IVLNCATISSTLWGROVNWKSLIBMMORGMMCELLFWCAPWAIZASPXTENORBMYRSFAMIFCISBLUINVXHMXPRDALLP
12/6/200211/14/200210/11/200210/11/200210/11/200210/11/20029/30/20029/30/20029/30/20029/30/20028/15/20027/24/20027/11/20027/11/20026/28/20026/12/20026/12/20026/12/20026/12/20025/1/20024/24/20024/18/20023/1/20022/21/20022/21/20022/7/20021/16/200212/31/200111/30/200111/30/200111/15/200111/2/200110/9/200110/9/200110/9/200110/5/200110/5/20018/6/20017/18/20017/18/2001
T=0
T = 10
T = 20
1.351.384.32.670.8011.51.261.4311.131.231.441.181.19problem with data1.2791.090.790.390.7291.521.31.421.011.6310.30.480.531.111.091.421.371.091.161.5191.61.421.41.41.450.940.481.441.941.391.431.050.960.660.871.782.531.670.6855.321.4211.391.551.562.13.41.021.391.021.47990.90.950.81.051.3421.953.451.21.31.461.44
1.41.051.884.461.752.3391.491.750.581.511.711.740.520.330.721.251.111.031.41.730.761.68—0.751.332.560.355.381.81.673.58—2.90.79——3.521.51.74
(continued )
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128TABLE 10.1
TRADE LIKE A HEDGE FUND
Continued
Pac-West TelecommunicaEdgewater TechnologyGottschalks, Inc.eLoyalty CorporationRobotic Vision SystemsLillian VernonCyrk Inc.Casual Male Corp.Cone MillsImmune Response Corp.Exabyte Corp.P-Com Inc.New Century Equity HldDamark InternationalAdaptive Broadband CorFriede GoldmanHA-LO IndustriesWashington Group Int’lNashua Corp.Dixie Group Inc.Books-A-MillionSpartan MotorsBombay CompanyLaser Vision CentersHanger Orthopedic GroupAmes Department StoresFrozen Food Express Ind.Insteel Industries Inc.TALK.Com, Inc.Birmingham SteelChiquita BrandsEpicor SoftwareCKE RestaurantsGuilford MillsWHX Corp.GC CompaniesPillowtex Corp.Lason Inc.Oakwood HomesKomag Inc.Coeur d’Alene MinesSwiss Army BrandsSports AuthorityMagellan Health ServicesInacom Corp.
Ticker
DateEffective
T=0
T = 10
T = 20
PACWEDGWGOTELOYROBVLVCCYRKCMALCOEIMNREXBTPCOMNCEHDMRKADAPFGHHMKWNGNSHDXYNBAMMSPARBBALVCIHGRAMESFFEXIIITALKBIRCQBEPICCKRGFDWHXGCXPTXLSONOHKMAGCDESABITSAMGLICO
7/11/20017/6/20017/6/20016/14/20015/31/20015/23/20015/11/20015/11/20014/27/20014/16/20014/2/20014/2/20013/30/20013/22/20013/22/20013/8/20013/8/20013/5/20012/27/20011/31/200112/29/200012/28/200012/28/200012/20/200012/11/200012/11/200012/8/200012/4/200011/28/200011/16/200011/7/200011/2/200010/4/200010/4/20009/26/20009/20/20008/10/20008/8/20008/8/20008/2/20007/27/20007/27/20006/30/20006/23/20005/2/2000
1.153.3531.061.567.132.451.141.641.481.06251.65621.1252.710.921.31.073.062.34371.3751.34371.931.18751.311.51.2510.571.371.512.441.314.113.121.251.18751.51.15621.374.251.561.250.9375
0.963.333.450.991.868.92001.453.150.991.41.313.250.752.151.091.864.92.62521.93752.371.8750.931.381.43751.2521.251.751.156221.884.52.932.56252.81251.621.43751.434.3751.621.371.0625
0.923.453.280.771.848.92001.375.951.061.071.283.2500.980.961.574.73.43752.1252.65622.372.06251.25—1.68753—1.371.561.0312——62.372.3752.1251.682.31251.374.18751.51.620
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Deletions from the Indexes
