support and resistance levels cannot be ignored, neither can amajor 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.
 
i|;
TRADING LIMITS—A DAMPENING EFFECT 3879
 
 
FIGURE 22-10 Combining trends and trading ranges.
Yd 5 LY)
ABuy Follow the trend| ‘Zone if higher prices
         
    
 
SellzoneUseTrading anrange rangeprinciples:S }By5 Zoi) ZONEGE 1YW, Sel, Follow the trendif 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 bac-as 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.
 
it Moves
 
Frequency of Li
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 datés and do riot includethe actual delivery month. 
 
 
 
 
 
 
 
 
 
 
   
 
 
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. seals ustcorive ey 124contracts and the corresponding London action. Figure 22-11 illustrates the closing prices we Daas Care tay 1977)
of the two markets on the same day. Two problems must be considered: the conversion of ‘Converted to el at £1 = $1.70sterling to U.S. dollars, which was fixed at $1.70 for the entire comparison, and the over- - © _ Represents limit closerlapping 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 not -appreciably affect the comparison. -
‘The first US. 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 trader@who closed out his position on the open in the London market would have taken a fill of2850 and a joss of 12.67 cents per pound relative to the U.S. market. The traders lockedint their 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 priac day at 241.91(3187.50 sterling) could have gotten 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. to review limits; now, limits automatically expand to meet conditions. The S&P, along with
Remarkably, the London coffee prices had moved to 252.04 by the time the New York some other financial markets, have circuit breakers that cause the market to halt when spe-market was trading again. London prices had gained 1013 points during the time that a tific limits are reached. After a short pause they reopen and can trade to new levels beforelocked limit U.S. market gained only 850 points. In both cases, the volatility of the London another circuit breaker is activated, At an extreme level, however, the S&P will also ‘stopmarket with no limits was much greater than the U.S. equivalent, and the results do not trading, putting it in the same situation as New York coffee versus London coffee. The yearsshow any disadvantage to trading limits. have changed but the problems remain the same.
200JAN FEB FEB FEB FEB MAR7 oF 8 is 22 V
580 PRACTICAL CONSIDERATIONS | TRADING LIMITS—A DAMPENING EFFECT $31eeTABLE 22-4 Frequency of Limit Moves FIGURE 22-11 Comparing limit moves in U.S. and London coffee markets.Total Days Percentage Exchange i <bDays Closing of Limit Range of Limits | 300Examined at Limit Closes Closing Prices (dilb) !Sep 70 248 0 0 2.91-4.01 50 jSep 71 249 ° 0 2.74-5.08 50 |Sep 72 240 18 75 4.26-9.17 50 280Sep 73 239 9 38 5.44-10.50 50 ‘Sep 74 239 40 167 7.56-28.15 50-2.00Sep 75 239 s4 226 11,51-$0.82 1,00-2.00 1Sep 76 238 3 13 12.07-18.65 1.00 : 260‘The obvious conclusion to be drawn from the pattern of the sugar market is thar lim- |its did not expand quickly enough at higher price levels. In 1975, 22.6% of all trading days : 20closed 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- ificially alter the volatility of the market. The consolation is that a trading system is useless 5 a0ina 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 signals tand performance. tThe only realistic way of comparing the effects of limit moves against a limitless mar- i -
‘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.
intact ek ater tabi
Changing the Rules
\.ehabhanen = &
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, an exchange committee was convened
a
   
fit
 
 
582
 
PrCTICAL 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.
GOING TO 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.
One investment system that was sold at this time was mofe 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 the
system 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.
3. Always buy, never sell, because it is always successful.
4, 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.
5. Close out the position when there is a profit, not before.
6. 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. — ~
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 how a system-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. dollas, the rationale of. the systemseemed justifiable. 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 returns, systems just like this one will reappear. Given thebull market in stocks for the past 20 yeas, it is surprising that more of these systems are notin evidefice. With only small changes in the nine rules for trading silver, we could create ascenario that would be very believable to many people looking to enter the stock market.
sine bt
 
 
 
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. MI price channel (MID
¢. 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, Spstems 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 Grshort)2. The percentage of buy or sell signals that occurred on the same day, or within a fewdays 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 12 Systems
 
 
 
Trading SystemSystem CHL PAR DRM RNQ DRP Mit LsO REF OMC DRI MABPAR 057 =DRM 072.6RNQ 0.70 O4t 0.70DRP 0.65 0.81 C79 0.57Mil 0.75 0.54 087 0.73 0.67LSO 0.59 0.43 0.53 0.68 0.54 0.70 “7REF 055 037 C57 0.56 «0520.54 0.60DMC 0.72 0.41 0.68 0.78 0.55 0.74 0.58 0.57DRI 0.71 O42 0.69 0.77 0.55 0.70 0.59 0.66 0.64
MAB 072 055 075 C74 069 0.69 063 060 0.78 072
ALX O58 O55 042 O55 O57 O57 O58 O51 O52 056 057
Ail coefficients significant at the 0.01% level with the exception of REF and PAR coefficient, which is significant at the 0.05% level.
 
