tight bands that rapidly expand and contract with changes in short-term volatility, better suited todetermining short-term market swings. Longer-term moving averageshave wider, more stable bands, best suited for determining possible topsand bottoms of longer-term swings. If one is looking to trade marketswings, is it better to trade short-, intermediate- or long-term swings ofthe market? This is similar to asking the question in the original study ofwhich moving average did the best.
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I hypothesized that the feedback-loop components in the model forstock prices would cause certain size-price movements to repeat justenough so that a particular Bollinger band would catch the tops and bottoms of the move better than others. The new study would establish twothings:1. Which moving average did the best between 1966 and 1982 (likethe original study)2. Which Bollinger band method of defining market tops and bottoms did the best from 1966 to 1982It must be understood that the two strategies being tested are distinct and different. The first question would be answered by doing astudy like the original. The second question, testing the various Bollingerbands to try to catch tops and bottoms, required a little more thought.One of the limitations of using Bollinger bands as I intended to do isthat if prices reach the top of the band and I sell the S&P 500, there isno obvious strategy for when to buy again. Do I wait until I get to thebottom band before I buy back in? That wasn’t feasible; prices quiteoften didn’t return to the bottom band for some time. Sell-offs afterreaching the top band were often mild and wouldn’t decline enough toreach the bottom band.The Bollinger Band StrategyThe new study was set up to test every moving average between 5-dayperiods and 200-day periods, just like the original study. Each movingaverage would start with $1, and the study would keep track of the valueof that dollar every day. Each moving average would be tested as it wasin the original study, but I added this nuance from the Bollinger bandconcept: When a price reached the top Bollinger band for a given moving average, the computer would sell some of the money and put it in aT-bill account; the other money would be carried forward following thenormal moving-average method.The money that was sold out when the top band was penetratedwould sit in a T-bill account until the price went below the moving average; then the remaining money would also go into the T-bill account asthe normal moving-average strategy demands. At that point, 100% ofthe money would be in the T-bill account. If prices moved back up abovethe moving average, 100% of the money would be moved back into the
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S&P 500—in other words, all the money would now move according tothe moving-average strategy.What would happen if prices were to go way down and penetrate thelower Bollinger band? The computer would take some of the money outof the T-bill account and buy the S&P 500 on the assumption that pricesmay have reached the bottom of a trading range and it might be a goodtime to buy. The situation would stay this way (some money invested andsome still in T-bills) until prices again move above the moving average.At that point, the other money would go into the S&P 500, following thenormal moving-average procedure. If prices go under the moving average again, all 100% would come out of the S&P 500 and go back intoT-bills as usual.Summarizing the Trading Range StudyIn this study, I tracked two pools of money over the 16.5 years. One pool,Strategy 1, followed the moving-average strategy. The other, Strategy 2,followed the moving-average strategy except at certain moments, whenBollinger bands were penetrated, and then it followed its own signals.Preliminary studies of many combinations indicated that a good mix occurred when the Strategy 1 pool contained 60% of the assets and Strategy 2 contained 40%.Strategy 1Test every moving average between 5 and 200 days, including 8 verticalshifting variations up and down per moving average. I tested 1,755 movingaverages. For each moving average, the strategy was to buy the S&P 500 atthe close when the S&P 500 closed above the moving average, and to sellthe S&P 500 at the close when the S&P 500 closed below the moving average, with the funds going into a T-bill account, as in the original study.Strategy 2Test Bollinger bands that are twice the standard deviation away fromtheir moving average. I tested 1,755 Bollinger bands, one set for each ofthe moving averages. In Strategy 2, when the S&P 500 went above thetop Bollinger band, the S&P 500 was sold and the money put into a T-billaccount. It stayed there until prices either went below and then abovethe moving average or until the lower Bollinger band was penetrated. Atthese times, the money was again invested in the S&P 500. In Strategy 2,when the S&P 500 went below the lower Bollinger band, the S&P 500
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was purchased. It stayed invested in the S&P 500 until prices either wentabove and then below the moving average or until the upper Bollingerband was penetrated. At these times, the S&P 500 was sold and themoney put into a T-bill account.