PictureTel Corp.Aviation SalesRural/Metro Corp.Frontier Insurance GroupGenesis Health VenturesSouthern Energy HomesUSA DetergentsNCS Healthcare Inc.AMRESCO Inc.Benton Oil & GasDelta Woodside Ind.Hecla MiningPhyCor Inc.Galey & Lord Inc.Integrated Health ServicesMolecular BiosystemsFamily Golf CentersApplied MagneticsSystem SoftwareTCSI Corp.Breed TechnologiesDialogic Corp.Mariner Post-AcuteLechters Inc.Johnston IndustriesLSB IndustriesHauser Inc.KCS Energy Inc.Glamis Gold Ltd.Wiser OilShoney’s Inc.Filene’s BasementNorthwesternTultex Corp.BroadBand TechnologiesZoll MedicalDesigns, Inc.ImmuLogic PharmaceuticalsSciClone PharmaceuticalsNational Auto CreditGeotek CommunicationsTseng LabsNTN CommunicationsCellPro, Inc.Air & Water Technologies
Ticker
DateEffective
PCTLAVSRURLFTRGHVSEHIUSADNCSSAMMBBNODLWHLPHYCGNLIHSMBFGCIAPMSSAXTCSIBDTDLGCMPNLECHJIILSBHAUSKCSGLGWZRSHNBSMTNWSWTTXBBTKZOLLDESIIMULSCLNNAKGOTKTSNGNTNCPROAWT
4/19/20004/19/20003/31/20003/29/20002/23/20002/15/20001/28/20001/28/20001/13/20001/3/200012/30/199912/30/199911/23/199911/4/199910/21/199910/1/19998/31/19998/31/19998/30/19998/30/19998/17/19997/2/19996/18/19994/30/19994/30/19994/30/19994/27/19994/27/19993/1/199912/31/199812/31/199812/15/199812/10/199812/10/199810/22/19985/28/19985/14/19983/30/19983/19/19983/4/19982/9/19981/14/199812/31/199710/6/19979/25/1997
T=0
T = 10
T = 20
3.534.123.756.311.187520.931.061.251.68751.21871.34372.252.461.46875 1.906251.061.311.811.881.871.931.561.51.15625 1.18751.312.680.3750.251.6251.3751.252.8750.937510.937501.6251.68750.43750.687543.906300.6250.343751.532.211.52.52.187521.52.56251.121.371.561.682.122.751.3751.93751.52.093750.81250.81250.750.81251.31252.755.81256.68751.751.51.51.531253.18754.28121.751.93751.7501.40625 1.37511problem with data1.751.875
—6.2520.870.81251.21872.312.343751.31—1.621.431.31252.180.312512.8750.812501.50.62500.68752.252.252.06252.43750.681.522.81253.3750.906250.93752.757.8751.81251.93754.0625001.50.931.4375
(continued )
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130TABLE 10.1
TRADE LIKE A HEDGE FUND
Continued
JumboSports, Inc.RDM Sports GroupLevitz FurniturePharmaceutical ResourcesPayless CashwaysBanyan SystemsCasino MagicVenture StoresCompression LabsOmega EnvironmentalSunshine MiningMerisel, Inc.
Ticker
DateEffective
JSIRDMLFIPRXPCSBNYNCMAGVENCLIXOMEGSSCMSEL
9/2/19978/7/19977/25/19977/25/19977/17/19975/27/19975/27/19975/27/19973/31/19973/31/19971/22/19971/13/1997
T=0
T = 10
3.31253.93750.690.51.131.52.252.06problem with data1.93751.93751.28125 1.3752.52.625problem with dataproblem with data6.57.51.81251.9687
T = 20
3.5——2.061.8751.1252.5
91.9375
Source: Courtesy of Charles Kornblith, Wharton University.
TABLE 10.2
Total Study
Total ReturnNumber of SamplesAverage ReturnStandard DeviationSEMZ-score
T=1
T=5
T = 10
1079.66%1367.94%20.10%0.01724.6054
2010.02%13614.78%29.62%0.02545.8185
2154.03%13615.84%45.31%0.03884.0769
T=1
T=5
T = 10
82.11%26
134.81%26
212.76%26
13.16%11.36%0.02227551.4177141
15.19%27.74%0.054409830.95296697
18.18%38.96%0.07640651.0710029
Notes: SEM = stdev/sqrt(N); Z-score = avg. return / SEM.Source: Courtesy of Charles Kornblith, Wharton University.
