return of 0.68 percent if onerandomly buys any month. Not bad. Interestingly, if one only looks at thedata for the S&P 500 index since 1975, this system would have resulted in34 out of 34 successful trades with an average return of 10 percent pertrade. The last trade started on October 10, 2002 and ended on November 7,2002, returning a nice 12.28 percent. Enough to pay the bills and have aglass of wine to celebrate.
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Annual returns.
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FIGURE 11.3
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Everything You Wanted to Know About the 200-Day Moving Average
139
CONCLUSIONArguing about what direction the trend of the market is in (bull or bear)based on the 200-day moving average might be fun at cocktail parties butwill not really make anyone money. Instead, buying when the trend is absolutely, unequivocally down and the market is plummeting vis-à-vis its200-day moving average is usually the best time to take a trade on the longside. By the time the talking heads are debating a new trend when the pricecloses above the 200-day moving average, you are long gone out of the market, hopefully on vacation.
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TECHNIQUE 12
End of Quarter,End of Month,Outside Month
THE END OF THE QUARTER MYTHAs I write this, it is June 29, 2003, and tomorrow is the last day of the quarter. On the various systems I play I am getting a pretty strong short signalat the open on Nasdaq futures in the morning. I mentioned this to two different friends of mine—one a stockbroker at Morgan Stanley, the other aprofessional money manager who manages $500M in assets. Both of themsaid the same thing, “Oh man, I wouldn’t short QQQ the last day of thequarter. Aren’t you afraid of end of quarter window dressing?”I did a search on Google for “End of quarter” and “window dressing”and got 545 results. A typical quote was, “you might want to consider holding it a bit longer than you might otherwise, through the window dressingperiod. . . .” It does not make sense to me in general. I mean, it is not as if afund manager is going to improve his returns by marking up stocks likeMSFT or INTC. The volume is too great for any mutual fund machinationsto have any effect at all.So I ran a test of an end-of-quarter shorting system:• Short the open on the last day of the quarter.• Cover at the end of the day.
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I got the following results:QQQ: 8 out of 16 successful; average return of +0.68 percent.SMH: 9 out of 11 successful; average return of +1.72 percent.SPY: 29 out 41 successful; average return of +0.34 percent.^NDX (since 1988): 24 out of 60 successful; average return of +0.10percent.^SPX (since 1988): 33 out of 60 successful; average return of +0.11percent.^RUT (since 1987): 10 out of 62 successful; average return of –0.63percent.So, in fact, whether bull or bear market, people tend to avoid buying inthe broader markets on the last day of the quarter. Except, as could be expected, on the Russell 2000, where the illiquidity of the stocks that make upthe index are more prone to manipulation. The results suggest a possiblepairs trade going into last day of quarter: Short SMH and go long IWV, theiShares ETF for the Russell 2000.
THE END OF THE MONTH PANICAt the end of the month, every basis point counts for fund managers.Bonuses might be dependent on the monthly result, Sharpe ratios are beingcalculated, track records are being dressed up and paraded to investors. Ifthe market starts to slide mid-day then trouble is potentially brewing for theportfolio manager whose career is hanging on every tick. Consequently, ifthings look like they are going from bad to worse, the fund manager mightirrationally sell into that panic, knowing that he can just as easily buy backhis shares the next day.Such observation suggests the following pattern:• Buy the close when the last day of the month is down 1 percent.• Sell at the open on the first day of the month.
Example: QQQ, 3/31/2003The last day of March 2003, an otherwise great month for the markets, wasa down day for QQQ—they closed at 25.25. The next day, when the dustcleared and portfolio managers realized they had made the mistake of a lifetime, they drove up the market pre-open so that it ended up opening at25.44. As you can see in Figure 12.1, selling then resulted in a profit of 0.75percent. (Also see Tables 12.1 and 12.2, page 144.)
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143
27.3027.2027.1027.0026.9026.8026.7026.6026.5026.4026.3026.2026.1026.0025.9025.8025.7025.6025.50
25.4625.4025.3025.2025.10
Volume
80.00M60.00M40.00M20.00M
FIGURE 12.1
QQQ on March 31, 2003.