Restrictions on the New StudySince the original moving-average study, new investment vehicleshave been developed that overcome one of its major limitations:having to accept the next-day closing price after a signal is given onthe market’s close. When I did the original study, it wasn’t feasible—or even possible—to calculate the moving average right up to theend of the trading day and then to execute the free exchange beforethe market closed.With current computer systems, however, you can know thevalue of the S&P 500 minute by minute, right up to the close. Therealso are Spyders (representing one share of stock in the S&P 500)and programmed trading methods (for institutions) for buying andselling baskets of stock that mirror the S&P 500 at any minute. Forthe new study, therefore, I decided to assume the capabilities thatthese new trading vehicles might allow.I assumed that I could monitor the condition of the moving average and the Bollinger bands right up to the close. If a signal weregiven, the assumption was that the price of buying or selling the S&P500 would be the closing price for the same day. In practice, thismight be difficult to do if the moving average or the Bollinger bandswere very close to the price at the close, but I think it would be possible in most cases.These new ways of investing in the S&P 500 would change oneof the earlier assumptions. Previously I had assumed that there wasno transaction cost since I would use the free-exchange privilege ofthe index mutual fund. Since the study now assumes that Spydersare being bought or sold, a transaction cost for a round-trip transaction must be added. The spread, or price difference, between the bidand the ask was also assumed. For the study, I assumed a round-tripexpense cost to buy and sell, which included commissions and thespread between the bid and ask prices, of 35 basis points, which is35/100 of 1%.
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I cannot present the entire study here because it is too detailed. Although the study identified several good strategies, I’m going to showyou just one of the most successful results (Figure 8.9).As in the first study, the benchmark is the total return of the S&P500 during this 16-year period: 5.06%. In Figure 8.9, this buy-and-holdreturn is shown as the dotted line. The other line plots the average annual return each moving average produced (maintaining an asset mix of60% moving average and 40% Bollinger band). The two moving averagesthat are highlighted are the 72-day and the 132-day. Both producedback-tested average returns of just over 10, which is 5% more than theS&P buy-and-hold strategy produced. The chart also seems to indicate
FIGURE 8.9 The 1966 to 1982 study. The line at the bottom shows the S&P500 buy-and-hold strategy. In a sideways market, the two 72-day and 132-daymoving averages did pretty well. The study used two concurrent strategies: 60%of the assets followed the moving-average signal and 40% followed the Bollingerband strategies. These results reflect a variation of the simple moving average. Inthis study, better results occurred when the moving averages were raised upwardon the price scale by 1%, which is the opposite of what was discovered in the70-year study. The assumption here was buying and selling the S&P 500 Spydersand using the price on the S&P 500 at the close of the day the moving-averagesignal was given. A 35-basis-point allowance was used for the spread and thecommission.11%10%9%8%7%
Resonance Peaks72 and 132 day
6%5%4%
20
40
60
80
100
120
Moving Averages
140
160
180
200
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that almost any market-timing method works better than buy and holdthrough long trading range markets.In the earlier study, I tested a number of variations on moving averages by adjusting the moving average line up and down, searching for arelationship that would improve the moving-average returns. The curvein Figure 8.9 plots one of the variations that produced a good result. Thisvariation resulted from shifting all the moving averages upward by 1%.In other words, I calculated the moving average and then multiplied it by1.01, which raised the moving average on the price axis. It had the effectof generating sell signals earlier and buy signals later.I decided to focus on two moving averages from this study, the 72day moving average and the 132-day moving average. It is important tonote that moving averages around 130 days worked well in almost allstudies of various market periods. They worked the best for the entire70-year study and for the 16.5-year sideways market. The difference wasonly in the shift: In 70 years, the 130-day moving average shifted downward 1.5%, and in the sideways period, the shift was upward by 1%.The ResultsI have always found it easier to visualize how these strategies performedby looking at the day-to-day result of each moving average. Figure 8.10shows the day-by-day result of the 132-day moving-average strategy(60% Strategy 1 and 40% Strategy 2), and Figure 8.11 shows the 72-dayresults (also 60% Strategy 1 and 40% Strategy 2), both plotted against theS&P 500 buy and hold.It’s easy to see from these figures how the strategies work. The moving averages and their Bollinger bands provided a good time measure tocatch the major upward moves early while sidestepping most of the declines and allowing the Bollinger bands to catch the extremes of themovements.Because both moving averages (132-day and 72-day) gave consistentreturns and each gave a better than 10% average annual return for the16.5-year period, I decided that a combined strategy using both movingaverages would probably perform the best. An average of the two wouldproduce about the same total return as either one alone, but the path toget there would be smoother for the same reason we diversify in portfolio theory (i.e., when one investment zigs, the other zags). The total return for combining the 72-day and the 132-day moving averages 50 : 50
THE NEW MOVING-AVERAGE STUDY
FIGURE 8.10 Plotting the day-by-day value of the 132-day result (movingaverage and Bollinger band) versus the daily S&P 500 buy and hold.
