lied to Forecasting Financial Market Trends,” Market Technicians Associa-tion Journal (May 1985, pp. 91-131).ARTIFICAL INTELLIGENCE METHODS 417
 
—FIGURE 15-9 Specific buying and selling days.
 
Selling days1
       
Selling days—
Buying daysPrice movessatisfying Buying days
conditions
 
 
3. The direction of changes in trading volume4. A 10-day momentum
By entering a broad selection of indicators and trying to avoid duplication, the com-puter can find unique values for combinations of indicators that primarily occur during thedays selected as buy and sell periods. Ideally, all buy signals should occur when one indi-cator, or the value of combining indicators, exceeds a specific value. For example, all buysignals occur when the average value of the RSI and the market sentiment (contrary opin-ion) is below the 10% level. However, having all buy signals occur here is not enough. Poorsignals may appear at this level, which cause large losses. The perfect system will have nolosing signals occur in this zone.
Unfortunately, in the real world there are no perfect solutions. The trades that are sig-naled by the combinations of indicators will have to be studied for net return, risk, andother performance criteria. However, the technique of setting up classes of indicators, buyand sell days, is a new and valid approach to system development. It is analogous to themultiple regression method used by econometricians to find the relationship between sta-tistics and prices. Although the econometricians use inflation, supply, interest rates, and soforth, pattern recognition can employ technical indicators and discrete patterns to forecasta buy or sell day. ~ :
ARTIFICIAL INTELLIGENCE METHODS -
Artificial intelligence refers to a computer process that performs an operation corre-sponding to, or approaching, human thinking. This is intended to distinguish it from sim-ple pattern recognition, with which it is often confused. The state of the art in artificialintelligence is the separation of two ideas. The collection of information that is stored inthe brain has been termed the knowledge base. This is distinguished from reason, rules,and logic, called the inference engine. These ideas are not very different from the databaseand trading strategies that are discussed here. - .
The closest practical approach to artificial intelligence is heuristic programming. ThisTefers to computer learning in very much the same way as finding the way out of a maze.The computer starts with rules relevant to the problem, then records the successful and4\8 PATTERN RECOGNITION
 
unsuccessful experiences> Eventually, it has a complete table of what to do for each situa-tion, or at least a table of probable solutions. This is a realistic, intelligent approach whenthe same events can be expected to recur in the same way. It does not help in new situa-tions without the added complication of incorporating extrapolation, basic relationships(e.g., price level to volatility), and other forms of expectations.
The danger of the heuristic approach to pattern recognition is that it may continue todefine extensions of combinations of patterns that have already produced inconsistent orpoor results. Allowing the computer to identify a limitless collection of patterns is justanother case of overfitting, but this time at a highly sophisticated level.
Heuristic programs have improved current technology in searching, optimization, andgame-playing strategies; however, they are not readily available. There is no doubt that thistechnique will be quickly absorbed into trading strategies as it develops.° Those readersinterested in the types of methods considered to be in the category of artificial intelligence,such as neural networks and genetic algorithms, should refer to Chapter 20 (“AdvancedTechniques”).
® Two books of interest that represent the state of the art in heuristics and game playing are Judea Pear!, Heuris-tics (Addison-Wesley, Reading, MA, 1984), and M.A. Bramer, Computer Game-Playing: Theory and Practice (Hal-sted Press, New York, 1983).| 16
Day Trading
 