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TABLE 12.1
Results for the End of Month Panic System (basedon QQQ, March 4, 1999 to June 30, 2003)All Trades
All TradesAverage Profit/Loss %Average Bars Held
131.32%1
Winning TradesAverage Profit %Average Bars HeldMaximum Consecutive Winning Trades
11 (84.62%)1.66%16
Losing TradesAverage Loss %Average Bars HeldMaximum Consecutive Losing Trades
2 (15.38%)–0.57%11
TABLE 12.2
End-of-Month Panic Trades
Position
Symbol
Entry Date
EntryPrice
Exit Date
ExitPrice
%Change
LongLongLongLongLongLongLongLongLongLongLongLongLong
QQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQ
11/30/199912/31/19995/31/20009/29/200012/29/20001/31/20012/28/200112/31/20012/28/20025/31/20029/30/200211/29/20023/31/2003
73.591.3883.1288.7558.3864.347.4538.9133.7830.0420.7227.7225.25
12/1/19991/3/20006/1/200010/2/20001/2/20012/1/20013/1/20011/2/20023/1/20026/3/200210/1/200212/2/20024/1/2003
74.3296.1985.1990.2558.5664.5546.9739.5734.153020.9128.4225.44
1.125.262.491.690.310.39–1.011.71.1–0.130.922.530.75
In general, by the way, as Victor Niederhoffer has pointed out in Education of a Speculator (Wiley, 1998), developing systems for holdingovernight is the best source of profits. Just as a blind example, say youbought the close of SPY every night and sold every morning. From 1993 to
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2003 your average return per trade would have been 0.05 percent. Conversely, buying the open and selling the close of SPY since 1993 would haveresulted in an average profit per trade of –0.01 percent (i.e., a loss of 0.01percent per trade). Consequently, since 1993, all of the returns in the market have occurred overnight.
THE OUTSIDE MONTHOne more interesting month pattern is the outside month. If the market hasan unusual large-range month with both the high and the low being outsidethe range marked off in the prior month, then that volatility has a tendencyto revert to its mean in the coming month, resulting in a higher likelihoodof an up month. Here is a system to take advantage of that tendency:• Buy SPY the first day of the month when the high the prior month washigher than the high two months ago and the low the prior monthwas lower than the low two months ago.• Sell on the close of the last day of the month.Table 12.3 summarizes the results, showing an average profit of 2.20percent per trade holding for one month. Random buying of a month is0.78 percent. See Table 12.4 for a list of outside months since 1993.
TABLE 12.3
Outside Month, 1993–2003All Trades
All TradesAverage Profit/Loss %Average Bars Held
122.20%1
Winning TradesAverage Profit %Average Bars HeldMaximum Consecutive Winning Trades
8 (66.67%)4.31%13
Losing TradesAverage Loss %Average Bars HeldMaximum Consecutive Losing Trades
4 (33.33%)–2.03%11
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TABLE 12.4Position
LongLongLongLongLongLongLongLongLongLongLongLong
Outside Months Since 1993
Symbol
Entry Date
EntryPrice
Exit Date
ExitPrice
%Change
SPYSPYSPYSPYSPYSPYSPYSPYSPYSPYSPYSPY
11/1/19942/1/199611/3/19972/2/19987/1/199811/2/19986/1/199911/1/19992/1/20008/1/200010/2/20004/1/2003
41.958.0287.2593.88107.85105.14124.17130.94134.39138.8139.7785.25
11/1/19942/1/199611/3/19972/2/19987/1/199811/2/19986/1/199911/1/19992/1/20008/1/200010/2/20004/1/2003
40.4158.2789.5298.77105.7110.18131.07133.61132.17147.21138.4991.91
–3.560.432.65.21–1.994.795.562.04–1.656.06–0.927.81
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TECHNIQUE 13
Ten PercentDown—Panic 101
entiment indicators have been useful timing tools in the 2000–2002bear market and have flown in the face of the commonly used adage,“The trend is your friend.” The question is: Is it possible to develop atrading system that takes advantage of these extremes in despair? Let uslook at two different systems, one for stocks and the other for indexes,where the panic levels are extreme. We will try to find out what happens ifwe blindly take the other side of the panic.