FIGURE 8.11 Plotting the day-by-day value of the 72-day result (movingaverage and Bollinger band) versus the daily S&P 500 buy and hold.
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TABLE 8.1 Yearly results of the combined 72- and 132-day moving-averagestrategies from 1966 to 1982S&P 500
Combined 72 and 132
1966196719681969197019711972197319741975197619771978
–10.1%23.9%15.5%–9.2%2.2%15.4%19.4%–14.8%–26.7%34.1%22.9%–7.2%6.6%
–0.1%19.3%13.7%4.6%18.0%17.8%7.3%1.6%– 4.5%21.0%14.8%0.8%12.6%
AMFLY
Year
was 10.3% per year from 1966 to July 1982. Table 8.1 shows the combined yearly results.
TE
MOVING AVERAGES AND FEEDBACK LOOPS
Recall from Chapter 1 the stock market model that says the price ofstocks equals a fair value modified and stretched by the action of threefeedback loops. These loops are generated by the emotional reaction ofinvestors focusing on three separate time frames. The conclusions fromthese moving-average studies seem to show that these feedback loops,once started, tend to continue for specified periods. In other words, theeconomic factors (fair value) can change as the economy changes, butthe one constant—the human being and his or her reaction to events—is nearly the same through all eras. These reactions create the recurringcycles that moving averages measure.The moving averages that did the best in the study seem to be theones that fit or harmonized with how groups of investors react and create market movements as feedback loops. As stated before, these feedback loops can run for a maximum of about 13 weeks down or about 26weeks up. The 132-day and 72-day moving averages fit in the time scalewe would expect of feedback loop movements.
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Will this change over time? After all, there were only 400 mutualfunds in the mid-1970s, and now there are over 10,000; the marketseems more complex than it used to be. Today the Internet allows people to trade on a daily basis for a small commission. It would seem thatthe relative number of investors in the three time realms—short-term,intermediate-term, and long-term—is not a constant but is changing,maybe significantly. Won’t this modify the size of the various feedbackloop movements and their relationships, disturbing the ways these timerealms interacted in the past? I believe it will have an effect, but it is difficult to anticipate exactly what that effect will be.The increase in day trading should modify the short-term feedbackloops; perhaps that will set into motion more intermediate-term moves.The definite increase in short-term price volatility reflects the largernumber of traders who trade for short periods. (In other words, theshort-term feedback loop has been magnified.) My hope is that the 72day and 132-day moving averages are long enough to smooth away someof these changes and will still work.
