5
FIGURE 12.6 Fibonacci time targets. Fibonacci ratios are used to find turning points inthe trend by projecting the distance between two clear price peaks forward 1.618 percent of thedistance between the two previous peaks.
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As an example, suppose that the “Q’s” (the Nasdaq QQQ) peaked at 1250on March 30, declined and then peaked again at 1240 on June 30, 91 dayslater. The most likely time for another peak or valley (we can’t tell you whichwill occur, only that it will be a turning point) will be 147 days after the lastpeak (91 × 1.618 = 147), on or about October 26. If prices have been in anuptrend prior to October 26, we can expect that date to be a top; if it is in adowntrend, we can expect a bottom. If prices were drifting sideways aheadof October 26, then nothing is expected.Figure 12.6 shows a number of different time targets calculated fromhighs (marked with letters) and lows (marked with numbers). The ratios .382and .618 are used, although .618 is most popular.To get our time targets, we normally measure the distance between thehighs and multiply by .382, .618, or 1.618 to get the projection for the nexthigh or low. We can do the same using the lows, but the highs are consideredmore important. The location of the low may not be as clear.If you are thinking about trying all of the major ratios, 100, 61.8, 50, and38.2, you will get a lot of targets. Prices are likely to turn within a day or twoof one of them, simply because there are so many. To prove a theory, use onlythe most important scenarios.
W.D. GANN—TIME AND SPACEBoth W.D. Gann and R.N. Elliott are extremely popular with technical analysts. Both formed their trading approaches by the mid-1930s. Gann published individual, small studies of market movement; Elliott’s book The WavePrinciple was published in 1938.Gann has contributed a variety of retracement theories and price targetsto the literature. His philosophy was “Conserve your capital and wait for theright time.” It is important to remember that Gann believed in seasonality,and all his work applies to commodities markets. However, there are interesting universal concepts:1. Traders like whole numbers. There are more orders clustered at 5 and
10¢ points than at values in between. There are more orders at $.50 and$1.00 than at 5 and 10¢.2. Natural price divisions for support and resistance are most often 0 per-
cent and 100 percent. After that, 50 percent, 25 percent, and 12.5 percentare most important, in that order.
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2x1
1x11x21x3
1x4
0xn
FIGURE 12.7
Gann’s geometric angles. Using graph paper,Gann decided that the most important support levels were thoseformed by drawing lines through the corners of the boxes. Theseare also called fan lines.
3. Geometric angles form support levels. Using square graph paper for your
chart, lines are drawn upward to the right through the corners (1 × 1angle) to create 45° support lines. Steeper angles are drawn throughthe corners of multiple boxes 1 × 2, 1 × 3, . . . , and lower angles are 2 × 1,3 × 1, . . . , and 1 × 0. When shown together, these support lines are calledfan lines (see Figure 12.7).
Gann Squares and HexagonsGann had an interesting way of finding price targets that included an impliedvolatility calculation. Using soybeans, he began with the lowest recordedcash price of 44¢ per bushel and placed that in the center of the square. Hethen added 1¢, moving first to the right, then up and counterclockwise untilhe included all prices at which soybeans have traded. This method, called thesquaring of price and time, is based on the cardinal square. It can be seenin Figure 12.8.The two diagonal lines passing through the center of the chart, as wellas the vertical and horizontal lines through the center, are the prices thatGann used to forecast major support and resistance levels. You should notethat, as the square gets larger, the prices along the diagonal, horizontal,and vertical lines get farther apart. For example, along the vertical beginningat the center, we read 4, 47, 58, 77, 104, 139, 182, 233, 292, 359, and 434, representing percentage increases of 6.8, 23.4, 32.7, 35.0, 33.6, 30.9, 28.0, 25.3,22.9, and 20.9. Based on what we know now, we would expect the volatility
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FIGURE 12.8
Gann’s square. Starting from the lowest traded price, Gann moved rightand then up in a counterclockwise direction, creating a price square. Key levels of supportand resistance are expected to fall on the horizontal, vertical, and diagonal lines. The pricechange between the levels in the square shows the increase in volatility relative to price.(With permission from Figure 14.19, p. 369. P.J. Kaufman, Trading Systems and Methods,3rd edition. New York, John Wiley, 1998.)
of prices to keep at an equal percentage, or increase slightly. Considering thiswas done in the 1940s, it’s pretty good.We could speculate that that Gann created the square by first writingdown the key resistance levels, and then working out the geometric patternthat would cause these levels to fall on a diagonal, vertical, or horizontal.Gann also used the hexagon for other markets, which might give us a fewmoments of doubt.
