and plenty of sample code. See Figure C.1.
Once our program has been written, we then move intothe testing phase. To begin with, we must choose one or moredata series to test. For stock traders this is an easy task. Futurestraders, however, are faced with contracts that expire after a rela-tively short period of time. I like to do my initial testing using acontinuous (spread adjusted) price series popularized by JackSchwager. (Schwager on Futures: Technical Analysis, Wiley, 1996.) Ifthose results look promising, I then move on to actual contracts.
Next, we must decide how much data to use when build-ing our system. I use the entire data series, without saving any forout-of-sample testing (building your system on part of the dataand then testing it on the remaining “unseen” data). Manyexperts would disagree with this approach, but I believe it to bethe best with my methodology that relies on good solid concepts,virtually no optimization, and a testing procedure that covers awide range of parameter sets and markets. I start with a method-ology that I believe to be sound and then test it to either prove ordisprove my theory. I have found that most individuals do thereverse, they test a data series to arrive at a trading system.
I do not account for transaction costs (slippage and com-missions) when testing systems, but instead factor them in at theend. I believe that this keeps the evaluation process more pureand allows my results to remain useful should certain assump-tions change in the future.
I require my systems to work across:
¢ Different sets of parameters. If 1 were considering using a5/20 moving average crossover system, then I would expect6/18, 6/23, 4/21, and 5/19 to also perform reasonably well.If not, I immediately become skeptical of the 5/20 results.staaaaellaeeiielaaeeieiitaeeietaaeeiettaeetaaeelbaaeeleideeielitdeleieteeeeieieeeiaeniiaaa
//fileName: |JMBook.Four%Model/ Written by Fred G. Schutzman, CMT/{Logic by Ned Davis
//see Zweig book: Martin Zweig’s Winning with New IRAs, pages 117-128/{Model was designed to be applied to a weekly chart of the Value Line Composite Index(VLC)//Program uses the weekly (usually Friday) close of the VLC] to initiate trades
//ouy if the weekly close of the VLCI rises 4% or more from its lowest close (since the lastsell signal)
//sell if the weekly close of the VLCI falls 4% or more from its highest close (since the lastbuy signal)//Date last changed: February 8, 1998
eeeeeSystem Properties********
Properties tab:
Pyramid Settings = Do not allow multiple entries in same directionEntry Settings = default values
Max number of bars system will reference = 1
Sn nerH nen rnEHreaHt inne Retain rn eneH inti iaE nani nEaaean tee aaa aE Ia)
Inputs: perOffLo(4.00), { percent off lowest close }PerOffHi(4.00); { percent off highest close }
Variables: LC(0), { lowest close}HC(0), { highest close }trend(0); { 0 = no trades yet, +1 = up, -1 down }
{ initialize variables }
lf currentBar = 1 then beginLC = close;HC = close;trend = 0;
end;
{ update trend variable and place trading orders }if trend = 0 then beginif ((close-LC) / LC) > = (perOffLo / 100) then trend = +1;if (HC-close) / HC) > = (perOffHi / 100) then trend = -1;endelse if trend = +1 and ((HC-close) / HC) > = (perOffHi / 100) then beginsell on close;trend = -1;LC = close;endelse if trend = —1 and ((close-LC) / LC) > = (perOffLo / 100) then beginbuy on close;trend = +1;HC = close;end;
{ update LC & HC variables }If close < LC then LC = close;If close > HC then HC = close;
{ End of Code }
 