S
THE 10 PERCENT PULLBACKThe idea is simple: Buy a stock that is 10 percent lower than the prior day’sclose. But what could happen to cause such a drop? Any number of things:••••
Massive earnings warning.SEC investigation announced.The company fails several FDA trials.The CEO skips the country and all the money is missing from the bankaccount.• Etc.Well, OK, that makes sense then. I mean, if the company goes from $2a share in profits to $2 a share in losses, then maybe it deserves to fall 10
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percent during the course of a day. Who would want to own it? Certainlynot the mutual funds who might be dumping tens of millions of shares thatday. Definitely not the brokers who put their clients into the stock and nowthey are thoroughly embarrassed at the result. And feeding on top of thisare the trend-following day traders who are shorting the trend. A stock inthis situation becomes a death spiral.So here is a system for taking advantage of a market panic:• Buy a stock that is 10 percent lower than the prior day’s close.• Sell at the end of the day.Consider all S&P Mid-Cap 400 stocks over the past five years. I chosemid-cap to avoid any so-called size effect, but the same test can obviouslybe performed on any subset of stocks.Assume we start off with $1M and use $50K (5 percent of portfolio) pertrade. See the results listed in Table 13.1 (see page 151). Since January 1,1997, the system permitted about 8,200 trades and 60 percent of the tradeswere profitable, with an average profit per trade of 1.4 percent. The maximum drawdown of the system was –3.5 percent, as opposed to –40 percentfor a buy and hold strategy (as evidenced by the thick wavy line in the equity curve in Figure 13.1).In a variation of that system:• Buy a stock that is 10 percent lower than the prior day’s close.• Sell after holding for one month.As a test, consider all Nasdaq 100 stocks since 1995. Assume startingwith $1M and using $2,000 (0.2 percent of equity) per trade. See the annualreturns shown in Figure 13.2 (see page 150) and listed in Table 13.2 (seepage 152). The results can be summarized as follows:Average annual return: 13.89 percentStandard deviation of returns: 9.07Sharpe ratio: 1.53Average return per trade: 8.16 percentAverage return per winning trade: 28.82 percentAverage return per losing trade: –18.67 percent
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Ten Percent Down—Panic 101
FIGURE 13.1
Portfolio equity curve.
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Annual returns.
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FIGURE 13.2
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TABLE 13.1
Ten Percent Pullback SystemAll Trades
Buy & Hold
Starting CapitalEnding CapitalNet ProfitNet Profit %Exposure %Risk-Adjusted Return
$1,000,000.00$6,744,820.50$5,744,820.50574.48%7.50%7,663.94%
$1,000,000.00$1,998,198.00$998,198.0099.82%100%99.82%
All TradesAverage Profit/LossAverage Profit/Loss %Average Bars Held
8,197$700.841.42%1.00
397$2,514.3599.85%1,499.00
Winning TradesGross ProfitAverage ProfitAverage Profit %Average Bars HeldMaximum Consecutive Winning Trades
4968 (60.61%)$12,969,821.00$2,610.675.30%1.0041
282 (71.03%)$1,101,028.75$3,904.36155.07%1,499.0014
Losing TradesGross LossAverage LossAverage Loss %Average Bars HeldMaximum Consecutive Losing Trades
3229 (39.39%)$–7,224,984.00$–2,237.53–4.54%1.0025
115 (28.97%)$–102,831.17$–894.18–35.56%1,499.005
–3.54%$–142,059.754/14/2000$335,618.533.353.24
–40.43%$–1,107,053.2510/9/2002$258,692.670.910.16
Maximum DrawdownMaximum Drawdown $Maximum Drawdown DateStandard ErrorRisk Reward RatioSharpe Ratio of Trades
EXTREME ADVANCES-DECLINESSometimes the extremity of a panic should not be measured just by depth(for instance, a 10 percent selloff), but by breadth (for instance, every stockin the universe went down today). While it is unlikely that every singlestock goes down even in a crash (in fact, gold stocks usually go up then), itdoes seem like an extreme if for every one stock that is up, seven stocks aredown. For the S&P Mid-Cap 400, a ratio of 7 down stocks for 1 up stockwould translate to the number of advancing stocks minus the number of declining stocks being lower than –300 (50 stocks up, 350 stocks down).
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TABLE 13.2
Annual Returns
PeriodStarting
$Return
%Return
%MaximumDD
Exposure
Entries
Exits
99,167.25108,217.5070,164.13358,756.75247,274.00168,689.00565,377.88153,366.75
9.929.855.8128.0815.118.9627.555.86
–1.48–2.86–2.12–5.51–2.01–14.45–16.89–7.50
5.768.248.2512.448.9123.2418.7312.49
3515696379899213,1122,4751,867
3015986059869192,7992,7701,764
1/24/19951/2/19961/2/19971/2/19981/4/19991/3/20001/2/20011/2/2002
The system I propose for taking advantage of this measure of theextremity of market panic is:• Buy the Mid-Cap ($MDY) index at the close of the market if the numberof advancing stocks minus the number of declining stocks is lower than–300.• Sell in two months.Since 1996, the system makes the trades shown in Table 13.3. You cansee that not a lot of trades would have been generated—only nine, six ofwhich are profitable. However it is interesting to see that those days of extreme market reactions to the downside, where everyone was selling everything, called significant market bottoms over that time period.