Retracements, Reversals, Fibonacci Numbers, and Gann
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AFTERTHOUGHTMany traders perform best when they have a system to watch, even whenthey don’t follow it rigidly. A system provides a valuable structure for traders.It can serve as a guide to avoiding stupid decisions, such as holding a tradetoo long that fights with the trend. For example, you may be watching abreakout system and get a buy signal as prices jump through a key resistancelevel. Rather than buy immediately and guarantee a horrible fill, you wait forthe fast move to end and prices to pull back before buying. You’re not trading against the trend, just using common sense to improve your entry.Many traders perform well by knowing the trend and knowing where thesystem entered the trade. They have a knack for doing better. In the long run,this type of trading will not do as well as the system when prices are running.That is, in a very trending market, getting into a trade quickly gives the higherprofits. When the trends aren’t as clear, during a noisier market, waiting fora better price will be a more profitable strategy.In the final analysis, trading around a trend system does worse during atrending market and better in a sideways market. It smoothes out performance and ends up being very close to the same net profit.
Questions1. What are the three most likely percentage retracement levels?2. What significance would you put on a 100 percent retracement?3. Write the first 6 numbers of the Fibonacci summation series.4. In the Fibonacci summation series, for large numbers in the series, what
is the ratio of the Nth value to the previous value?5. If prices moved from a low of $35 to a high of $55, then retraced to $45,
and started to move higher, a Fibonacci ratio of .618 would tell you toexpect prices to reach what level?6. If a high occurred on December 4, a low 20 days later, and another high
15 days after the low, in how many days would you expect a new high orlow according to the Fibonacci ratio .618?7. In a Gann square, the key support and resistance levels are supposed to
fall where?8. As you move outward in Gann’s square or hexagon, the various support
and resistance levels represent (a) an increase in (b) unchanged, or (c) adecrease in volatility?
C H A P T E R 13
Volume, Breadth,and Open Interest
rice change is the most important indication of what is happening toa stock, index, or commodity. When price goes up, there is moredemand or less supply. We spend a lot of time looking at a price pattern, drawing or calculating trendlines, and turning the chart upside down tosee if we’ve exhausted every combination.Adding volume to the picture introduces an entirely new dimension. Volume has nothing to do with price. It tells you about the extent of participationin the day’s price change. If we think about it in extremes, we would have lessconfidence in a move up if only one person was buying than if 1 millioninvestors were buying. By adding volume to our trading decision, we can addimportant reliability.Chart patterns are more dependable when price movement is the resultof broad participation. We will extend this same principle to market breadthand to futures market open interest.
P
THE BASIC PRINCIPLES OF VOLUMEThe standard interpretation of volume has been part of the trading culturefrom its beginning. Volume is always considered in combination with pricemovement:Volume
Price
RisingRisingFallingFalling
RisingFallingRisingFalling
Interpretation
Volume confirms price riseVolume confirms price dropVolume indicates weak rallyVolume indicates weak pullback
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FIGURE 13.1
Amazon price and volume chart. At the beginning of the bull market inAmazon, volume sharply increased along with prices. After the first peak, volume clearly droppedand continued to drop on the second peak. It wasn’t until June 2000 that volume started to riseagain, confirming a downtrend although with less participation.
Therefore, volume confirms direction. When volume declines, it indicatesthat a change of direction should follow.Amazon.com gives a good example of the bigger picture of volume. InFigure 13.1 we can see the sharp increase in volume in May 1998 just aheadof the major upward move in Amazon prices. At the beginning of 1999 pricesmake their first peak on high volume, but then volume starts to fall sharply.When prices make their second peak in April 1999, volume is much lower.Higher prices and falling volume are considered signs of a weak rally, andprices again drop sharply. When the third peak occurs in December 1999, volume is even lower. A major decline follows. Fewer and fewer investors andtraders were willing to participate in the second and third attempts to pushAmazon prices higher. It’s important information that can be applied to fastertrading as well.
