open interest and falling prices. Comimodex also considers a dropin open interest along with falling prices to be a bullish factor. The movement of volume istreated in the same manner as open interest and can confirm a bull or bear trend. Anincreasing volume momentum with rising prices is support of an upward move; othercombinations indicate bear trends. -
Added together, the signals are ranked from a strong buy to a strong sell with lesserdegrees in between. The system must be given credit for the quantification and balancingof these elements, which are generally treated as highly interpretive charting techniques.The rules for applying the daily signals to trading combine both the individual strength ofthe signal with the movement of the Commodex trend index. The trend index itself acts asan overbought-oversoid indicator, encouraging profits at specified levels and consideringa position reversal in more extreme situations; stops are placed using the 20-day movingaverage with predetermined band penetrations. Additional objectives are based on the378 PRACTICAL CONSIDERATIONS
 
profits accrued from a trade, with a 50% return justifying a protective stop on part of thepositions, and a 100% profit requiring the liquidation of half the position. These moneymanagement concepts are an important aspect of any system and tend to round out Com-modex.
The Commodex system has been used as an example of combining techniques thathave been studied individually in previous sections. It is important to see that each ele-ment is simple to understand and avoids duplication; it has single and double moving aver-ages (with and without bands), momentum indicators derived from volume and openinterest, an overbought-oversold indicator formed from a combination of all elements,trading stops, and liquidation based on money management and inverse pyramiding.
Combining Trends and Trading Ranges
Trends and trading ranges account for most price movement; a small percentage cannot beidentified. Most traders must decide whether they intend to profit from trend moves orsideways markets and then develop techniques that target that objective. A trend is con-cerned with the. periodic tendency of prices to move in one direction without a limitingobjective, and a trading range is a definition of price containment. The role of time is dif-ferent for the two approaches. The trend is expected to advance with some regularity overtime, while prices within a trading range can move in any direction with varying speed,providing the upper and lower bounds are not violated.
Trading ranges and trends take turns dominating price movement, with the tradingrange most common. Long-term trends are easy to'see, as for example, represented in thebuying power of the U.S. dollar and the Consumer Price Index. When there is no actual oranticipated change in fundamental factors, prices fluctuate in a restricted range, boundedby support and resistance levels. The top of a trading range is often wider than the bottombecause of the inherently greater volatility at higher prices; but even with the broader for-mation, there is a clear point at which prices have gone higher and are no longer withinthe trading range.
It often happens that the two techniques of price trend and trading ranges are in con-flict: The trend is up and a resistance level is encountered, or the downtrend is stopped bya support level. Established support and resistance levels cannot be ignored, neither canamajor trend; it makes’ sense to combine both features. The simplest way is to use the trad-ing range while prices are within that area and follow the trend when prices break outeither above or below (Figure 22-10).
The exact rules depend on the size of the trading range, the speed of the trend, andwhether the support and resistance levels have been established over time. Recent rangeformations offer less of an obstacle than those that have survived for some time. If therange is narrow, a moving average buy or sell signal invariably occurs at the resistance orsupport level and is met with an initial reversal. For a larger range, a medium-speed mov-ing average signal may occur closer to the center of the range and allow some opportunityfor trend profit before resistance is encountered. For very wide ranges, there may be amplelatitude for a moving average to signal entry and closeout without the interference of sup-port and resistance levels. One: method of combining the two techniques is to usewhichever signal is generated, regardiess of the system. The following combinations ofshort position entry and exit are possible for medium to wide ranges:
1. Enter a new short position when the moving average turns down.
2: Enter a new short position when prices enter the sell zone around the resistancelevel. -
3. Enter a new short position when prices fall below the support area, then close outthe short position when the moving average turns up.TRADING LIMITS—A DAMPENING EFFECT 579
 
 
FIGURE 22-10 Combining trends and trading ranges.
 
