a row; then theaverage should take effect and eliminate any effects of one particularbad year (or any one particular good year for that matter). When theseasonal pattern is annual, it takes quite a while for the “average” tobe felt. More-frequent seasonal patterns (such as “the market risesnear the end of each month”) offer more opportunities for trading.In the preceding example of VIX trading during the 1997–1999time period, it was quite clear that VIX peaks occurred in Octoberand low points occurred in July. Was this just a coincidence, or doesVIX have some seasonality to it?Most option traders have a general feeling that volatility is low inthe summer and explosive in the fall of the year. It turns out thatthose are correct observations, but much more can be gleaned fromstudying the patterns of volatility over the entire trading year. Moreover, not every year is the same. Thus, volatility displays constantseasonality—it encompasses year-round action. However, muchof the time, there isn’t anything untoward about what’s transpiring;there are just a few times each year when the volatility chart is particularly interesting.
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This information should be of great use because it can aid notonly in timing but also in how aggressive to be in pursuit of the strategy. For example, if an investor knows that options are entering aperiod in which volatility generally declines, then he would want anystraddle buying opportunities to be especially solid with respect tomathematical probabilities. This doesn’t mean that he would avoidvolatility buying altogether just because the seasonal tendenciesmight indicate that a volatility decline could be expected in the coming months.For the purposes of studying seasonality in this case, the CBOE’sVolatility Index (VXO) is used, since it has the longest history, goingback to 1986. Also, the study is arranged by trading day of the yearrather than by actual date. Since there are about 250 trading days ineach year (some years have a couple more), this makes for a nice uniformity in the results; that is, if there were 15 years in the study, theneach of those trading days had 15 different volatilities to average. Ifcalendar days were used instead, then, because each day of the yearoccasionally falls on weekends or holidays, there would be 365 datapoints, but only about 10 or 11 volatilities averaged for each one.Figure 4.24 shows the composite implied volatility for all the datathat was available—from January 1, 1989, to December 31, 2003.Although VXO data backdates to January 1, 1986, the volatilitiesfrom October 1987 through the middle of 1988 were so distorted bywhat happened in the crash of 1987, that we began this study afterthe effects of that event had subsided from the market.Figure 4.24 displays the average VXO for each trading day. They-axis shows the magnitude of those volatilities. Actually, the magnitude is not important. Rather, it is the shape of the graph that is mostmeaningful (again, a dynamic interpretation). In other words, wewant to observe where the peaks and valleys occur. The x-axis istechnically the trading days from the beginning of the year (asexplained earlier); but to make some sense of it in terms of the calendar, the months of the year have been noted on the x-axis. Themonths were placed at intervals that represent where they would fallin the year, in terms of trading days.There are a number of things that are evident from this graph.Volatility tends to begin the year with a rather sharp rise to a spike inmid-January. Then it transcends into a rather steady state, with
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Figure 4.24$VXO COMPOSITE SPREAD: 1989–2003(By Trading Day of Year)24
Average $VX0
23222120191817J
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another sharp rise in late March to a peak in early April. After that,volatility then begins to decline rather noticeably to its yearly lows.The annual low point in volatility occurs, on average, just about thefirst of July. There is then a slow, accelerating increase in volatilityfrom July until the October peak. After that, the volatility decline isvery sharp, culminating in a bottom in late December.You might ask, “How reliable is this pattern?” We know with certainly that many Octobers have seen serious increases in volatility—especially years with nasty October market declines (1989, 1990,1994, 1997, 1998, 1999, 2001, and 2002). But what about therest of the pattern? Does it really hold up?Obviously, some years are going follow the pattern more thanothers. For example, 2003 saw a volatility peak in March and asteady decline for the entire remainder of the year. But 2002, thebottom of the bear market, had a generally high volatility all year,highlighted by two peaks—at the stock market bottoms in July andOctober. Thus, in 2002, July was a high volatility, not the annuallow as is usually the case. Thus, some years do not conform to thepattern very well. In order to give some perspective on how the data
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in the study conformed to the composite pattern, each year wasexamined to see if the five major seasonal points occurred that yearor not. The data are shown Table 4.11.The last line shows how many years out of the 18 in the studyconformed to that particular one of the five patterns. The July low,the October high, and the November-December decline in volatilitywere the most reliable, each conforming in 14 or 15 of the 18 years.The least reliable pattern was the April peak (10 out of 18 years).As mentioned earlier, these seasonal patterns are just guidelines.Individual stocks will behave in their own way much of the time.Hence, it is possible to find straddle buys that work even if established in October. It’s just a lot more likely they can be found in July.