The Problem with VolumeBefore we get too far into the merits of using volume, let’s address its problems so that we can watch for pitfalls along the way.
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What do you do if there is a very small increase or decrease in volume?You treat it as any other increase or decrease in volume. The amountdoesn’t seem to matter.What if the price is unchanged? You continue using your analysis from theprevious day.What if price moves up by just 1 point? It still seems best to apply thebasic rules. Any higher close is important. Ignoring the day doesn’t workas well.What if volume is erratic from day to day? Volume can vary a lot from dayto day. You can choose to use it just the way it is, or you can smooth thevolume with a three-day moving average just to be sure that you’re notfooled by one low volume day between two strong days. With certainanalysis you can also limit your use of volume to extreme changes, veryhigh volume days, or large drops in volume. We’ll discuss this more later.With all of these problems, volume is still important. You need to find thebest way to use it rather than find an excuse for not using it.
Volume Is a Predictor of VolatilityMost often high volume and high volatility occur at the same time. It’s easyto see that one confirms the other. Sometimes volume can be high, and theprice can end nearly unchanged for the day. We need to look at that day asa sign of potential volatility—a lot of traders with opposing opinions justhappen to offset each other. Tomorrow, if there is an imbalance in the buysand sells, prices could explode in either direction. Therefore, high volumemeans high risk.
More Examples of Volume InterpretationMicrosoft. Using volume becomes clear when you look at more examples. In Figure 13.2 there are periods in Microsoft where the price madesignificant moves and where volume spiked or dropped sharply. The firstexample is in December 1999, where we get a sharp rally from about $90 to$120. Volume triples just ahead of the rally and then starts to drop as theprice rise continues. As prices round out at the top, we can see volume dropsharply into the holiday season. Volume then starts to increase as pricesdecline. Happy New Year! It will be a long time before Microsoft sees thatprice again.
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Rally onhigh vol
Drop in volumeafter peak
Suddendropin volat peak
Drop involume
Steady increase in volumeduring decline and testof highs
Dropin volume
FIGURE 13.2
Examples of price and volume for Microsoft. The first pattern of risingprice and volume followed by a sharp drop in volume is a classic case, as are the two drops involume at the far right. The middle pattern is not as clear. You shouldn’t force an interpretation.
There are two other clear examples at the right of the chart, where volume dropped at the end of a downtrend and during the following uptrend.The case in the middle is not as clear, but can be interpreted after the fact.Volume increases toward the end of the downtrend, but seems to continue toincrease through the next rally. Some of you may find this pattern consistentwith the rules and others may not. Volume doesn’t solve all problems.AOL. The AOL chart in Figure 13.3 is typical of the erratic pattern of volume that is difficult to interpret. Although there is an underlying decline involume from late April through September of 1999, there are continual volume spikes that identify local tops and bottoms (mostly bottoms). Whenprices finally start back up in October of 1999, volume still seems to declinesteadily. We know now that AOL was destined to see much lower prices, butvolume would tell you that the move from $40 to $95 was a weak rally andshould be avoided. You might find that being right in the long run but missing a big move is an unsatisfying experience. Fortunately, there are a lot ofother stocks from which to choose so that your capital doesn’t sit idle.
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FIGURE 13.3
AOL price and volume example. Although erratic, volume delines steadilyafter the first price peak. Unfortunately, volume also declines on the second rally from $40 to$95, suggesting a weak rally. In the long run that was true, but making the decision to standaside might not be easy.
VOLUME SPIKESMadness is the exception in individuals but the rule in groups—Nietzsche*A volume spike is just what you would expect, a single day on which the volume was much higher than the previous day—at least twice as high, perhaps3 or 4 times as high.A volume spike means that everyone has jumped into the boat at thesame time. Experienced traders will tell you that when the public jumps in,it’s time to get out.You can see volume spikes on the three charts that we’ve already studied.Let’s look again at the last one, AOL. We see the highest volume days in April,August, and September 1999, and in January 2000. What is common about
*Quoted by Donald Cassidy, Trading on Volume, New York, (McGraw-Hill, 2001).