 
4
Y jew Follow the trend
‘zone _ #f higher prices
    
 
UseTrading tradingrange rangeprinciples
Buyzone
BIS Yj, Sell7;\ zone Follow the trend
if lower prices
 
 
4, Close out a short position when prices enter the buy zone above the support level.5. Close out a short position when prices break through a resistance level moving up.
The same rules apply in reverse for long positions. The advantage of this filteringmethod is that new short trades are not entered at support levels, which causes immediatelosses or prolonged trades of little result.
TRADING LIMITS—A DAMPENING EFFECT
The existence of trading limits in some of the U.S. markets has always been the concern ofnovice speculators who seem convinced that their first entry into the market will result inan adverse locked-limit move, stripping them of their future and happiness overnight.There is no doubt that many people have suffered from being caught on the wrong side ofa move, but trading limits would tend to protect rather than harm them. The limits estab-lished by the exchanges are intended to allow free trading within the normal range of pricefluctuation. While the agricultural markets still have traditional daily limits, the financialmarkets have gone to a system of suspending trading for a short period, then reopeningwith larger limits. If properly established, these limits should rarely be reached. As pricesrise, the volatility of the market increases, and so the limits must be expanded to corre-spond to the new price range. At this point, trading risks become proportionately greaterand margins are raised. :
The purpose of limits is to prevent an immediate reaction to unexpected news frommoving prices to unjustifiable levels. The first reaction to bad news is usually moreextreme than is-realistic, and when proper-assessment of the problem is completed, theresults are rarely as bactas initially thought. Limits also serve to give the losing trader moretime to capitalize the position, or meet a margin call, rather than be forced to liquidate.
Frequency of Limit Moves
Sugar prices, which had a spectacular rise in 1974, can serve as an extreme case of chang-ing volatility. Beginning in 1969, Table 22-4 shows the remarkable price move seen in thefrequency of limit moves.-The contracts shown have no duplicate dates and do not includethe actual delivery month.580 PRACTICAL CONSIDERATIONS.
 
——————TABLE 22-4 Frequency of Limit Moves
 
 
Total Days Percentage ExchangeDays Closing of Limit Range of LimitsExamined at Limit Closes Closing Prices (d!lb)Sep 70 248 0 0 2.91-4.01 50Sep 71 249 0 0 2.74-5.08 50Sep 72 240 18 75. 4.26-9.17 50Sep 73 239 9 3.8 5.44~10.50 50Sep 74 239 40 16.7 7.56-28.15 -50-2.00Sep 75 239 54 22.6 11.51-50.82 1.00-2.00Sep 76 238 3 1.3 12.07-18.65 1.00
 
The obvious conclusion to be drawn from the pattern of the sugar market is that lim-its did not expand quickly enough at higher price levels. In 1975, 22.6% of all trading daysclosed at the limit; at low price levels, the limits were of no consequence. The 1974 priceof sugar increased by 15 times its 1969 price, while the limits only expanded from 50 to200 points, a factor of four. Limits present a problem for a trading system because they arti-ficially alter the volatility of the market. The consolation is that a trading system is uselessin a market that is locked-limit for a week. You might find it enlightening to test your sys-tem ona market and period where limit moves were evident to see their effect on signalsand performance. :
The only realistic way of comparing the effects of limit moves against a limitless mar-ket is to compare the U.S, and London exchanges. Using the May 77 Coffee contract for themonth of February 1977, we can show three separate examples of limit moves in the U.S.contracts and the corresponding London action. Figure 22-11 illustrates the closing pricesof the two markets on the same day. Two problems must be considered: the conversion ofsterling to U.S. dollars, which was fixed at $1.70 for the entire comparison, and the over-japping hours’ of the New York Coffee and Sugar Exchange and the London SugarExchange. The exchange hours may have some difference in the daily price but should notappreciably affect the comparison. .
The first U.S. locked-limit day was on February 7, when the New York coffee prices forthe May 77 contract moved to 230.82 (up 300 points). On the same day, London prices forthe May 77 contract moved from 218.80 to 230.56 (actually 2883 to 3038 sterling). A traderwho closed out his position on the open in the London market would have taken a fill of2850 and a loss of 12.67 cents per pound relative to the U.S. market. The traders lockedintotheir New York position could have gotten out on the open on February 8 at 233.50,a loss of 568 points. Had both the U.S. and London traders waited for the closing prices asshown in Figure 22-9, the corresponding losses would have been reduced to 1176 pointsin London and 318 points in New York.
The second case was on February 17 and 18 when the U.S. market stayed locked at thelimit for 2 days. A trader entering the market in London on the priqs day at 241.91(2187.50 sterling) could have goiten out on the next day at 247.07 (3255.07) for a loss of516 points. The corresponding New York trader would have entered at 246.00 and exitedat 254.50 for a loss of 810 points.
Remarkably, the London coffee prices had moved to 252.04 by the time the New Yorkmarket was trading again. London prices had gained 1013 points during the time that alocked-limit U.S. market gained only 850 points. In both cases, the volatility of the Londonmarket with no limits was much greater than the U.S. equivalent, and the results do notshow any disadvantage to trading limits.TRADING LIMITS—A DAMPENING EFFECT 581
 