USING STANDARD TECHNICAL ANALYSISThere will be other ways to try to invest through a period like the one I’mexpecting. Besides using the strategies presented in this chapter, standard technical and fundamental analysis and the lessons we learned during the 1970s and 1980s will be very important. Much of this informationis summarized in the indicators and ideas presented in Chapters 4 and 5.These ideas cannot be back-tested as thoroughly as the methods shownin this chapter, but the good track records of some market technicianswho actually navigated the stock market of the 1970s show the potentialof this knowledge.My principle of time invariance says that if an idea is useful for locating an intermediate-term top or bottom, the same principle is usefulfor locating short-term tops and bottoms. The only difference is that thetime scale of measurement should be reduced to reflect the differenttime domain of interest. It will be important to remember this during theupcoming period.Of the various technical tools available, I cannot overemphasize howimportant market sentiment will be at locating the intermediate tops andbottoms that will make up the trading ranges of this period. The long,successful records of investment recommendations by Robert Farrell,
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Martin Zweig, Bob Schaeffer, and Joseph Granville are attributable to agreat degree on their use of contrary opinion indicators.Although I believe the near future will essentially be a trading rangeperiod for the overall stock market, certain groups of stocks will outperform others. A trading range market will apply for most stocks, but a bullmarket—albeit a slow-moving and undramatic one—will be in force fora number of other stocks and for select groupings. The task is to identifythese stealth bull markets, as I like to call them. Only after looking backover 2- or 3-years will we be able to separate the trading range groupsfrom those that have been slowly advancing over the period. These particular segments will appear to be in a trading range, but in reality theywill be trading ranges with a distinct upward bias that will become clearonly after a number of years.For example, there will be a time to buy technology stocks again. Inearly 2000, I wrote the following.I believe that before this trading range correction is over, a completereversal in the extreme speculation that occurred in the technologysector must occur. I think that someday we will hear a chorus arise saying, “How could we have seen so much potential and have been sowrong?” When I hear that chorus, it will be one important sign that theend of the correction is near and a new investment cycle in technologyis ready to begin.
That prediction is coming true very nicely. Technology stocks willagain rise out of the ashes—when the investment community believesthere is no longer much of a future in technology.The change will not be dramatic but will slowly emerge. Prices willbegin a gradual but constant rise, causing little commotion or attention.We are rapidly approaching that point, and it happened a lot faster than Ihad projected when prices were at their peak. I had expected that it wouldtake about 4 years to squeeze the speculative excesses out of the technology sector. The market is indicating that it will happen faster than that.THE RISE OF HEDGE FUNDSHedge funds are a very misunderstood investment form. This is unfortunate because hedge funds will offer investors a new way to makemoney during a trading range market. It will take a lot of re-education toovercome the misconceptions.
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Why Mutual Funds Might Not Do as WellI remember at the end of 1982 that the 10-year performance numbers ofmutual funds were dismal. At least half of the funds posted negative returns during the decade, which meant that most mutual fund investorswho had held funds for 10 years made little if any money. Sixteen yearslater, by 1998, over half the mutual funds were reporting 10-year performance numbers exceeding 20% per year—accounts increasing morethan four and five times in value.Had the mutual fund money managers become that much better atpicking stocks over the 16 years between 1972 and 1998? Of course not.This situation simply reflects what we discussed in Chapter 2, that anylarge, diversified group of stocks will behave much like the market. Thenegative 10-year fund numbers between 1972 and 1982 simply reflectthe fact that the stock market, as measured by broad stock indices, wasin a trading range. The high returns from 1988 to 1998 were simply a reflection of skyrocketing stock prices. This means that most of the returnfrom stock mutual funds doesn’t originate from the skill of the moneymanager but from the natural return from stocks over the period in question. If we are entering another trading range market, mutual funds as aclass will very likely give correspondingly bad results, just as they did between 1972 and 1982.Mutual funds invest according to the mandate of their prospectus—the legal document that describes their investment goals, the type of investments they can use, and a little about their strategy. Most fundscannot sell short the market to any great degree and, in fact, SEC lawputs a restrictive upper limit on this practice. Mutual funds are primarily a bull market investment vehicle. They also have certain turnoverlimits. Mutual fund money managers aren’t supposed to become shortor intermediate-term traders or to hold high cash positions if they arenervous about stock prices. History has shown that mutual fund managers increase cash in bear markets, but few increase it to a high level.The mutual fund cash position has never exceeded 15% for mutual fundsas a group, even during the worst 2-year bear market of the last 40 years.Mutual funds are not designed to trade a trading range market.As I explained in Chapter 5, it fits within my understanding of contrary opinion to have the general return from mutual funds fall offsharply in the coming years. After all, the last 10 years have witnessed thelargest explosion in mutual fund assets in our history. The influx of investor money has been enormous. In a sense, contrary opinion says that