Table 4.11YEARLY VXO PATTERNSYear
JanSpike
AprPeak
JulyLow
OctPeak
Nov-DecDecline
198619871988198919901991199219931994199519961997199819992000200120022003Out of 18:
YNYNYYNYNNYNYYYYNY11
YYNNNNNYYYYNYNYYNY10
YYNYYYYYYNYYYYYYNY15
YY!(Nov)YYNYYNYNYYYYYYN14
YYYYYNYYYYNYYYNYYY15
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Straddle buying is best when positions are established in December, late January, and June or July. Conversely, volatility sellers usingthe composite patterns should look for opportunities very early inJanuary, in April (or late March, some years), and in early November.While such a simple approach won’t produce profitable resultseach year (no more than the adage “sell stocks at the end of Apriland buy them back at the end of October” works every year [2003was a bad year to practice that particular strategy]), it is still a goodguideline for volatility traders. Moreover, the composite graph shouldgive all option traders—and perhaps stock traders as well—a feel forhow volatility can be expected to behave during a full year of trading.Remember, though, that traders should adhere to expected returnson specific positions more than they should rely on the compositevolatility chart.
Trading Volatility DirectlyThe forgoing sections used volatility as a guide toward trading thebroad market. But it is now possible to trade volatility directly.Volatility futures were listed on the CBOE in March 2004. Speculators in those futures might be able to rely on the composite volatilitychart in order to initiate intermediate-term trades—looking to buythem in July and reverse to a short position in October, covering inlate December.Another strategy would be to buy VIX when it is low (in the 10to-15 area) and sell it when it’s high (above 40). Refer once again toFigure 4.19 to see that those are the general ranges where $VIX islow or high.I have never been too sanguine about plotting oscillators andother fancy technical indicators on the $VIX chart. There really is noreason that they should work because not only is $VIX a sentimentindicator, but it is also tied somewhat to the actual volatility of the$SPX options. For example, if actual (historic) 20-day volatility is 10percent and $VIX is trading at 15 percent, are $VIX futures cheap orexpensive? What if we also know that $VIX futures have rarelytraded below 15 percent for years? Does that add any real value tothe situation? If you only looked at $VIX as a chart and applied tech-
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nical indicators to it, you might think it was ready to rally, especiallyif it had spent some time “basing” in the 15 percent area.But how can it rally very much if actual volatility remains so subdued? In fact, it can’t. So the differential between actual and impliedvolatility is an important factor, too, if you’re trying to predict whatthe $VIX chart is going to do.Eventually, the CBOE plans to list options on VX futures. Whenthat happens, there could be some very interesting strategies available, although they will still have the characteristics that any spreads,straddles, or outright option positions always do. When volatilityoptions become available, traders will have to be cognizant of the“volatility of volatility” in order to price them. See Figure 3.2 for agraph of that volatility (at the very end of Chapter 3).