 
FIGURE 22-11 Comparing limit moves in U.S. and London coffee markets.
 
fibxO
280
220
 
 
 
OO AN FEB FEB FEB FEB MARm4 8 is om 1+ US. Colfee (May 1977)o——+ London Coffee (May 1977)Converted to lb at el * $1.70® Represents limit closes
 
 
The third case of locked-limit moves began on February 24. On the day prior to the firstlocked-limit day, the U.S. market traded actively even after the London Exchange moved upan equivalent of 698 points. There should have been ample time that day or even the priorday, when the U.S. market traded at the limit but closed lower, for any trader to exit anundesirable position. Figure 22-11 shows the larger moves of the London market peakingand starting down to meet the plodding U.S. prices. The market with no limits has overre-acted to the bullish news by at least 1,000 points. Of course, for traders who didn’t get outof New York coffee soon enough, the overreaction of the London market was not very grat-
ifying.Changing the Rules
Due to the frequency of locked-limit moves during the exceptional periods, and the needto keep changing them as inflation forced prices higher, most exchanges have changed theway daily trading limits are established. At one time, 2n exchange committee was convenedto review limits; now, limits automatically expand to meet conditions. The S&P, along withsome other financial markets, have circuit breakers that cause the market to halt when spe-cific limits are reached. After a short pause they reopen and can trade to new levels beforeanother circuit breaker is activated. At an extreme level, however, the S&P will also stoptrading, putting it in the same situation as New York coffee versus London coffee. The yearshave changed but the problems remain the same.582 Ph-sCTICAL CONSIDERATIONS.
 
The normal policy for agricultural markets is that, following a trading day in whichprices closed at the limit, limits expand to 1% their initial value. They may remain at thislevel for 1 or 2 days, provided prices continue to close at either limit (higher or lower).Limits will then expand to twice the initial range; if a locked-limit move persists, limits areentirely removed for 1 day. After this, or after any day that prices do not close at the limit,the pattern begins again with the initial limit value, Occasionally, the initial value may bealtered by the exchange.
GOINGTO EXTREMES
In 1974, public awareness of inflation caused an overwhelming interest in all forms ofhedging, with large numbers of naive investors purchasing silver and gold as currency pro-tection. Many sophisticated investors turned to the futures markets, which offered leverageon their purchases; some learned how to use the markets themselves and others relied onadvice. con
One investment system that was sold at this time was more of a leveraged substitute forthe purchase of bouillon than a trading strategy. At the time it was published, it had alwaysworked—the sponsor of the system stood. behind it with his reputation. The rules of thesystem were: .
1. Trade silver futures because of their intrinsic value, historic performance, potential,
and fundamental demand with short supply.
2. Use the futures contract between 3 and 7 months from delivery to combine the ad-
* vantages of liquidity and duration.
. Always buy, never sell, because it is always successful.
. Buy whenever you like: Although any sophisticated method can be used, it won’tmatter in the long run—any guess will do just as well. Follow the same method foradding to positions or reentering after closing out a trade.
. Close out the position when there is a profit, not before.
. Meet all margin calls—don’t let the market beat you.
7. Invest $5,000 per contract (5,000 troy ounces). This will allow a $1-per-ounce ad-
verse move (silver was at $4.50 per ounce).
8, Whenever you need reinforcement, reread the reasoning behind this system.
9. Do not let anyone or anything interfere with following this system. ~
a
aw
How did the investors do? It depended on when they started. Entering in the first half of1975, shortly after the system was released, showed individual contract returns rangingfrom profits of 51¢ to losses of 18¢ per ounce. A drop in silver prices then produced lossesof up to $1.02 per ounce for the next 9 months (slightly over 100%), followed by a 2-monthrally, and losses again. This system would have worked from 1979 to February 1980 andthen lost for the next 15 years. An investor following these rules, entering at a chance placewould have had more than a 10: 1 likelihood of losing. Any profit made would: have beengiven back if the investor persisted in following the method.
In trying to understand hew a systen+such as this can have a chance of reaching thepublic, remember the time in which it was introduced. With prices increasing drastically,food shortages, and publicity over the devaluing U.S. dollar, the rationale of. the systemseemed jusiifiable. There was serious talk about leveraged inflation funds using futures.These systems fill an immediate need, without regard to long-term consequences. There isno doubt that, if high inflation rerurns, systems just like this one will reappear. Given thebull market in stocks for the past 29 yeass, it is surprising that more of these systems are notin evidefice. With only small changes in the rine rules for trading silver, we could create ascenario that would be very believable to many people looking to enter the stock market.SIMILARITY OF SYSTEMS 583
 