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these spikes? They occur at the bottom of a price move. After a spike, pricesreverse. In Figure 13.2 spikes occur at both tops and bottoms.A spike doesn’t tell you how long or how severe the following reversalwill be. It just tells you that the current move is exhausted. It may turn out tobe a major top or bottom, or simply a local turning point.Volume spikes are a good example of extremes. It is easier to identify andtrade an extreme. If you start to spend a lot of time trying to decide if volumeis confirming or rejecting a price move, then it’s not clear enough to trade.Put it aside and try to find another stock or another way to make the trade.The theory of a spike is that when everyone has entered the market, thereis no one left to buy (or sell) and prices must reverse. The crowd is alwayswrong—at least their timing is always wrong.
VOLUME INDICATORSThere have been many attempts to clear up the erratic behavior of volumeand create a clinical “signal” of when volume is confirming or rejecting theprice move. Most of this involves some smoothing of the numbers and seemssensible. A few of these methods have been very popular.
Volume OscillatorVisualizing the pattern of volume can be very helpful, and the simplest way todo this is with a volume oscillator. A volume oscillator is a two-step process:1. Calculate the 14-day moving average and the 34-day moving average of
volume.2. Plot the difference between the 14-day and 34-day averages.
Looking at the Microsoft chart in Figure 13.4 from mid-January 2000through the end of March 2000, we see an increase in volume as prices drop,and then a clear drop in volume when prices begin to rally in mid-March. Asprices reached their peak at the end of March, the volume oscillator hadfallen to near zero.
On-Balance VolumeBy far, the most well-known of all volume indicators is On-Balance Volume(OBV), made famous by Granville. It is simply the accumulated volume,where volume is added when prices rise and subtracted when prices fall:
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FIGURE 13.4 A volume oscillator. Using the difference between a 14- and 34-day averageof volume, the volume oscillator is a good visual representation of the increases and decreasesin volume. From February through May 2000 volume favored the downside. A sharp decrease involume at the end of May signaled the end of the downtrend.
If today’s price change > 0, then OBV = OBV + today’s volumeIf today’s price change < 0, then OBV = OBV − today’s volumeOnce we have created the OBV line, we interpret the OBV to make tradingdecisions instead of using the price. In Figure 13.5 the OBV is plotted alongwith the volume at the bottom of the chart. You’ll notice that it looks verymuch like the price chart rather than the volume chart, even though it iscreated from volume. The obvious difference between the price chart andthe OBV line is that the peak is shifted from the end of 1999 to the endof March 2000. On the OBV line, the low in November is more significantthan it appears in the prices, and it shows a breakout of the lows at anearly point.
Volume AccumulatorThe Volume Accumulator (VA), created by Mark Chaiken, uses buying orselling strength as a way to assign volume to the buyers or sellers. If the
Volume, Breadth, and Open Interest
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FIGURE 13.5
On-Balance Volume. On-Balance Volume (OBV) is created by adding the volumewhen prices rise and subtracting the volume when prices fall. You then use the OBV line to maketrading decisions, rather than price.
close is above the middle of the trading range, then the percentage abovethe middle determines how much volume goes to the buyers; if it is below themiddle of the range, then that percentage of volume goes to the sellers:VA = ((close − low) / (high − low) − .50) × 2 × volumeIf close = high, then all volume goes to the buyers.If close = low, then all volume goes to the sellers.If close = middle of the range, then no volume is added.If you want to check your arithmetic, when prices close three-fourths of theway up in today’s range (for example, a high, low, and close of 44, 40, and 43),then 50 percent of the volume is added to the indicator VA.