niques of time of day and daily patterns, discussed in such rigid form in Chapter 15,
are put to use by the day trader. Day trading requires extreme discipline, excellentplanning, anticipation, and concentration. The need for a fast response to changing situa-tions tends to exaggerate any bad trading habits; as in other fields, the shorter the responsetime, the greater the chance for error. In this chapter, we will extend the idea of day trad-ing to systems and methods that may also be held overnight, but expect to limit the tradeto about 24 hours.
To keep mistakes to a minimum, each day's strategy must be planned in advance. Itshould focus on the most likely situations that might occur based on the nature of the cur-Tent price movement. There should also be a contingency plan for the extreme unexpectedmoves in either direction. Making spot decisions during market hours will cause more fre-quent errors.
Computers have caused the number of day traders who rely on systems to increase,and have created an entire class of screen traders. The steady increase in automatedexchanges, led by Germany’s DTB and followed by France’s conversion of Matif, is sendinga strong message that electronic trading will dominate the future. The availability of intra-day price feeds and system development platforms, such as Omega’s TradeStation, havegreatly increased the number of day-trading participants. Only 10 years ago the best onecould expect was to display standard indicators and moving averages on a real-time pricechart. Now you can fully program complex trading strategies that combine more than onemarket and more than one time frame into a single package and display buy and sell sig-nals on the screen as well as record a historic log of trades. All of these tools have greatlyincreased competition among individual and commercial traders.
For the arbitrageur, computers have had an even stronger impact. Sophisticated sys-tems at banks and large financial institutions consolidate data feeds that bring currenttransactions on every type of interest rate vehicle in every maturity and major currency.Analytic programs can find issues that are outliers and show which combinations (calledstrips) can produce a riskless profit. For the individual trader, few of these opportunitiesare available, although they add liquidity to the market. Individuals, however, find it mucheasier to create spreads of different deliveries within the same market as well as spreadbetween two related products. Stock traders can create sector baskets or look for perfor-mance differences within a sector. Spread trading and formulated values, such as theenergy crack or soybean crush, can be improved using similar displays. Many of the oppor-tunities that now seem so easy to see would previously have been missed. This faster, moresystematic response to the market allows traders to improve profits and reduce risk in anyday-trading method.
A day trade is a position entered and liquidated during a single trading day. The tech-
IMPACT OF TRANSACTION COSTS
Transaction costs are the greatest deterrent to day-trading profits. The failure to executenear the intended price, plus the commission costs, can remove a large part of potential420 DAY TRADING
 
profitability and even turrrexpected profits into losses. An aspiring day trader has two waysof improving performance: by paying lower commissions and by careful selection of oppor-tunities. Table 16-1 presents the percentage relationship of moderate transaction costs tothe maximum daily price move. The average dollar volatility for the years 1990 through1996 is shown next to the percentage represented by a $100 transaction cost. In general,$100 is a modest value for the combination of commissions and slippage, and traders wouldbe very pleased to extract an average profit of one-half the daily volatility. A practicalapproach would therefore use twice the percentage effect of a $100 cost shown here.
Realistically, a day trader would choose the index markets, more volatile currencies,and long-term interest rates as their best opportunity for profits. Corn represents the leastdesirable market because very low volatility leaves more risk than opportunity. Although a$100 transaction cost may seem high for this market, a $20 commission and slippage equaltoa minimum move of 4¢, or $12.50, totaling $45, would be the smallest possible costs.An occasional fast move in the market, based on unexpected economic news, or largeorders entering at one time, must result in a larger number, raising the average.
To keep dollar volatility of a futures contract to a level acceptable by most traders,exchanges have been forced to resize contracts, specifically stock index markets, as overallshare values have climbed. During 1997, the S&P was reduced from $500 per basis pointto $250, and the FTSE-100 from £25 to $10. In 1998, the French CAC40 contract was.cutto 25% of its previous size. This increases the relative size of transaction costs.
Liquidity j
The importance of liquidity is magnified in day trading. Execution slippage of $100, mea-sured as the difference between the system price, or Market Order price, and the actualfilled price, will have little impact on a month-long trade netting $2,000; however, it willbe critical for a day trade with a profit objective of under $300. The selection of day-tradingcandidates begins with those markets of greater volume. Whether one contract or 1,000, a
 