Further Observations on Index VolatilityThere are volatility measures besides VIX and VXO. As mentionedpreviously, there are two companion measures—QQV and VXN,which follow the QQQ Tracking Stock and the Nasdaq-100 Index(NDX), respectively. They could be analyzed as well, although Ihaven’t really found that they offer results much different from thosewe would obtain by studying VIX and VXO.In addition, we could also create or find other composite impliedvolatilities. One that we occasionally look at is the composite impliedvolatility of the stock options on the stocks that comprise the OEX.This sometimes gives a slightly different picture, for equity optionimplied volatility does not necessarily conform exactly to indexoption implied volatility, which is what VIX measures. Still, it’s oftenvery close; so we only use that composite of stock options as a secondary guide—and even then, only on occasion.Another question that often arises is, “How does historicalvolatility fit into all of this?” After all, doesn’t VIX have to be relatedto historical volatility to some extent? The answer is, yes, it does—but not as directly as you might think. In fact, it’s often the case thatVXO trades at a higher level than the actual volatility of OEX. Thisseems to be mostly due to the fact that traders have high expectations when they buy OEX options and they tend to slightly overpay
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for them. Perhaps this is because of the ease of establishing a “market” position with just one trade, rather than having to place 100orders on individual stock options to accomplish the same thing.Thus, traders are willing to pay up a little for the convenience of getting the whole order done with just one simple trade. This is especially true if one is buying protection for a portfolio. The price ofbuying an OEX out-of-the-money put is much higher than the equivalent price of buying out-of-the-money puts on each individual stock(in fact, some arbitrageurs actually buy the 100 individual equity putsand sell the OEX puts, establishing what is known as a dispersiontrade).Since VIX is related to historical volatility to some extent, itbehooves the option strategist to pay attention to both. For example,after the market started to rally in March 2003—a rally that extendedfor the rest of the year—VIX began to fall and reached very low levels by May. Some market observers were calling for a market correction because VIX was “too low.” However, actual (historical)volatility was dropping even more rapidly. So even though VIX waslow—about 22 or 23 at the time—the 20-day historical volatility ofOEX had already dropped to 16 percent. Hence, in that context,VIX was not cheap, and traders should not have been expecting VIXto rise without some sort of increase in the actual volatility of themarket—an increase that was not forthcoming, as it turned out.Conversely, it is relatively rare to see VXO trading much belowthe 20-day historical volatility of OEX (or to see VIX trading belowthe historical volatility of SPX). The only times that VXO hasdropped below 70 percent of the historical volatility of OEX havebeen times of extremely severe market volatility—the crash of 1987,the Dow limit down in 1997, the Long-Term Capital hedge fund crisis in 1998, and so on. As you know, each of those were good buypoints, so this situation might be used as an additional volatilityindicator.
THE PUT– CALL RATIOThe put–call ratio is simply the number of puts traded in a daydivided by the number of calls traded on that same day. Normally,
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options are grouped into similar categories when calculating theratio. For example, an index option put–call ratio, or maybe a goldoption put–call ratio, might be calculated. In order to smooth out thefluctuations of the daily numbers, some moving averages of theput–call ratio are usually tracked. The dollar-weighted put–call ratiocan be tracked as well, as it is often an even better contrary indicatorthan the simple put–call ratio itself. To differentiate between the twotypes of put–call ratios, we will use the terminology “standard”put–call ratio to refer to the typical, volume-only ratio, while“weighted” will refer to the dollar-weighted put–call ratio.Technicians have been calculating the put–call ratio for a longtime, even before the advent of listed options, for it is known to be avaluable contrary indicator. When too many people are bullish(when they are buying too many calls), then contrarians short themarket because the majority is usually wrong. Similarly, when toomany traders are bearish and buying puts, then a contrarian will lookto buy the market. The put–call ratio is a measure of how many putsare trading with respect to calls, so that the contrarian can attempt toquantify his measurements.The general patterns to compare