SIMILARITY OF SYSTEMS
A primary concern of both the government regulatory agency (CFTC) and individualtraders is the similarity of computer-based systems that are used to manage large positions.If the propagation of technical trading systems has similar foundation and testing methods,it is possible that many of them will produce buy and sell signals on nearly the same day.That is, these systems may appear different in their rules and parameters, but they couldbe essentially quite similar—too many people looking at the same markets and using thesame tools. .
First, consider the extreme case in which two systems with the same trend-followingphilosophy have the same profit over the same period of time. Will the signals occur on thesame day? Are they on the same side of the market most of the time? Figure 22-12 showsone combination that has a low correlation given this situation.
System A is a slow trend-following method, which avoids the choppy markets but netsonly a small profit. System B jumps in and out, capturing profits quickly but with frequentlosses. They both return the same profits. System B is on the same side of the market as Aabout 50% of the time because the overall trend was up; therefore, it cannot be negativelycorrelated, but it could have a low positive correlation. If system B were not as fast as inthis illustration, the positive correlation would be greater. As the time periods used for cal-culation become closer, the correlation increases.
If computer-based, trend-following systems with different calculation periods are nothighly correlated, then it is possible to reduce portfolio risk by trading a variety of differ-ent techniques and time periods; however, the reality of the issue may be different fromthe theory. Lukac, Brorsen, and Irvin’ performed such a study. They compared 12 populartrading techniques (mostly trend-following) over 12 varied futures markets. for the years1978 to 1984. Each system was optimized, using 3 years of data, and the best parametersused to trade the next year. The systems selected were
1. Channel systems
a. Closing price channel (CHL)b. MII price channel (MID)c. L-S-O price channel (LSO)
* Louis P Lukac, G. Wade Brorsen, and Scott H. Irwin, Similarity of Computer Guided Technical Trading Systems(CSFM-124, Working Paper Series, Columbia Futures Center, Columbia University Business School, New York,March 1986). Also by the same authors, “Do similar signals from trading systems move prices?” Futures (Novem-ber 1987).
 
FIGURE 22-12 Two trend-following systems with low correlation.
 
 584 PRACTICAL CONSIDERATIONS
 
2. Momentum/oscillatorsa, Directional indicator (DRI) 'b. Directional movement (DRM)c. Range quotient (RNQ)d. Reference deviation (REF)3. Moving averages
a. Moving average with percent band (MAB)b, Dual moving average (DMC)
4, Systems with trailing stopsa. Parabolic Time/Price System (PAR)
b. Alexander's Filter Rule (ALX)c. Combined Directional Movement and Parabolic Time/Price System (DRP)
The study used three measures to test system similarity:
1, The percentage of the time that systems are on the same side of the market (long orshort) :2. The percentage of buy or sell signals that occurred on the same day, or within a few: days of one another3. The correlation of aggregate monthly portfolio returns
The results show a significant positive correlation in the system profitability (Table22-5). However, there is no pattern that shows that one particular type of system is notablymore correlated than others. The Parabolic and Directional Parabolic systems are most sim-ilar because one is based on the other.
Only four of the systems were significantly profitable: CHL, MII, DRP, and DMC. Thecorrelations of those systems do not seem any more significant than others that were notprofitable. In Table 22-6, the percentage of trades that occur on the same day is very low. Amore informative comparison is seen in Table 22-7, which tallies the percentage of daysthat each system held the same position. This last table is a practical way of finding the per-formance correlations.
 