Source: Reprinted with permission of Futures Magazine, 250 S. Wacker Drive, #1150, Chicago, IL 60606, (November 1987).
 
 
i|iii|}
SIMILARITY OF SYSTEMS ses
SSeS
TABLE 22-6 Percent of Trades That Occur on the Same Day
Trading System
 
 
System CHL PAR DRM  RNQ = DRP__ Mil tsoO. REF = DMC) DRI MAB.PAR 19*
DRM 2s 2
RNQ 22" 9 ts
DrRP 30 93" 4g 10
Mil 20* 1s 10 28" 17
Lso 22 13 7 27 18 23
REF 12 7 7 9 12 14
DMC 16 6 8 28" 6 12 18 ise
ORI 18 9 i4 3a" 10 32" 22 15 25"
MAB 23 18 23 234e TB ase tL 19* 23"
ALX 12 20* 12 I9* 20* 9 17 10 10 16 7
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, IL 60606 (November (987)P
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 ItThere 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 Hoid the Same Positions
 
 
 
Trading SystemSystem CHL PAR DRM RNQ  DRP Mil  LSO_ REF = OMC_—ORI_ MABPAR 70 —DRM 82 76 -RNQ 75 él 73DRP 68 83 75 59 7Mn 82 69 80 75 65.Lso 3 58 7 73 57.73 >REF 72 37 69 69 55 7269DMC BI 62 7 79 61 79 «76 78DRI 70 36 68 72 S47 667 23MAB 65 54 66 62 83 63 6t 87 65 59ALS R 64 7 63 5973 65 67 73 63 58
aPercent of the trading days each pair of systems is on the same side of the market (long or short) at the same time. All coefficiegss are signifleant, assuming a binomial distribution with 99% confidence limits + :
Source: Reprinted with permission of Futures Mogazine, 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 timethe 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. ,
Soe eat
| 23
Risk Control
 
trading system alone will not assure success without proper risk control beginning
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. It 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. .
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."
Bernoulli’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 ieft 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. Thisimnplies that people are risk-averse. Most people 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 lust, 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 of how the market functions.
' Peter L. Bernstein, ed., The Portable MBA in Investment (John Wiley & Sons, 1995, p. 37).ip
 
5388 RISK CONTROL,
 
FIGURE 23-1 Changes in utility versus changes in wealth.
 
CorrespondingUtility
    
/\ cms | rest
 
 
 
InitialWealth
 
Source: Peter Bernstein, The Portable MBA in Investment 1995, p. 38.© 1995 Peter Bernspermission of John Wiley & Sons, Inc,
 
Reprinted by
 
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 keeprisks low and returns steady; others would like to risk all of their capital for a chance at the“big move.” This trait is called the investor's risk preference. The risk preference or utilityof an investor for a specific venture (in this case a trade) can be found by adding theexpected value of the investor's utilities or preferences for the various outcomes of thatevent,
P=WiPitWrPrt*+WrPy Where F wj=1
where there are 1 possible outcomes. The weighting factors may be the results of personalbias or may be the calculated probabilities of each outcome. For example, a golda likely profit of $4,000, with a risk of $1,500. Adjust the reward values by di1,000. If the probability of success is 60%, the total utility of the trade is:
  
P(trade) = 0.60 x 4 + 0.40 x (-1.5) =1.8 -
If the probability of success were increased, the utility P would increase linearly. Butinvestors do not feel the same about different rewards. Given a scale of 0 to 100 (negative(© positive reaction), an investor may rank the 60% chance of a $4,000 profit and a 40%chance of a $1,500 loss as 2 $5. ff the reward is increased fo $8,000 while the risk remainsat $1,500, the investor might raise the preference of the trade to 80, aithough the utilitywould be 4.2, more than twice as large.
‘The various patterns of a cusve drawn through the computed utilities represent therisk preference of the individual. Figure 23-2 shows the curve formations progressing fromextreme risk aversion to extreme risk seeking. As the risk increases in (1), she trader is lesslikely to participate in the trade; in (3), there is equal chance of taking the trade at all risklevels; and in (5), the trader is more likely to enter a trade that has higher risk.
 
  
ja1i4i
 
LIQUIDITY - 589
 
FIGURE 23-2 Investor utility curves.
Concave downward Linear Concave upward
Me
(1) Extreme (2) Moderate (3) Neutral (4) Moderate (5). Extremerisk averter risk averter to risk risk seeker risk seeker
isk-——>>
Increasing Fi
Source: Rj. Teweles, C.V. Harlow, and H.L. Stone, The Commodity Futures Game: Who Wins, Who Loses, Why?(McGraw-Hill, New York, 1974, p. 133). © 1974, Reprinted by permission of The McGraw-Hill Companies.
Common Sense
Risk control is as much an issue of common sense as it is complex rules and mathematics.Most of the chapter that follows shows how various measurements, diversification, andleveraging techniques can reduce risk; however, successful traders have