are shown in Figure 4.25.When the put–call ratio is at a high level, a lot of puts are beingbought, and that indicates a market buy. Then, the put–call ratiodeclines while the market is rallying. Eventually, bullish sentimentbecomes too strong, and the put–call ratio bottoms just as the marketis making a top. After that, the put–call ratio rises while the market isfalling, until the whole cycle begins again. Ideally, the put–call ratioand the underlying instrument chart are mirror images of each other.In reality, of course, it’s never that perfect; but that is the ideal pattern one would like to find.Put–call ratios can be computed on nearly any underlying instrument—stock, index, or futures contract. They are useful contraryindicators on most all of them, but not on every single one. Someguidance will be presented to help the reader in deciding which onesare best to use. Each different type of underlying instrument has itsown particular application. Also, the equity-only put–call ratios arevery important.Index options, for example, are quite useful—but not all of them.Whenever an index option is heavily traded by hedgers or arbi-
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Figure 4.25PUT– CALL RATIO
trageurs, its usefulness as a contrary indicator wanes. For this reason,many of the sector indices, such as the Semiconductor Sector Index($SOX) or the Gold and Silver Index ($XAU), are quite useful. ButQQQ, SPX, and OEX options are not because many institutions routinely buy the puts as a hedge. We will expand on this concept later,but for now it is sufficient to note that fact. However, the use of theweighted put–call ratio on these indices can be used—another factorin favor of using weighted ratios.One of the most useful put–call ratios is the equity-only put–callratio. As the name implies, this ratio is calculated by using all stockoptions that trade. It is used to predict the “market” overall. When itgives a signal, an investor can generally trade the index of hischoice—SPX, OEX, Dow-Jones (DJX). The equity-only ratio is usefulin both the “standard” and the “weighted” forms.Stock option put–call ratios can be useful. In the first edition ofthis book, I doubted that fact; but I have come to the conclusion—
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verified in actual practice by a number of successful trades—that,with proper care, put–call ratios can be used on stock options. Thebest situations are liquid stocks—ones with plenty of option volumeand ones that are unlikely to be takeover candidates or to be easilyinfluenced by rumors. Stocks with low average option volume, however, may not be as useful; for a large option order—even if only acovered write or a spread—might unduly influence the ratio. Thissame statement applies to less liquid sector options as well. Furthermore, in stocks, there is sometimes inside information present in themarket—as was shown earlier in this chapter. In those cases, optionactivity is a direct indicator, not a contrary one; so this just stressesthe point that investors should be vigilant when using the put–callratio for stock trading.As for futures options, they are best utilized where liquidity isgreat. One sums the volume over all the monthly contracts (FebruaryGold plus April Gold plus June Gold, etc.). However, it makes nosense to calculate a “futures-only” put–call ratio (similar to the equityonly ratio) because there is no relationship between grain options,say, and oil options.In general, we look for liquid option contracts in any of thesemarkets. Furthermore, we would ideally like to see the put–call ratioreach an extreme reading as a precursor to making a trade. All ofthese concepts will be expanded on within this section.One other ratio used to be important, but its relevance haswaned in recent years. That is the index put–call ratio, which in theory is the sum of all index options that trade, but in practice wasmostly just the OEX options, since that index dominated option trading for years. However, as institutional hedging has become moreand more prevalent, the concept of an index ratio is not as important. Currently, I prefer to look at weighted ratios on a few specificindices, but not the sum of all index options as a whole.
The DataThe standard put and call volume data is available in the newspaperevery day and also from online sources, such as www.tbsp.com orwww.gfds.com, which sell raw daily data for a fairly low price. The