TABLE 22-5 Correlations of Aggregate Monthly Returns from [2 Systems
 
 
 
Trading SystemSystem CHL PAR DRM RNQ DRP Mii LSO REF DMC DRI MABPAR 0.57 =DRM 0.72 0.61RNQ 0.70 041 0.70DRP 0.65 0.8! C79 0.57Mil 0.75 0.54 0.87 0.73 0.67LsO 0.59 0.43 0.53 0.68 0.54 0.70 ooREF 0.55 0.37 0.57 0.56 0.52 0.54 0.60DMC 0.72 0.41 0.88 0.78 0.55 0.74 0.58 0.57DR O71 O42 0.69 0.77 0.55 0.70 0.59 0.66 0.64MAS 072 0.55 0.75 0.74 0.69 0.69 0.63 0.60 0.78 0.72AX 0.58 0.55 0.52 0.55 0.57 0.57 0.58 0.51 0.52 0.56 0.57
 
a ee
Ail coefficients significant at the 0.01% level with the exception of REF and PAR coefficient, which is significane at the 0.05% level,
Source: Reprinted with permission of Futures Magazine, 250 $. Wacker Drive, #1 150, Chicago, iL 60606, (November 1987).SIMILARITY OF SYSTems 585
 
 
TABLE 22-6 Percent of Trades That Occur on the Same Day
 
 
 
Trading SystemSystem CHL PAR DRM = RNQ__ODRP. MIL Lso REF DMC DRI MABPAR i*DRM 2 IRNQ 22" 9 15DRP 30% 93 48*F 10)Mit 20* 15 10 28" 17Lso 20" 13 17 27 18 236REF 12 7 7 if 9 12 14DMC 16 6 8 238" 6 12 18 19*DRi 18 9 14 3B 19 32%" 22" 15 25"MAB 28 18 23 23" 7 18 25 i Io* 23ALX 12 20* 12 19* 20* 9 17 10 10 16 17
 
Percent of trades that occur on the same day by each pair of systems. Significance assuming a binomial distribution with * denoting 95% con.fidence limits and ** denoting 99% confidence limits.
Source: Reprinted with permission of Futures Magazine, 250 S.Wacker Drive, #1150, Chicago, !L 60606 (November 1987).
The study concludes that computer-based systems trade on the same day significantlymore often than would randomly be expected, but the actual percentage of trades thatoccur on the same day is small. These systems have the potential to move market prices,but the trades do not often occur at the same time. One must be concerned, however, iftrend-following systems are holding the same position 75% of the time, they must competewith each other when they exit, even if that occurs over a period of a few days. Trading sig-nals that occur at the exact same time may not be necessary to push the market.
Correlation When You Don’t Need It
There is often a theoretical answer and a practical one to the same question. There is nodoubt that a variety of trend-following systems generate trading signals at different price
 
TABLE 22-7 Percent of Trading Days Systems Hold the Same Positions
 
 
 
Trading SystemSystem CHL PAR DRM RNQ  ODRP Mil LSO REF DMC DRI MABPAR 70 — ,DRM 82 76 -RNQ 75 61 2B :DRP 68 83 75 59 7Mn 82 69 80 75 65Lso 73 58 71 73 37 73 ~REF 72 57 69 69 55 72 69DMC 8i 62 77 79 6! 79 76 78DRI 70 56 68 72 54 7 69 67 3MAB 65 54 66 62 53 63 61 57 65 59ALX 72 64 71 68 59 2B 65 67 73 63 58
 