An Unexpected Comparison between On-Balance Volumeand the Volume AccumulatorWe should expect the OBV and VA lines to be very different because thecalculations of the VA are so much more complex. In Figure 13.6 it seems
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FIGURE 13.6
Comparison of the On-Balance Volume and Volume Accumulator.On-Balance Volume (gray line) and the Volume Accumulator (dark line) are remarkably the same,even though the calculations seem different. Both are intended to be used for trading instead ofprice.
remarkable that there should be so little difference between the two indicators. Sometimes we can be fooled into thinking that two apparently different methods yield different results. Our first hint of this was when welooked at the difference in performance of four trending methods. The conclusion was that, if the market trended, any of the methods would work.We’ll see many more examples where we can simplify our trading by usingonly one method.Further Comparisons. It’s not always the case that the Volume Accumulator is the same as On-Balance Volume. In Figure 13.7, On-Balance Volumestarts higher, drops lower, and then stays lower than the Volume Accumulator. Across the entire chart, the Volume Accumulator shows an upwardtrend, while On-Balance Volume shows a break in June 1994. Look at thechart carefully and try to decide how you would use either of these indicatorsto your advantage.
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FIGURE 13.7
Recent-Exxon Mobil volume patterns. In this example, the OBV and VA showvery different patterns. OBV shows a sell in January 1994, while VA holds an uptrend throughoutthe entire interval. Neither is better than a simple price trend for this one-year interval.
September 11It is always interesting to see how indicators performed on September 11,2001. In the charts of XOM (Figure 13.8) and the S&P (Figure 13.9) we seeslightly different pictures.On September 10 XOM was trading at $41.42 on volume of about 10million shares. Markets were closed September 11 and reopened on September 17 to a rapid sell-off. The bottom came on September 21 when XOMtraded at a low of $35.01 with volume of 21 million shares. The spike inFigure 13.8 shows the day. By October 11, prices were back at $41.77, up 19percent, erasing the entire decline that began September 11. Other spikes inFigure 13.8 mark local turning points, except in mid-December.The S&P 500 show a slightly different picture of building volume from thereopening of the New York Stock Exchange until the bottom on September21. Volume in Figure 13.9 comes from the total futures contracts traded. TheS&P index doesn’t trade; therefore, there is no volume.
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FIGURE 13.8
XOM on September 11, 2001. Prices fell sharply when the NYSE reopenedon September 17, hitting a low on September 21 with a volume spike. By October 11, prices hadfully recovered the 19 percent drop that occurred from September 11 to September 21.
FIGURE 13.9
S&P on September 11, 2001. When dealing with a broad index, the volumespike following the September 11 attack is clearly the major event on the chart and signals areversal. Although the volume spike was an accurate signal, you would need nerves of steel anddeep pockets to buy on September 21.
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Because the S&P represents a much broader market than XOM, volumeafter September 11 is clearly much higher than any other time. The entiremarket was swept away by selling over five days, only to bounce back to aprice higher than before the attack on the World Trade Center.Volume Indicators on September 11. How did the OBV and VA indicatorsperform during the crisis? On the XOM chart they both rally when the marketreopens after September 11, but the VA continues higher and then falls whileOBV drops and rebounds. The OBV actually has the same pattern as the prices.The indicators move in opposite directions, proving that they are not the sameindicator in disguise as it appeared at first. On the S&P chart, the OBV dropsafter September 11 and doesn’t recover. The VA follows the price pattern.Prudence. Volume spikes tend to be an accurate indicator of price reversals and September 11 was no exception. Afterward, it looks as if it was a lostopportunity; the chart clearly shows a buy signal. Don’t fool yourself. Youcould only buy between September 17 and September 21 if you had nerves ofsteel and deep pockets. There was enormous risk. Try to remember thatwhen you’re looking back at this chart in five years.
The Crash of 1987As you gain experience, you’ll suffer through other extreme events. The crashof October 1987 seems to have been pushed aside by the more recent bullmarket of the 1990s, but it was devastating at the time. In Figure 13.10 we seea volume spike on the day of the crash, but it doesn’t rise above the other volume bars as far as we would expect. Would you have taken it as a buy signal?On-Balance Volume gained credibility during the 1987 crash by turningdown ahead of prices. The Volume Accumulator didn’t react soon enoughand hardly reacted during the crash. We would prefer an indicator that workedin extreme price moves.
Automatically Identifying a Volume OutlierA volume outlier is the statistician’s name for a spike. If you are tryingto automate your trading rules in order to test them, it’s easy to recognizean outlier:1. Calculate the average volume over 20 days (call that N days), beginning
five days ago. You will not be using the last five days to avoid volume thatis creeping higher.