Figure C.1  (EasyLanguage Code): This EasyLanguage code was writtenusing TradeStation’s Power Editor™. It has the look—and power—of a fullblown programming language. See Figures C.2 and C.3 for the results on thistrend following system described by Martin Zweig.500 Appendix C
e Different periods of time (e.g. 1990-95 and 1981-86). Asystem that tests well in the Japanese Yen over a recent fiveyear period should also test reasonably well over any otherfive year interval. This is another area where | appear tohold the minority point of view.
e Many different markets. A system that has worked well incrude oil should also work well in heating oil and unlead-ed gasoline over the same period of time. If not, I will lookfor an explanation and will usually discard the system. I goeven further than this, however, and test that same systemacross my entire database of markets, expecting it to per-form well in the majority of them.
Once our testing is complete, let us visually inspect thecomputer generated trading signals on a price chart to ensure thatthe system does what we intended it to do. TradeStation facilitatesthis process by placing buy and sell arrows directly on the chartfor us! If the system does not do what it is supposed to do, weneed to make the necessary corrections to the code and test itagain. Keep in mind that very few ideas will test out profitably,usually less than 5%. And, for one reason or another, most ofthese “successful” ideas will not even be tradable.
STEP 5: EVALUATE RESULTS
Let us try to understand the concept behind our trading system.Does it make sense or is it just a coincidence? Analyze the equitycurve. Can we live through the drawdowns? Evaluate the systemon a trade-by-trade basis. What happens if a signal is a bad one?How quickly does the system exit from losers? How long does itstay with the winners? Make sure we are completely comfortablewith the test results, otherwise we will not be able to trade thissystem in real time.Three key TradeStation statistics to analyze are:
¢ Profit factor. Equals Gross profit on winning trades/Grossloss on losing trades. This statistic tells us how many dol-lars our system made for every $1 it lost, and is a measureThe Essentials of Building a Trading System 501
 
of risk. Long term traders should aim for profit factors of2.00 or higher. Short term traders can accept slightly lowernumbers.
e Avg trade (win & loss). This is our system’s mathematicalexpectation. It should at least be high enough to covertransaction costs (slippage and commissions); otherwise wewill be losing money.
e Max intraday drawdown. This is the biggest drop, in dol-lar terms, from an equity peak to an equity trough. I preferto do this calculation on a percentage basis. I also differen-tiate between drawdowns from a standing start (where I amlosing money from my own pocket) versus drawdowns froman equity peak (where I am giving back profits taken fromthe markets). I am usually more lenient with the latter.
MONEY MANAGEMENT
Money management, while outside the scope of this appendix, isan extremely important topic. It is the key to profitable trading,every bit as important as a good trading system.
Money management techniques should be well thoughtout. Accept the fact that losses are part of the game. Control yourdownside and profits will take care of themselves.
In this area, practice diversification as much as possible.Diversification will enable you to increase your returns while hold-ing your risk constant, or decrease your risk while holding yourreturns constant. Diversify among markets, systems, parameters,and time frames.
CONCLUSION
We have discussed the basic philosophy of trading systems andwhy objective is better than subjective. We covered the three mainbenefits of a computerized approach and designed a 5 step plan forbuilding a trading system. And last, but not least, we touched uponthe importance of money management and diversification.502 Appendix C
Trading systems can improve your performance and helpto make you a successful trader. The reasons for that are clear:
e they force you to do your homework before making a trade
e they provide a disciplined framework, making it easier foryou to follow the rules
e they enable you to increase your level of diversification
With lots of hard work and dedication, anyone can build asuccessful trading system. It is not easy, but it certainly is withinreach. As with most things in life, what you get out of this effortwill be directly related to what you put into it. (See Figures C.2and C.3.)
(VG—--Y) Value Line Geometric - UNDE
 
‘These dots represent the level thal must be equaledOF exceeded on 2 closing basis to issue a reversal signal
 
‘Total Equity (inciuding open poekions}
 
 
 
 
 
 
 
Figure C.2_ (Price Chart): This trading system was designed to be appliedto a weekly chart of the Value Line Composite Index (VLCD, but also testedwell on a daily chart of the VLCI and on both weekly and daily charts inother markets, votes of confidence in the underlying concept. This is the sys-tem described in Figure C.1.The Essentials of Building a Trading System 503
[eae een ae| i aPerformance Summary. All Trades
718.01 Open position P/L 0.001118.18 Gross loss ~400.14
137 Percent profitable 48%87 Number losing trades 70
78.06 Largest losing trade -15.9516.68 Average losing trade 6.722.82 Avg trade(win & loss) §.24
7 Max consec. losers21 Avg # bars in losers
45.012.79 Max # contracts held45.01 Retum on account
 
Figure C.3 (Performance Summary): Here is a 36 year PerformanceSummary of the system shown in Figures C.1 and C.2. Performance over thelast 12