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when this carries to such an extreme, investors will get the opposite of whatthey expected; if so, investors are going to be disappointed in their returns,and this flow of money into mutual funds will soon reverse, as investorsstart looking for other ways to earn money. A flat U.S. market will probably also bring about flatter world stock prices. There will be bull marketsin some countries, but if the U.S. stock market enters a trading range,other countries’ stock markets probably will, too. Investors throughout theworld will be facing the same or similar problems. To overcome this, I believe investors will start turning their attention to hedge funds.Hedge FundsHedge funds are grossly misunderstood. Most people think hedge fundsare risky, yet hedge funds often use strategies that are less risky thanmost mutual funds. One of the problems here originates in language, andit is the same problem as with the term mutual funds. Someone mightsay that mutual funds are risky but a government-guaranteed, T-bill,money market fund is a mutual fund. We classify both this T-bill moneymarket fund and a high-risk Internet fund as mutual funds, but their risklevels are completely different as mutual funds. The common factor isnot the risk of the investment, it is that they follow the same laws andrules required of a mutual fund.The same is true of hedge funds. Many hedge funds are as differentfrom one another as night and day, but they are similar in one respect:They must follow certain common legal and administrative rules demanded of hedge funds by the SEC.Since a hedge fund can execute investment strategies that are restricted for mutual funds, the SEC wants to make sure that a hedge funddoesn’t become a mutual fund in disguise. Therefore, unlike mutualfunds, which have no shareholder limits, U.S. hedge funds are limitedregarding the number of investors to a maximum of either 99 or 499, depending on a number of criteria. Furthermore, not everyone can investin hedge funds even if they want to. Each investor must be accredited,which means that each investor has either a specific high net worth or annual income.The rules also prevent hedge funds from advertising. It’s as if thegovernment is saying, “You can exist outside the normal mutual fund regulatory arena and do your nonstandard investment strategies, but onlyunder strict conditions.” Another feature of hedge funds, not allowedwith mutual funds, is that the money manager can participate in the
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earnings of the fund. In other words, the hedge fund manager’s earningscan include a certain percentage of the gain in the fund. This is strictlyprohibited in mutual funds.A hedge fund is an investment vehicle that commingles investors’money in one fund, follows the SEC requirements for hedge funds, anduses a variety of investment strategies and investment types. In my opinion, unlike a mutual fund, a hedge fund’s investment return dependsmuch more on the skill of the manager and not so much on the naturalreturn for stocks, bonds, and so forth. This is exactly what is required ina trading range market.Expected Rising Popularity of Hedge FundsI believe the next 5 years will see a large increase in interest in and popularity of hedge funds. I make this prediction based on the following.• The number of accredited investors has exploded. The stock market advance has thrown more and more people over the $1 millionmark for net worth. Ten years ago, only about 0.3% of the population was accredited; now this percentage is well over 1%.• The low return from mutual funds during a trading range marketwill spur investors to start looking around for alternatives. This willinduce a learning cycle to understand more about these alternative methods of investing. Hedge funds are often called alternative investments.• If the stock market experiences the decline in volatility I’m expecting (as outlined in Chapter 7), there will be an interest inother markets with greater volatility and the potential to producestronger investment returns. Currencies, gold and silver, oil, andother investments will be considered. Some of these other markets are best tapped through some type of hedge fund, notthrough a mutual fund.If these observations are correct, it will be important for investors tolearn a lot more about this expanding investment area.Hedge Fund Investment StrategiesThe expansion in financial products (futures and options in world stockand bond indices and currencies) has increased the variety of ways a
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money manager can try to profit from investments besides stocks andbonds. These new strategies are really just the application of some oldand familiar concepts applied to these new financial products: short selling, hedging, arbitrage, and leveraging. A new addition is the use of derivatives (futures and options) in place of the actual investment. Fromthese strategies come a number of methods that try to make money overand above the simple action of buying a portfolio of stocks or bonds.These strategies require a lot more investment skill and expertise.Several companies evaluate the performance of hedge funds. Theycategorize hedge funds into types, much as mutual funds are categorized by the type of stocks or bonds they invest in. However, since hedgefunds are primarily distinguished by an investment method and not by anasset class, the categories are usually types of investment strategies. Forthis book I have used the classification of Van Hedge Fund Advisors International, Inc. Following are the 14 strategy classifications that arecommonly used to categorize hedge funds.1. Aggressive growth2. Distressed securities3. Emerging markets4. Fund of funds5. Income6. Macro7. Market neutral—arbitrage8. Market neutral—securities hedging9. Market timing10. Opportunistic11. Several strategies12. Short selling13. Special situations14. ValueI have chosen five of these strategies that might be particularly likelyto do well during a trading range market (Figure 8.12).1. Fund of Funds. Managers invest in a group of single-manager hedgefunds or manage accounts that use a variety of invest-ing strategies, creating a diversified investment vehicle for their investors.
