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Example 6.1. Acme V System

*************************»»»»»**»»«*******************»»*****«***** Acme V System; Anticipate a "V" Bottom based on Linear Regression


{V Parameters} VolatilityFactor(2.o), Regressio $(5)> RangeFactor(1.0), {Position Parameters} Equity(100000), RiskModel(3), RiskPercent(2.0), RiskATR(1.0), EntryFactor(0.25), DrawTargets(True);

Variables: N(o), ATR(0.0), ATRLength(ZO), HA(O.O), HALength(50), LRValue(O.O);

ATR = Volatility(ATRLength);

HA = Average(Close, HALength);

LRValue = LinearRegValue(Low, RegressionBars, -1);

{Entry Signal}

If (DayOfWeek(Date) = l or DayOfWeek(Date) = 2) Then Begin {Calculate shares based on risk model}

N = AcmeCetShares(Equity, RiskModel, RiskPercent, RiskATR);

If High < Lowe5t(High, RegressionBars - l)[l] and

Range <= RangeFactor * ATR and

Low > LRValue and

Low > MA and

High > Low[l] Then Begin

{Draw Entry Targets on the Chart} If DrawTargets Then

Conditionl = AcmeEntryTargetsCV", Close + (EntryFactor * ATR), 0, 0, 0); BuyCAcme LE V") N Shares Next Bar on Close + (EntryFactor » ATR) Stop; End; Ind;

6.3 Examples

The foUowit charts are examples oftrades generated by the Acme V System. Each example uses Equity of $100.000 and the Percent VolatUitj Model with a risk of2/o.

6.3.1 Micrasemi 1

Figure 6.4 shows an entr nght at the 50-day moving av-erage. Note the difference between entering at the moving average on the same day versus enteiing the next day on a breekout above the high- a difference of almost two points.

MSCCLAST4)riy / / ! Mov Aval line(ClosB,SO,0) 29.394

Figure 6.4. Mi.

li Corporation Volatili

Given the performance ofthe maiket from eariy 2000 to eariy 200Z with the Nasdaq declinit over 60° o, we tested the performance ofthe V sjstem over this period since it is a long-only sjstem. Over one thousand stocks from various sectors were back-tested dariy data from the TradeStation historicsl database. The results are showninTable 6.1.

The profit factor for the test period is 1 75. Although the winning percentage is under 50°* the average winner was nearly twice the amount ofthe average loser. The next step is to test the V system near the 50 day moving average to sec if resuhs are improved by using a support level.

130 6 Volatility Trading

Table 6.1. Acme V Sj-stem Performance from Marcli 2000 - March 2002

" Winners Winners A\g Win Losers A\« Loss ProfitFactor

47.2% 1491 $2,609.83 1669 -$1,333.79 1.75

Table 6.2 shows the results of confining entries to pnces within halfthe ATR of the 50-day mo\it a-erage. The profit fector decreased from 1.75 to 1.20, with a winning percentage of only 39° o. Now, confess that you expected the profit factor to be higher because of support at the mo\ii average. Intuitively, such a conclusion is logical, but in trading one learns quicldy that the Icgicsl choice is not the best choice

Lets explore the reasons for the disparity inresuHs. Retum to the beginning ofthe chapter and read the first page. Assume the trader has a choice between a V signal that is five points abo\e the mo\ii a-erage and another signal that is one point above the mo\Tng average. Consideiing the number ofpoints above ftie mo\Tng a-erage, describe the key factors that differentiate these two trades. Clearly, there are two distiiuishing factors, and they are both psjcholcgicsl. hi the traders mind, the second trade is both "cheaper" (comfort factor #1) and also conformist (comfort factor #2 because the hterature tells the trader to buy when a stock approaches the 50-day mo\Ti a-erage). The reahty is that a stock that has been trading abo\e a key mo\Tng a-erage and then proceeds to test that a-erage wih strike fear among the long holders and inspire short entries as weh. Our modus operandi is: Support is meant to be broken

Table 6,2. Acme V System Perfonnai

ir MA from Marcli 2000 - March 2002

"p Winners Winners Avg Win Losers Avg Loss Profit Factor

39.2% 131

$2,463.57 203

$1,322.13 1.20

6.3 Examples 131

6.3.2 Veritas Software

The V sjstem enters near the low ofthe day, as shown in Figure 6.5. This is the only way to put the odds in your favor when a stock is in a downtrend. Entering on a high stop gives too much ofthe profit away. In general, the V sjstem is an excehent sjstem for intraday range trading. The trader can enter when the stock goes green and either close the position at the end ofthe day with aprofit or get stopped out close to the low.

Figure 6.5. Veritas Software Volatility

63.3 webMethods

Figure 6.6 shows two examples ofV entries weh above the fifty-day mo\Tng average. The ad\antage ofthe V sjstem o-er traditional ADX/DMI combination sjstems is that the ADX and DMI can filter out trades even if a stock is trading above its mo\Tng average. Further, the DMI is deceptive because when a stock is in along shahow downtrend, the DMI ratio wih flip from positive to negative, even though the long-term trendis up.

Do not eliminate stocks priced below $20 per share. Both ofthe entries in Figure 6.6 occurred in the $15-$16 range, and at the time, webMethods had an ATR of -1.3. Most of the industrial and cychcsl stocks trade at much higher prices with lower ATRs. We remind you to drink from the fountain of liquidity

šiire 6,6, webMethods Volatility

63.4 SeaChange

The second Acme V entr in Figure 6.7 is a losii trade that followed a choppy downtrend. Entries after inside days are slightly more difficnlt but lisk-hmited.

SEACLAST4)jdy 01/04/2002 MovAvfl 1 line 30.003 AcmeVStraHfly LinearRearesskin

1i,;iir.-(. 7 Si-.ini.iii,-,. V.,I.Ullin

IBTKLAST4)>iv OS/2S/20D1 Moy Avg nine 510.4S AcmeVStralafly LIni

Figure 6.8. Biotechnology Index Volatility

6.3.6 Computer Associates

The chart inFigure 6.9 shows a V entrin Computer Associates (CA:NYSE). The problem with this entrj is the gap down that occurred two days eadier. Our reaction to this chart is that the V sjstem code should be changed to look for down gaps overthe entire hnearregression range. Ifthere are any gaps ov-er the raie,thenthe trade isnuUified.

Ultimatel), the traders gosl is to eliminate mistakes, which means not taking trades such as the one in Figure 6.9. What may seem as minor observations

6.3.5 Biotechnology Index

Rim the V sjstem on aU ofthe indices to get a sense ofwhere the seaors are trading. For the entr in Figure 6.8, we buy either the Biotechnologj HOLDR (BBH:Amex) or a basket of biotechnolc stocks in the Nasdaq 100 such as Amgen(AMGN:Nasdaq), Bicgen (BGEN:Nasdaq), and Protein Design Labs (PDLLNasdaq). The adv-antage of using the sector indices to tiier trades is that they trend smoother than individual stocks, and the av-erage holding period is leader. The disadv-antage oftrading a basket of stocks is that it is a difficnlt combination of maintainiiffi multiple ixedtions and picluiffi stocl:s that may not trade sjiichronously with the index. Instead, we prefer high-cap stocks that are components ofthe BBH.

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