TABLE 16-1 Volatility and Liquidity, U.S. Markets,
~ 1990-1996
Market $Volatility %$100  *Cotton 540 18.5
Corn 163 61.3Soybeans 405 247Australian dollar 353 28.3British pound , 848 118 —Canadian dollar ~ 291 34.4Deutschemark 703 14.2Japanese yen 869 15
Swiss franc 975 ~ 10.3Gold 3ll 32.2High-grade copper ae 238Crude oil 454 22.0Heating oil 518 19.3
S&P 500 2,184 4.6NYSE Composite 1,144 . 87Treasury bills 160 625Treasury notes "568 17.6
Treasury bonds 764 13.1IMPACT OF TRANSAL riON COSTS 421
thinly traded market produces slippage that will cut sharply into profits. In choosingamong index markets that usually offer the greatest volatility and profit potential, you arealways safest with the markets that combine the highest volume and highest volatility.
Occasionally, markets with light volume show larger price moves than similar marketstraded on other exchanges. Traders will be tempted to profit from these moves but willconsistently find that the execution of an order at the posted price is elusive. The reality oftrading these markets is that a Market Order is not advisable due to the thinness of the trad-ing, a Limit Order may not get filled, and a spread is not quoted at anything resembling theapparent price relationships that you see on a quote screen; there is no real way to takeadvantage of these perceived profits. If an execution succeeds, exiting the position still hasthe same problems plus some added urgency.
Missed Orders
Because the profit objective, projected daily range, holding time, and end-of-day con-straints all put limits on a day trade, there are situations in which the market jumps after anews release and you cannot get filled anywhere close to your intended price. With mostof the potential profit gone before you enter the order, it would not be surprising to sim-ply skip that trade. These missed orders, called unables, can add up to a large part of yourprofits; at the same time they never reduce your losses.
Some markets are prone to more unables. For the energy complex, heated military orpolitical activity in the Mid-East can cause a prolonged period of very erratic price move-ment, resulting in as much as 20% unexecuted trades during a 1-month period. If we con-sider the normal profile of a short-term trading system as having an average net profit of$250, an average loss of $150, and a 50% frequency of profits, we expect a profit of $5,000for every 100 trades and a reasonable profit-to-loss ratio of 1.66. If, however, there are 10%unables, that missed opportunity must come from the profits; if the market was moving inthe opposite way, you would get all of your positions filled. Then 10% of the profitabletrades means 5 trades out of every 100 for a total of $1,250 missed. This reduces the totalprofits to $4,750 and the profit factor to 1.50. It may turn a marginal trading strategy, orone with small profits per trade, from a profit to a loss.
Price Ranges
The average daily range (not the true range) shows the maximum potential for a singleday-trading profit. Some markets, such as gold and corn, combine a lack of liquidity with anarrow daily range and are easily disqualified from a day trade opportunity. Eurodollarshave extremely high volume but very little movement; therefore, they are also not a goodcandidate for day trading. When volume is combined with volatility, the world index mar-kets, followed by the currencies and long-term interest rates, are shown to be the bestchoices. Energy markets represent the next tier, grains remain active, and other marketshave far lower volume.
Day traders may find that those markets with traditional daily trading limits present aproblem during high-volatility periods. Day trading does best in markets that have wideswings not deterred by exchange limits; a single locked-limit move can generate a loss thatoffsets many profitable day trades. High volatility and Jocked-limit moves present a contra-diction for day trading. Rules that provide for expanding limits have greatly helped reduce thefrequency of locked-limit days; however, traders must always be on guard for this situation.
Estimating Slippage Costs
1f you know the cost of slippage, you can do a much better job selecting the markets totrade and have a realistic appraisal of your trading expectations. The factors that make up422 DAY TRADING
 
slippage are volatility, overall market volume, current market activity, and the size of theorder being placed. Of these items, current market activity is the most difficult to record,because it requires some estimation of volume as it accumulates throughout the day. Whileactual volume is not available for most markets, a reasonable approximation can be madeusing tick volume, the number of price changes during a fixed interval. In general, tick vol-ume is directly proportional to actual trading volume; during periods of greater activity,both contract or share volume will increase along with the number of price changes.
If you have carefully recorded the order price, execution price, volatility daily bigh -low), daily volume, time of day, and tick volume, you can find the importance of each fac-tor and estimate the slippage for any trade by applying the model:
Actual slippage at time T= ao + a X volatility + a, x daily volume +4; X current activity at time T + a4 x size of order
By creating a spreadsheet of values for all trades, you can solve for 4, @;, @2, 3, and a4, andthen estimate future slippage at any time T during the day, given the current volume andorder size. This approach was taken in 1992! for large Stop orders using a ratio of ordersize to current market activity. The results, shown in Table 16-2, show: that slippage wasvery modest for most markets. The far right column gives the slippage likely at the 5% level;that is, there is only a 5% chance of having slippage greater than $135 per contract forsugar, combining both entry and exit. Commissions were not included. The unusuallylarge “worst” loss in Treasury bills was confirmed as correct.
Price Level
Continuing volatility is most common in markets that are at abnormally high price levels.Bull markets are followed by bear markets, and the combination creates sustained activity.Prices that are volatile at low levels are most likely to be at the end of a decline and can bereturning to previous, less volatile patterns. The agricultural markets, when carryover
1 Thomas V. Greer, B. Wade Brorsen, and Shi-Miin Liu, “Slippage Costs of a Large Technical Trader,” TecbnicalAnalysis of Stocks & Commodities January 1992).
 