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2. Market neutral, securities hedging. Managers invest in securitiesboth long and short, attempting on average to have a low net market exposure. Managers generally attempt to select longs that are undervaluedand shorts that are overvalued, theorizing that market volatility will beminimized.3. Special situations. This category is also known as event-driveninvesting. Managers invest when stock and bond prices are expected tochange in a short period of time due to a special situation, such as a stockbuy-back, spinoff, bond upgrade, or earnings surprise, to name a few.Managers take long positions in positive situations and short positions innegative situations.4. Opportunistic. Managers employ a variety of approaches for capitalappreciation. Managers opportunistically move to asset classes or strategies that give what they feel are the best possible returns. An opportunistic manager could also be invested in many different strategies, likevalue, special situations, and distressed securities at one time.5. Market timing. Managers switch among asset classes in an attempt totime various markets. Asset classes used include stocks, bonds, mutualfunds, and money market funds.FIGURE 8.12 The quarterly growth, starting at $1, of the five hedge fundcategories. (Source: Van Hedge Fund Advisors International, Inc.)
Hedge Fund Categories16.0Opportunistic
12.0Market Timing
8.0Special Situations
4.0Fund of FundsMarket Neutral
0.0
87 88 89 90 91 92 93 94 95 96 97 98 99Source: Van Hedge Funds
Year
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AN OPTION STRATEGY FOR TRADING RANGE MARKETSOptions on indexes such as the S&P 500 or the Dow Jones industrials areone of the new derivative investments mentioned in Chapter 5 in the discussion of the theory of contrary opinion. I called options bets onwhether the stock market was going up or down. Buying a put is a betthat prices will fall, and buying a call is a bet that prices will rise. Ofcourse, puts and calls are not really bets; they actually represent something real and tangible.An index option is a contract between two people that exists for aspecific period (the expiration date). A call option is a contract that allows the owner (buyer) of that option to purchase the index at that setprice (called the strike price) for that entire period. If a buyer uses thatcontract to purchase the index, it is said that he or she exercised the option. The seller of that contract must be willing to sell that index to thatbuyer at the fixed price for the life of the contract. Settlements are incash.There are many options on an index, defined by expiration date andstrike price. For an option in which the strike price is higher than thevalue of the index at that moment, the option’s actual value (called its intrinsic value) is zero. This should be clear because who would want topay more for something than it is worth? Even if an option has no intrinsic value, it will always have a time premium value. The time premiumvalue is the price given the option by speculators who are willing to buyit now, hoping the stock or index might rise above the strike price,thereby giving the option a true value. If it doesn’t, the option price (thetime premium) slowly sinks to zero on expiration, and the buyer loseseverything.Let’s look at a real example. On July 13, 2001, the S&P 500 indexclosed at 1,215.64. The call option to buy the S&P 500 at a strike price of1,300 for the next 5 months was priced at 34 S&P points. Who wouldwant to exercise this option, paying 1,300 for the S&P 500 when theycould buy it for 1,215? No one would. We can see, therefore, that the intrinsic value of