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equity-only data is more difficult to compile. An investor could download all of the individual stock data and then add them up, which isactually what we do at McMillan Analysis Corp.; but that would be amajor undertaking for most people. An easier way is to utilize theinformation that is available on the CBOE web site, www.cboe.com.The CBOE will even e-mail its statistics to you daily, for free, if youwish, or you can visit the CBOE web site yourself. One of the available statistics at the CBOE site is “equity-only” volume. Now it’s truethat the CBOE’s stock option volume is not the same as the volumeon all the exchanges (although it is sizeable), but that doesn’t reallymatter; for the shape of the chart of the CBOE’s equity-only ratio isthe same as that of the chart of the true equity-only ratio—and it’sthe shape that’s important, as you will soon see.Lest you think that it’s not worth it to bother with the equity-onlyratio, be aware that for many years the equity-only ratio has givenimportant signals with far better timing than any other broad marketratio — better than any of the index put–call ratios, for example. Infact, there is evidence that the equity-only ratio is the “purest” ratiobecause there is so little arbitrage in equity options anymore, andmost money managers don’t buy equity puts for protection—theybuy index puts. Therefore, equity options may represent a bettercomposite picture for contrarians.The simple put–call ratio follows this formula:“Standard” put–call ratio = Total put volume/Total call volumeFor example, consider IBM. At the end of the trading day, onewould total up the volume on all the individual puts and then dividethat by the sum of the volume of all the individual calls. That wouldbe the “standard” put–call ratio for the day for IBM. Some tradersmay look at intraday ratios, but I haven’t found them particularly useful unless there is massive volume—and usually that is related to anews event, which may dominate the stock’s movement despite whatthe put–call ratio might be indicating.The dollar-weighted put–call ratio follows this formula:Σ (Put volume × Put price)“Weighted” put–call ratio = —————–——————Σ (Call volume × Call price)
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You multiply each individual option’s volume by its price and find thesum of all the puts, then divide by a similar sum of all the calls. Tosimplify things, you can use closing volume multiplied by closingprice; but if you have the horsepower, you could calculate theweighted ratio all day long by summing the volume multiplied by theprice at each tick.The weighted ratio measures the dollars being spent on putsversus the dollars being spent on calls. This is generally a moremeaningful figure than just volume alone. Consider this case. Suppose that 1,000 puts trade at a price of 0.10. That’s a lot of volumefor most option series, but the actual dollars spent here are just$10,000. Meanwhile, suppose another trade takes place, using aslightly in-the-money option, the kind that a serious speculator wouldprobably use: 100 contracts at a price of 5. That’s $50,000 worth ofspeculation. So, the first trade carries 10 times the weight of the second one (1,000 contracts to 100 contracts) in the standard ratio; butin the weighted ratio, the second one, carries 5 times the weight ofthe first trade ($50,000 to $10,000). This is why the weighted ratiois often a more useful contrary indicator—because it measures wherepeople are putting their money.The data for this ratio are difficult to obtain without calculatingthem yourself. Our company, McMillan Analysis Corp., does calculatethe data on a number of stocks, futures, and indices and for the equityonly ratio each day. Those data are available to subscribers of our put–call ratio charting services—either “The Strategy Zone” on our website, www.optionstrategist.com, or weekly “Put-Call Charts” by e-mail.The weighted ratio tends to give more extreme readings and moretimely signals. It is, therefore, a preferable ratio over the standardratio, although the standard ratio gives many excellent signals, too.Notice that put volume is in the numerator of the preceding fractions. So, bearish activity makes the put–call ratio rise (presumablywhile the underlying instrument is falling). Conversely, call volume isin the denominator of the fraction, so bullish activity is reflected inlow put–call ratios (presumably while the underlying is rising in price).The ratios themselves can be expressed as a percent or as theabsolute ratio. For example, if an equal number of puts and callstraded, then the daily number would be 1.00 (absolute) or 100 (percent). I prefer to use “percent,” as it is more the accepted norm.
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It is customary to use a moving average to smooth the data. I usea 21-day moving average almost exclusively, although sometimes aslightly longer-term average, such as the 55-day moving average, canbe helpful. A 21-day moving average gives about six to eight signalsper underlying instrument per year. Since I am mainly a positiontrader, this works out well for me. If you want more trades, you couldshorten the ratio, but at the risk that you would be subject to a lot ofwhipsaws.