TABLE 10.3
2002 Returns Breakdown
Total ReturnNumber of SamplesSamples Excluded Due to Problemswith DataAverage ReturnStandard DeviationSEMZ-score
Notes: SEM = stdev/sqrt(N); Z-score = avg. return / SEM.Source: Courtesy of Charles Kornblith, Wharton University.
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Deletions from the Indexes
TABLE 10.4
2001 Returns Breakdown
Total ReturnNumber of SamplesSamples Excluded Due to Problemswith DataAverage ReturnStandard DeviationSEMZ-score
T=1
T=5
T = 10
140.89%33
505.61%33
330.38%33
017.43%0.03034061.4072023
030.71%0.053457772.8661064
044.03%0.07663831.3063482
T=1
T=5
T = 10
546.32%35
870.75%35
1064.10%35
015.61%29.89%0.05051633.0899317
024.88%36.44%0.06158774.03955358
030.40%50.47%0.0853023.5641278
T=5
T = 10
247.80%18113.77%29.69%0.069969561.96752364
313.97%18117.44%54.86%0.12929961.3490194
Notes: SEM = stdev/sqrt(N); Z-score = avg. return / SEM.
TABLE 10.5
2000 Returns Breakdown
Total ReturnNumber of SamplesSamples Excluded Due to Problemswith DataAverage ReturnStandard DeviationSEMZ-score
Notes: SEM = stdev/sqrt(N); Z-score = avg. return / SEM.
TABLE 10.6
1999 Returns BreakdownT=1
Total Return141.37%Number of Samples18Samples Excluded Due to Problems with Data1Average Return7.85%Standard Deviation19.48%SEM0.0459145Z-score1.7105537Notes: SEM = stdev/sqrt(N); Z-score = avg. return / SEM.
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132TABLE 10.7
TRADE LIKE A HEDGE FUND
1998 Returns BreakdownT=1
T=5
T = 10
169.06%13013.00%11.66%0.032325754.02289179
173.72%13013.36%46.19%0.12811.043188
T=1
T=5
T = 10
60.71%11
81.99%11
59.09%11
45.52%7.52%0.02266982.4346512
47.45%8.19%0.024698813.01772042
45.37%15.43%0.04652211.1547403
Total Return108.25%Number of Samples13Samples Excluded Due to Problems with Data0Average Return8.33%Standard Deviation9.40%SEM0.0260656Z-score3.1945545Notes: SEM = stdev/sqrt(N); Z-score = avg. return / SEM.
TABLE 10.8
1997 Returns Breakdown
Total ReturnNumber of samplesSamples Excluded Due to Problemswith DataAverage ReturnStandard DeviationSEMZ-score
Notes: SEM = stdev/sqrt(N); Z-score = avg. return / SEM.
CONCLUSIONFurther avenues of study before using an approach based on deletion fromthe indexes include:• What is the effect of deletions on the other indexes? Nasdaq 100 stocks,in particular, have a lot more liquidity and volatility.• What happens in the Kornblith study when taking into account volume(i.e., only buying the stocks with x shares of volume per day)?• What happens when you only look at the stocks that had the largestprice decreases prior to the effective date?Nevertheless, despite these concerns, if a direct-access broker is usedto keep commissions low, I think a strategy based on deletions from theindex is playable.
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TECHNIQUE 11
Everything YouWanted to KnowAbout the 200-DayMoving Average butWere Afraid to Ask
onstantly we hear reference to the 200-day moving average in themedia. “The S&P index just crossed its 200-day moving average andthis is a very bullish sign.” “MSFT crossed its moving average so weshould expect to see a nice upwards move over the next week.” And so on.I was skeptical. It does not seem to make sense to me that this movementwould be a bullish event. Plus, most of the time I read or hear about the 200day moving average, people are talking about the entry (the crossover ofthe average) but never the exit so it has been hard to formulate a successful trading strategy. Also, I was never sure what people meant by the word“bullish.” Does it mean the market goes up forever now? Or just tomorrow?First of all, what is the 200-day moving average? Simply put, it is theprices of the prior 200 days added together and divided by 200. As canbe seen in Figure 11.1, a chart of the 200-day moving average, most of thetime when we are in a bull market, the closing daily price of the S&P isabove the 200-day moving average, and most of the time when we are in abear market, the closing price of the S&P 500 is below the 200-day movingaverage. The real question is, when the daily price of the S&P closes overthe 200-day moving average, are we also moving from a bear period to a bullperiod?In the following I present several possible systems using the 200-daymoving average. First I attempt to mirror and test the prognosticators in themedia that forecast the change in trend with each move in the 200-day moving average. Then I demonstrate a long-only system based on the idea ofusing the 200-day moving average as a countertrend indicator that hasworked well in both bull and bear markets.