TABLE 13.3
Trades
Entry Date
EntryPrice
Exit Date
ExitPrice
%Change
BarsHeld
10/27/19978/27/19984/14/20003/12/20016/14/20019/17/20016/3/20028/2/200210/4/2002
308.70305.25431.37478.61509.98445.19515.82419.70389.47
12/24/199710/26/19986/14/20005/9/20018/13/200111/13/20017/31/200210/3/2002Open
319.28322.30489.55510.71501.93479.45441.27399.18Open
3.415.5613.476.69–1.607.67–14.47–4.9115.18
414141414141414140
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CONCLUSIONBuying panic is difficult. During those moments of panic it is not likely thatI can pick up my calculator and coolly figure out how much money I amabout to make. More likely, I am thinking, “It’s the end of the world!” andplanning out my log cabin in Canada. Nevertheless, it is at these momentswhere opportunity gives birth.
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TECHNIQUE 14
Taking Advantageof OptionExpiration Day
o identify a trading edge one must first pray to the gods of efficientmarket theory (EMT) that they turn the other way for a short while.Rational, efficient markets, with all information baked in, do not makefor exploitable edges. However, if there is any day in a month where it canbe claimed that the EMT gods take a short vacation, it has to be the thirdFriday of each month—option expiration day (OED).Everybody has a theory as to what happens on option expiration day.Some that I have read about only in the past week (as I write this it is theday after a “quadruple witching day”) include:
T••••
Stocks gravitate towards round numbers.Extreme countertrend moves occur in the last hour.The market tends to trend the week before option expiration day.Fade the market at the end of option expiration day.
And on and on. Everyone wants to game the market that day, and probablymore money is lost by traders on that day then any other day of the month.Let us look at a couple of ideas that have withstood the test of time andhave demonstrated results that are statistically significant when placedaround option expiration day. None of these ideas by themselves generatean enormous number of trades (there are only so many option expirationdays and we are still looking for extreme conditions), but taken as a groupthey add up.
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All data used for testing the following systems are from the S&P andthe NDX in the years 1988–2003. The trading vehicle could be SPY or S&Pfutures, or QQQ or NDX futures depending on the index we are looking at.
OED SYSTEM #1: DON’T FIGHT THE TRENDIn general it is not that great an idea to buy a four-month high. Four-monthclosing highs have occurred on the S&P 407 times since 1988. Buying onthose days and closing out the position one week later has resulted in a successful trade in 58 percent of the occurrences (239 trades) with an expected value of 0.17 percent per trade, counting both winners and losers.Basically, the results are slightly less than expected given that the averagedaily return on the S&P 500 is about 0.04 percent.However, when the following three conditions occur it becomes profitable to buy:1. The S&P 500 makes a 4-month (80 trading days) closing high.2. The VIX closes within 20 percent of its 4-month low.3. It is the Friday the week before option expiration week (one week be-
fore option expiration day).If these conditions occur, then buy on the close of that Friday. Then sell onthe close of option expiration day one week later.The results are shown in Table 14.1 and Table 14.2. In summary, thereis an average gain of 1.14 percent per trade. Taking out the VIX conditionstill results in a decent system but one not as strong: 17 out of 23 successful trades with an average gain of 0.65 percent per trade. Leaving in the VIXcondition but taking out the condition that states OED occurs in one weekleaves us with 191 out of 304 successful trades and an average gain of 0.28percent. It appears that the proximity of OED is critical to the trade.For example, as shown in Figure 14.1 (see page 158), the S&P 500 hit afour-month closing high at 1396.06, the VIX had a four-month closing low at19.63, and OED was one week away. Buying at the close and holding forthat week resulted in a 1.86 percent gain.
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TABLE 14.1
OED System #1—ResultsAll Trades
Long Trades
171.14%5
171.14%5
Winning TradesAverage Profit %Average Bars HeldMaximum Consecutive Winning Trades
15 (88.24%)1.38%59
15 (88.24%)1.38%59
Losing TradesAverage Loss %Average Bars HeldMaximum Consecutive Losing Trades
2 (11.76%)–0.68%52
2 (11.76%)–0.68%52
All TradesAverage Profit/Loss %Average Bars Held
TABLE 14.2
OED System #1—The Trades
Entry Date
EntryPrice
Exit Date
ExitPrice
%Change
MAE %
MFE %
1/13/19894/14/19895/12/19897/14/19895/11/19902/8/19914/12/19912/10/19953/10/19954/13/19955/12/19959/8/19959/13/199611/8/19962/12/19987/9/199911/12/1999
283.87301.36313.84331.84352359.35380.4481.46489.57509.23525.55572.68680.54730.821,024.141,403.281,396.06
1/20/19894/