Interpreting the RatiosThe concept of interpreting the put–call ratios is an easy one in theory; but in practice, things become a little more complicated. It is aneasy matter to say that when the ratio gets “too high,” you shouldbuy the market. Conversely, if the ratio gets “too low,” you shouldsell the market. Quantifying “too high” and “too low” is where thingsget tricky. Past experience has shown that static interpretations ofthe put–call ratios are an incorrect approach, for investors andtraders change their investing patterns. Rather, a dynamic approachis best. A dynamic approach means looking for peaks and valleys—at whatever absolute levels they may occur—in the put–call ratio toindicate buy and sell points.As noted earlier, the standard equity-only put–call ratio rangedfrom 30 to 55 during the bull market of the 1990s. This led manycasual observers to adopt a static approach, saying that buy signalsappeared when the ratio reached 53 or 55. True, many buy signalsduring the bull market did occur at that level. However, such a staticinterpretation will eventually get you into big trouble. Thus, when thebear market started in earnest—in 2000—the equity-only put–callratio blew right on through the 55 level, eventually reaching highsnear 90. If you had bought that last time when the ratio reached 55,you would have been buried under an avalanche of selling as themarket transitioned from bull to bear.Thus, the proper interpretation is to look for peaks and valleyson the put–call chart. Peaks are extremes in put buying and are buysignals for the underlying. Valleys are extremes in call buying and aresell signals for the underlying. Figure 4.26 illustrates this concept
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quite clearly. Mathematicians call peaks “local maxima” and valleys“local minima,” but it doesn’t make much difference what you callthem as long as you use them properly in your trading. You will see,in all of the put–call charts presented in this chapter, that thedynamic approach is taken in their interpretation. Ideally, the peaksand valleys would occur at extreme levels on the chart, but that is notalways possible. It has been my experience that a signal that arisesfrom a severely extreme reading is not necessarily any better than asignal that occurs at a more modest level on the put–call chart.On a typical day, there are always more equity calls traded thanputs, so the equity-only put–call ratio is less than 100. More likely, itis quite a bit below that—more like 50 on most days. However, anindex put–call ratio will be much higher, if that index’s options areused for hedging, as most of the broad-based indices options are.Typically, one might see the “standard” OEX put–call ratio range as
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high as 150. Weighted put–call ratios are much harder to pin downand trade in vastly wider ranges that standard put–call ratios do.That is one of the advantages of the weighted ratio —it registers suchviolent extremes that it is easier to determine when the public hasreached a crescendo of bullish or bearish opinion.No matter how you state the ratio, its actual level is unimportant.It’s much more useful to know its relative level. This will becomemore obvious when actual charts are observed, but consider this.During the bull market of the 1990s, the equity-only put–call ratioranged, in general, between about 30 and 55. It was as low as 30 atextremely optimistic times, and it was as high as 55 during panic selling times (October 1997 or October 1998, for example). So, sell signals occurred when the public was overly optimistic (at about 30 onthe put–call ratio), and buy signals occurred when they were too pessimistic (at a put–call level of about 55). However, when the bearmarket set in after the turn of the century, there was a lot more putbuying on a routine basis. During the 2000–2002 time period, theequity-only put–call ratio generally ranged between about 55 and 90.Thus, sell signals occurred at 55, which was the optimistic readingduring those years. In other words, the 55 level, which had previously denoted buy signals during the bull market, now was generatingsell signals during the bear market. The moral of this story is do notuse fixed levels to interpret the ratios—and avoid the advice ofanyone who tells you to do so.Let’s look at some historical examples. Recall that put optionsdidn’t start trading until 1977, and index options until 1983. Therefore, it wasn’t until after 1983 that traders had the index put–callratio and the total put–call ratio available to them. Since there wasvery little use of index puts as protection in those days, the indexratio was considered to be the best source for the speculative pulse ofthe market. Moreover, there was a lot of arbitrage in equity options,so the equity-only put–call ratios were somewhat distorted by thisarbitrage.In those days, the index put–call ratio ranged between about 60and 100 at the extremes, much lower than today’s average range.When the ratio rose to near 100, the market could be bought, andwhen it fell to 60, it could be sold.
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In October 1985, the index put–call ratio reached 100, and the marketembarked on a huge eight-month rally. OEX moved from 175 to 239 byJuly 1986. Then, in December 1986, the index put–call ratio reached 100once again; and the market rallied for another eight months, setting manyall-time highs along the way. OEX rose over 100 points in that time. Theratio reached very low levels in March 1985 and April 1986, neither ofwhich was a tremendous sell point; but in both cases the market leveled offand went sideways for several months after each occurrence.These buy (B) and sell (S) signals, using the intermediate-term 55-daymoving averages, are shown in Figure 4.26, while the graph of OEX overthe same period is in Figure 4.27.
What happened next made many technicians discard the put–callratio as a useful indicator. The index put–call ratio (coming off theFigure 4.27OEX DURING 1987
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