C
133
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FIGURE 11.1
TRADE LIKE A HEDGE FUND
S&P 200-day moving average.
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Everything You Wanted to Know About the 200-Day Moving Average
135
TRADING SYSTEMSHere is the system I feel most closely mirrors what the media is forecastingwhen the 200-day moving average is mentioned:• Buy the S&P when the close crosses over the 200-day moving average.• Sell when the S&P crosses below the 200-day moving average.It is hard to qualify this outlook as bullish, but the results are positive.The reason for the hesitation is that only 28 percent of the occurrences ofthis system have resulted in a positive trade. In other words, if the S&Pcloses above its 200-day moving average, then there is a 70 percent chanceit will be lower by the time it goes below its 200-day moving average.That said, doing this trade on every occurrence since 1950 would havemade an investor money in the long haul. In summary: of the 142 occurrences since 1950, 40 were successful and 102 were unsuccessful, with anaverage return per trade of 3.23 percent (including the losses). An amountof $10,000 put into this system in 1950 would be worth $55,000 now; $10,000put into a buy and hold strategy, however, would now be worth $494,000.Particularly since January 1, 2000, there have been many false starts tothis indicator (Figure 11.2), with 17 occurrences and only 2 successful (including the most recent one that opened on April 21, 2003, and not closedyet). So when someone says “we just crossed over the 200-day moving average so now we are in a bull market,” it is best not to believe it.
THE ONE DAY 200 DMA SYSTEMHere is another system:• Buy the S&P when the close crosses the 200-day moving average.• Sell one day later.The idea is that maybe people get so excited about the event of the crossing that they rush to buy.The result is mildly positive but not statistically significant and doesnot beat commissions and slippage. Of the 147 occurrences since 1950, 74were successful and 73 were unsuccessful, with an average return of 0.11percent (equivalent to 1 point in the S&P today).However, the results get a little better when you buy the 200-daycrossover and hold for one month: 72% successful with an average gain of1.65 percent as opposed to the 0.68% average monthly return since 1950.
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1,550.001,525.001,500.001,475.001,450.001,425.001,400.001,375.001,350.001,325.001,300.001,275.001,250.001,225.001,200.001,175.001,150.001,125.001,100.001,075.001,050.001,025.001,000.00975.00950.00931.87925.00900.00883.85875.00850.00825.00800.00775.00
Volume
25.00M20.00M15.00M10.00M5.00M
FIGURE 11.2
False starts.
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Everything You Wanted to Know About the 200-Day Moving Average
137
The last trade in this system started on April 17, 2003, and ended on May 16,for a gain of 5.68 percent. Holding for a quarter does not improve the results: 2.67 percent per trade as opposed to an average quarterly return of2.04 percent since 1950.So perhaps it is bullish when the S&P 500 crosses its 200-day movingaverage and you hold for a month. Basically you can get double the returnwhen compared to a random buy and holding for a month.What happens now if you run the one month 200 DMA system on a basket of your favorite stocks? Buy a stock when it crosses its 200-day movingaverage then sell one month later. I ran the test on the stocks in the S&P 400mid-cap index over the past eight years as a simulation where each tradetook up 1 percent of equity. The results were marginally okay: average return of 0.62 percent per trade with the yearly returns shown in Figure 11.3demonstrating that you would have survived the worst of the bear marketbut still taken a big hit in 2002.In general, although conceptually it does seem bullish when the indexes cross their 200-day moving averages, it does not seem like there is aworthwhile trading strategy that results. Therefore, I decided to try onemore approach: a contrarian one that depends on the concept of mean reversion, that is, buy when the price of the S&P hits an extreme low relativeto its 200-day moving average. Specifically, and simply:• Buy when the S&P closes 20 percent below its 200-day moving average(e.g., the crash of 1987 or on September 20, 2001)• Sell one month (20 trading days) later.Since 1950, utilizing this system results in 79 trades, 65 of which wereprofitable (82 percent) and 14 unprofitable (17 percent) for an average return of 6.43 percent per trade as opposed to a