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FIGURE 13.10 The crash of 1987. The volume spike is on the right day, but may not be asclear as we need to buy. The OBV indicator (gray) gains credibility by turning down ahead of thecrash. The VA doesn’t seem to respond.
2. Compare today’s volume with your average volume from 6 to 25 days ago.3. If today’s volume is 2 to 3 times higher than the average for a stock, or 11⁄2
to 2 times higher for an index, you have a volume spike.Notice that individual stocks will show spikes that are far above the average,but a broadly traded index market has consistently high volume; therefore,spikes are not as extreme.
MARKET BREADTH INDICATORSMarket breadth measures the imbalance between the number of advancingand declining stocks on a given day. In general, more advancing issues shouldadd confidence to an upward price move. A net increase in the S&P 500 whilemore issues are declining should generate concern that the upward move ispoorly supported.
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The information for advances and declines is published along with stockprices each day. You also may want the volume of advancing issues andthe volume of declining issues. Both of these values can be found in the WallStreet Journal under “Trading Activity.”Market breadth indicators are best used as a confirmation of price direction. The table below shows that the interpretation of market breadth is thesame as the relationship between volume and price.MarketBreadth
Price
Interpretation
RisingFallingFallingRising
RisingFallingRisingFalling
Breadth confirms price riseBreadth confirms price dropBreadth does not confirm price riseBreadth does not confirm price drop
Advance-Decline IndexThe most well-known and simplest of the market breadth indicators is theadvance-decline (AD) index. It is a running count of the number of advancingissues minus the number of declining issues at the end of each day:AD(today) = AD(previous day) + advances(today) − declines(today)
Sibbett’s Demand IndexThe volume of stocks advancing compared to the volume of stocks decliningmay be considered more a “robust” measurement than simply the number ofissues advancing and declining. Throughout technical analysis we’ll see indicators that are equally weighted and their counterparts that use relative value.Sibbett’s Demand Index, (DI), uses the sum of the past 10 days’ upsideand downside volume because these volume numbers, just as with total market volume, can jump around quite a bit. A 10-day sum is really the same as a10-day average, only the numbers are 10 times as large:DI =
sum(upside volume, 10 days)sum(downside volume, 10 days)
where upside volume and downside volume are found in the Wall StreetJournal under “Trading Activity.”
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Arm’s Index—TRINThe Arm’s Index, called TRIN, combines the number of advancing anddeclining issues with the volume of the advances and declines. Its value isoften quoted on television and has gained popularity among technicians:TRIN =
(number of advancing issues / number of declining issues)(volume of advancing issues / volume of decline issues)
Bolton-Tremblay IndexThe Bolton-Tremblay Index (BT) recognizes that there are also unchangedissues each day. Without including the unchanged issues, we have an incomplete picture. This index also takes the square root of the change value, a familiar technique that reduces the importance of a few extremely large changes:BT =
(advancing issues − declining issues )unchanged issues
whereif BT > 0, then BT = BT + BTif BT < 0, then BT = BT − BT
Schultz A /T IndexSchultz takes the same advancing, declining, and unchanged data and represents it as a “bullish index.” By putting the advancing issues in the numerator,the Schultz A/T Index (SAT) would be 100 if all issues advanced:SAT =
advancing issues(advancing issues + declining issues + unchanged issues)
Is One Breadth Index Better Than Another?These five breadth indicators show some of the ways data can be massagedinto an index. There are dozens of others that have not been mentioned.There is no doubt that we should be more confident of a price rally whena large number of issues are advancing, or the total number of shares tradedis much greater for the advancing issues. We should be concerned whenmarket breadth drops, as we would when volume drops, during any pricemove up or down.
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Does it make a difference whether we include the unchanged issues inthe index? Is the total volume traded on advancing issues a better picturethan simply the number of advancing issues? Does the square root used inthe BT Index make the result more accurate? To find the answer, we shouldremember the charts that compared the On-Balance Volume with the VolumeAccumulator. Sometimes one looks better than the other, and sometimesthey look the same.