Percent ofthe trading days each pair of systems ison the same side of the market (long or short) atthe same time. All coeficiegs are sgnicant, assuming a binomial distribution with 99% confidence limits,
Source: Reprinted with permission of Futures Magazine, 250 S. Wacker Drive. #1150, Chicago. IL 60606 (November 1987).586 PRACTICAL CONSIDERATIONS
 
levels, some nearer to each other and some farther away. During active, high-volume trad-ing periods, a few of these systems can give buy signals without causing prices to move andother trending systems to be triggered. During sessions with light volume, it is more likelythat a system traded with a large position will cause piggy-backing by others, resulting in aprice spike that disappears once all the systems have kicked in.
The worst case is a price shock. Although not caused by systems, all trend systems notholding a position in the direction of the shock will get signals to enter at the same time,the result of a large price jump. The correlations mean very little and only diversificationusing different trading philosophies, rather than time periods, would help. Although rela-tively infrequent, large price shocks can be fatal. When designing your trading strategy,keep the practical issues of diversification and risk management always in sight.| 23
Risk Control
 
with each trade and continuing until a portfolio of different trading methods is cre-
ated. Systems have losing streaks that will ruin any investor with inadequateresources and poor timing; a speculator must decide the initial capitalization, the marketsto trade, and when to increase or decrease leverage. There are risks that can be controlledor reduced, called systematic risk, and another called market risk, that can take the formof a price shock and can never be eliminated.
This chapter tries to cover a broad range of topics relating to risk, including individualtrade risk, leverage, portfolio diversification and allocation, price shocks, and catastrophicrisk. It is not possible to say that one is more important than another. In a specific situa-tion, any one of the areas discussed may be the answer to preventing substantial loss. Thefirst part of this chapter discusses capitalization and shows why many traders will be suc-cessful for months and then lose everything in only a few days. It will explain the choicesin leveraging and offer alternatives of less risk, The last section analyzes when a system isperforming properly and when it is not living up to its expectations.
Risk control begins with a trading philosophy; the most common is called conserva-tion of capital. Iv is the assurance that the investor has been given the most opportunitiesfor success, which usually translates into keeping losses small. This is often accomplishedby allowing only small losses per trade or using a trend-following system. Once a trendposition is established, it is held as long as prices continue in the direction of the position,it is closed out when the trend changes. The resulting performance profile is one of morefrequent small losses and fewer large profits. -
A trading system alone will not assure success without proper risk control beginning
RISK AVERSION
Daniel Bernoulli, a famous mathematician, proposed a theory of utility in 1738 that distin-guished between price and value, where price is equal for everyone, but value (utility)depends on the individual making the estimate and their circumstances."
Bemnoulli’s approach defined a concept of diminishing marginal utility, shown in Fig-ure 23-1, which indicates that as wealth becomes greater, then the preference for morewealth diminishes. In the lower jeft part of the chart, where the investor has a small networth, the likelihood of accepting risk is much higher, although the magnitude of the riskis still small. When risk becomes greater, even proportional to reward, all investors becomecautious. Bernoulli’s graph shows the.curve beginning at Zero and moving up and to theright in a perfect % circle, ending horizontally where risk is no longer attractive. Thisimplies that people are risk-averse. Most peopie are not interested in an even chance ofgaining or losing an equal amount. Other theories that have been proposed are that themarket maximizes the amount of money fost, and the market maximizes the number of los-ing participants. All of these concepts appear to be true and are very significant in devel-oping an understanding ef how the market functions.
' Peter L, Bernstein, ed., Te Portable MBA in Investment (John Wiley & Sons, 1995, p. 37).588 RISK CONTROLer
 
FIGURE 23-1 Changes in utility versus changes in wealth.
 
  
{increase in Utity
   
   
in Utility
CorrespondingUtility
in Wealth
  
 
InitialWeaith
 
Source: Peter Bernstein, The Portable MBA in Investment 1995, p. 38.© 1995 Peter Bernstein, Reprinted bypermission of John Wiley & Sons, Inc. '
Risk Preference
The Bernoulli theory of utility is general, but each investor has their own unique objectivesand attitudes toward risk. Some of the participants in futures markets would like to ke