TABLE 16-2 Slippage (Loss) for Stop Orders (Slippage in Dollars per Contract)*
 
5% Chance— of Worse thanMarket Average Best Worst St Dev on Entire TradeWorld sugar 13.63 11.20 200.20 33.71 135Coffee 438,13 -22.50 | 168.75 48.44 (94Pork bellies 38.49 12.00 (68.00 42.22 169Soybean meal 14.34 0.00 60.00 21.46 86Heating oil 37.35 -17.50 10939 33.58 134Japanese yen 18.53 12.50 14250 | 28.26 USDeutschemark 18.06 0.00 162.50 33.67 135‘Treasury bills 62.86 0.00 700.00 139.51 558Copper 25.70 11.36 62.50 24.15 7Platinum 77.92 $7.86 280.00 85.68 343Gold 65.80 0.00 410.00 9172 ~ 387
 
*Source: Thomas V, Greer, 8. Wade Brorsen, and Shi-Miin Liu, "Slippage Costs of a Large Technical Trader.” Technical Analysis of Stocks & Commodities (January 1992).APPLICABILITY OF TRADING TECHNIQUES 423
 
stocks are increasing, show reduced volatility. Many experts have theorized that the highinterest rate yields seen in the 1980s, as well as the high precious metals prices, are a veryunusual event not to be repeated often.
Some markets do not have a high or low price in the normal sense of a physical com-modity; therefore, they do not contain volatility patterns directly proportional to pricelevel. For example, foreign exchange markets have low volatility when they are at levelsperceived as the fair value or equilibrium. Prices increase in volatility when they moveeither up or down from this level, because any change away from the norm is consideredunstable. '
Crude oil represents a different phenomenon because it is a controlled market. Whilecurrencies may become volatile as they move away from equilibrium, they will becomequiet at a new price if that is perceived as reasonable by the market. This is not the casewith oil, because the producing countries continue to drive prices back to their target lev-els by controlling the supply. Therefore, the farther prices decline from the producers’desired price, the more of a struggle exists between fair value and controlled price, result-ing in higher volatility. The dynamics of higher oil prices are similar to other physical com-modities. The day trader must always seek opportunities in potential volatility.
APPLICABILITY OF TRADING TECHNIQUES
Most traditional methods of technical analysis, in particular trend-following systems, arenot used for trading intervals of less than 3 days; however, the price fluctuations duringthese shorter periods are nearly all technical. An economic analysis of supply and demandcannot be relevant over such a short time span; that approach can only be used for estab-lishing longer-term trading policy. Other than the immediate reactions to overnight cashmarket movement, anticipated daily price changes based on political events and weatherhave not been successfully measured; however, techniques used for day trading can beapplied to slightly longer periods of a few days. The principles used in these time framesare very different, and the number of data points used in the calculations reflect on thefinal reliability. For example, a 3-day daily moving average relies on only three data pointsfor its decision of the direction of the trend; therefore, it will be very erratic.
Both day trading and short-term trading are concerned with timing to improve entryand exit points. The most common way to accomplish this is by a simple form of patternrecognition based on values relevant to the short time frame. From the floor trader’s view-point, only the most obvious recent key levels are important. Today’s price movements arecompared with today’s opening price, high and low, yesterday's closing price, yesterday'shigh and low, last week’s high and low, very memorable older support and resistancepoints, and finally, life-ofcontract high and low. When the same price satisfies more thanone condition, there is greater confidence in the importance of that point.
The importance of noise is also very different for the day trader and the trend follower.Noise, the underlying erratic movement of prices, is not a significant issue for the positiontrader looking to follow interest rates to high levels over the next year. But it is very impor-tant for the day trader, because the trend component of price movement is very small overa 24-hour period compared with the noise. This makes it impossible, using the ordinarytrend-following tools, to decide whether a move up over 15 minutes will begin a tend orwhether it is simply part of the more common market noise.
Time-of-Day Patterns
Time-of-day and short-term patterns are combined in the most popular forms of day trad-ing; the types of patterns have been discussed in Chapter 15. There are natural occur-rences during the trading day that make certain times more important than others. The424 DAY TRADING
 
