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8.2.5 Arms Index (TRIN)

Richard Arms created the Arms Index in 1967 to compare a ratio of ad\aiicers to decliners (Ad\ance/Decline Ratio) Tv-ithfhe ratio of ad\ancing volume to declining volume (UpsideDownside Ratio). The TRINs behavior is similar to the VIX; it is negatively correlated with the market. i.e., a high reading means the market is - and a low reading means the market is overbought.

As shown in Figure 8.8, the TRIN plotted in the lower panel resembles the profile ofan EKG. Spikes punctuate the chart; some technicians will smooth out the TRIN with a three-day or four-day mo\ing av-erage. The problem with smoothing any kind of price is that the average introduces lag, and because our trading signal would depend on a confirmation ofthe mo\ing av-erage, most of the move would already- have occurred

Figure 8S. Arms Index, or TRIN

The TRIN is the least predictable ofthe indicators in the Sentiment Model. .I of the other indicators show some degree of persistency from day-to-day or week-to-week. In contrast, the TRIN is a one-bar phenomenon. Its value lies more in its o\ersold readings (i.e., spikes) than in its overbought readings. The TRIN is another indicator that illustrates the asj-mmetry between corrections and rallies.

"ll.. Aim.liuW 1- ..1 .......

8.26 Bullish Consensus

The Bullish Consensus is a market sentiment indicator that was created in 1964 by Market Vane to track the buy and sell recommendations of market ad\isors and equit>- anal>-sts. Based on their recommendations, Maiket Vane calculates the bullish percentage, e.g., 59*> ofthe people are bullish, and so the remaining 41% are bearish.

Along with the New Highs indicator, the Bullish Consensus is the only other model indicator that is positively correlated with the market The chart in Figure 8.9 shows how closely the two track together, not coincidentally. When the market is up, people are bullish, and when the market is down, people are bearish. Clearly, when people are 1 bullish, the market is ripe for a Ml and vice\ersa

(SPX LAST-Weehly 10 )7/19»4


4 5 0

H \


/ 1


/ 1


V /



H(TVBULL-WeeMy 10/07/19»4




M J 5"


Figure 8.9. Bullish Consensus

8.27 Short Sales Ratio

There are - of short sales ratios, such as the Odd Lot Short Sales to Odd Lot Total Sales. Here, we refer to the Public to Specialist Short Sales Ratio on the NYSE. The theorybehind this ratio is that the public lends to sell short at the worst times (Figure 8.10 and the statistics prove it. The bottom line is that the specialist down on the floor has a much better sense ofthe market.

S3PX LAST-Weekty 03(01(2002





\ y/V vs/ 1100.00



M3ąC-Weekly 03/01/2002


2.D00 1.200

1001I > ll

j a S N b 2002 F "M

FUTP 8.10. Public to Specialist Short Sales Ratio

The Short Seles Ratio is negativaly correlated with the market. Further, it has sjinmetrical spikes down. The chart inFigure 8.11 shows the huge div-ergence that formed shortly before the market cracked in March 2000. The ratio spiked down again inJime 2000, setting up another correction.

tSPXLASTJWeehly 04/21/2000








WPECWeekty 04/21/2000




8.3 Market Trading System

With the sentiment indicators defined, we can now adapt the Acme M Sjstem to our Sentiment Model as a general market sjstem. The Acme Market Sjstem simply coimts the number ofbuUish or bearish pattems on any given bar. Iffhe number ofpattems is greater than the minimum number ofpattems specified by the sjstem, then a signal is generated; no other conditions ly.

The Acme Market Sjstem uses the /.(7 7/ . function for pattem confirmation. For any indicators with negative correlations, a high confirmation (retum value of 1) means the pattem is added to the iongS/nngVariable. Alow confirmation (retum value of 2) means the pattem is added to the ShorlSlring ariable. For indicators with positive correlations, the logic is reversed. For a high confirmation, the pattem is added to the ShorlSlring, and for a low confirmation, the pattem is added to the LongSlring.

The Acme Market Sjstem uses weekly data for its trading signals because some offhe data are not av-sulable electiorricaUy on a daily basis. Although data such as the Bullish Consensus are published on a daily basis, the data feeds do not transmit this data, making the cohection of sentiment data difficult to automate This sjstem can certainly be adapted to daily data, as most ofthe indicators are available electronicaUy.

Before we define the rules ofthe sjstem, we review the maiket correlations of each indicator in the Sentiment Model, as shown in Table 8.8. As with the Acme pattem model, the Sentiment model can be extended with other data, e.g., margin debt. The trader determines the market correlation of a new index, assigns a letter to it, and encodes it in the Acme Market Sjstem. When adding new indicators, find ones that represent different interpretations ofthe market to keep the Sentiment Model in balance.

Table 8.8. Maricet Correlations


Market Correlation

Volatiliiy Index (VIX)


Put/Call Ratio


New Highs








......M.iI.>Im:.....Ml I1..II.

i ii.ii.i >i>>*iiU( in II.........

8.3.1 longsignal


1. Total the number of Bullish Patterns.

2 Calculate the ATR for the last 20 bars (ATR:d).

Entry Rules

1. Number of Bullish Pattems 2

2 Buy the next bar at or above the High + (EntryFactor * ATR:d) Exit Rules: Profit Target

1. Sell half ofthe position at or abme the High + (ProfitFactor * ATR:d)

2. Sdl halfofthe position at or abo\e the High of ProfitBars ago + (2 * ProfitFactor * ATR:d)

Exit Rules: Stop Loss

1. Sdl all shares at or below the Lowest Low for StopBars -(ExitFactor * ATR:d)

8.3.2 short signal


1. Total the number of Bearish Pattems.

2. Calculate the ATR for tiie last 20 bars (ATRc).

Entry Rules

1. Number of Bearish Pattems 2

2. SeU Short the next bar at or below the Low - (Entrj-Factor * ATR:d) Exit Rules: Profit Target

1. Co\er half ofthe position at or below the Low -(ProfitFactor * ATRic)

2. Co\er halfofthe position at or below the Low of ProfitBars ago -(2 * ProfitFactor * ATRc)

1. Co\er all shares at or above the Highest High for StopBars -t (ExitFactor * ATR:d) The code for the Acme Market Sj-stem is shown in Esample 8.2. Example 8.2. Acme Market Sjstem

j****»*»*=,,p,TT#*4t#** t*******************

acme market system: look for combinations of multiple market patterns

1. vix (v)

2. put/call ratio (P)

3. new highs (h)

4. new lows (l)

5. arms index, or trin (t)

6. bullish consensus (b)

7. short sales ratio (s)

datai: market index data2: vix

data3: put/call ratio data4: new highs datas: new lows data6: trin

data?: market vane bullish consensus datab: public/specialist short sales ratio


(market parameters} mnimumpatterns(2), length(20), (position parameters} equity(100000), riskhodel(3), riskpercent(2.0), riskatr(l.O), entryfactor(0.2), drawtargets(true);

variables: n(O), atr(O.O),







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