opening gap and the continuation of that direction usually take the first 15 to 20 minutesof the trading day, as does the reaction to the U.S. economic reports that are released at7:30 a.M. in Chicago. After that, a price reversal occurs and a trading range is established,which lasts until the middle of the session. The midmorning period, which may marginallyexpand the initial trading range, tends to include low volume because many of the ordersoriginating off the floor (called paper) are exhausted near the open; floor traders take thisopportunity for a break, further reducing liquidity.
Following midday, activity steadily increases and the existing daily range is tested. It iscommon for most day traders to buy the bottom of the range and sell the top. A break ofeither support or resistance after midday is considered a major directional change; tradersquickly shift to the direction of the breakout with the expectation of holding that positionfor the balance of the day. A more thorough analysis of time is shown in Figure 16-1. Thischart, created by Walt Bressert, uses the important recent highs and lows and is very spe-cific about relationships between the developing range, the previous day’s range, and thetime of day. Readers may want to compare Bressert’s relationship with those found inChapter 15. Intraday highs and lows that correspond to key levels found on charts—suchas channel support and resistance, and head-and-shoulders objectives—are also likely tohave increased importance.
Intraday versus Overnight Price Ranges
Holding a position overnight involves margin and, above all else, greater risk. It-alsoincreases the opportunity for larger profits. In moderately active markets, the opening gap,the difference between the prior close and the next open, can be one-third to one-half thesize of the normal trading range. Markets that are traded in one time zone but reflect thebusiness of a completely different geographic region, have larger systematic gap openings.For example, the Nikkei 225 is traded at the Chicago Mercantile Exchange, but the Nikkeireflects the value of the Japanese stock market. While the day session in Chicago is openfrom about 7:00 A.M. to 3:00 pM. local time, the time in Japan.is 10 hours earlier, 9:00 pM.to 5:00 A.M., a period when there is no business activity in Asia, When Chicago opens, itmust immediately reflect the price of the previous closing session in Japan; therefore, itgaps to that level. This same situation happens to a lesser degree for European currencies,which are actively traded on Chicago’s IMM. When those markets open at 7:20 a.M., Europeis coming back from hinch and all local economic news has already been absorbed into themarket.
In Table 16-3 and Figure 16-2 we see that the currencies and metals, representing mar-kets actively traded 24 hours, have the largest overnight gaps. Viewing world markets onlyduring the U.S. business hours can put a trader at a disadvantage and force him to dealwith unpredictable, “uncontrollable risks. This has prompted many traders to watch themarkets through both day and night. Most computerized systems have no trouble contin-uing their calculation through various sessions. .
Point-and-Figure for Short-Term Trading
Point-and-figure charting has been a primary tool of day traders for many years. Using theminimum price movement as the box size and a 3-box reversal, many traders will keep acontinuous, although lengthy, chart of day-to-day price movement. Buy and sell signals canbe taken in the standard manner, but day traders are most likely to use these charts foridentifying countertrend,support and resistance levels. Intraday point-and-figure, as wellas moving averages, often show frequent changes of direction before a new buy or sell sig-nal occurs, even when the minimum box size is used. Trend methods are best applied toshort-term overnight positions in which the size of the move is much larger.425
APPLICABILITY OF 1 RADING TECHNIQUES
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TABLE 16-3 Percentage of Overnight Price Gap Com-pared with Subsequent Trading Range, for Selected
 
 
U.S. Markets
% Change OvernightMarket 1985~1989 1990-1995Cotton 29.6 27.5Corn 26.3 265Soybeans 25.5 23.8Australian dollar 51.9 435British pound 39.1 28.1Canadian dollar 39.0 31.9Deutschemark 37.9 30.9Japanese yen 43.0 35.8Swiss franc 38.4 25.5Gold 28.7 345High grade copper na 30.9Crude oil 324 26.6Heating oil " 33.8 29.0S&P 500 . 19.3 163NYSE Composite 22.0 19.9Treasury bills 27.2 25.6Treasury notes 26.6 13.6Treasury bonds 22.6 (16 ~
 
Price reversals that occur during the day can be plotted using a smaller point-and-figure box size than is common for daily charting. The more frequent reversals due to thecombination of more data and smaller box size will define the trend sooner or bring theprotective stop closer. Remember, stop-loss levels advance only when there are reversals.In this way, day traders’ improvements are transparent to the point-and-figure users whowork only with the daily high, low, and closing prices. In general, when there is a choice ofplotting a point-and-figure trend continuation or reversal, the reversal should be plotted.This allows the chart to reflect the reversal sooner and bring the stop-loss closer—both arean improvement over the standard rules.
Moving Averages
The intrinsic dependency on time makes a moving average less adaptable to day trading.To be used properly, a moving average must be recalculated at fixed intervals. Two philo-sophic questions must be answered with regard to intraday moving averages. Do trendsexist in this short time interval, and does it make sense to apply a moving average _to allintraday prices unevenly spaced with respect to time? In a previous section of this chapter,the conflict between noise and trends was discussed. Markets with a large noise compo-nent require more time to identify a tend, or a larger price move; therefore, it may not bepossible to enter a trend trade and still have enough profit potential before the end of thetrading session. It is likely that there will not be more than 25% of the daily range remain-ing after the trend has been identified, making the profit opportunity too small.
The versatility of computers allows all intraday prices to be used in a moving averagerather than the traditional 5-minute bar; furthermore, you can create a price bar based onevery 5 or 10 prices, regardless of time. In a liquid market, prices might be posted everyAPPLICABILITY OF TRADING TECHNIQUES