StockIndexFuturesTradingCollection-M[1]

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STOCK INDEX FUTURES TRADING COLLECTION

“Using the TICK to identify the intraday trend”

by David Bean (Active Trader, May 2006).

2 “Counterpunch stock index futures system"

by Active Trader Staff (Active Trader, Nov. 2002)

7 “Extreme open-close days”

by Xavier Maria Raj (Active Trader, April 2005).

9 “The Fibonacci Swing Filter”

by Gomu Vetrivel (Active Trader, Feb. 2005).

13 “Trading the opening gap”

by John Carter (Active Trader, Dec. 2004).

17 “Hitting the street: The S&P 500 futures' intraday reactions to economic reports”

by David Bukey (Active Trader, May 2005).

21 “Sector vs. index: The single stock futures-Dow spread”

by Keith Schap (Active Trader, Nov. 2005).

27 “Trading the basis: How stock index arbitrage impacts the market”

by David Lerman (Active Trader, March 2003).

31 “Stock index spreads: S&P vs. Naz”

by Keith Schap (Active Trader, May 2006).

35 “The multibar range breakout system”

by Dennis Meyers, PH.D. (Active Trader, Jan. 2004).

39 “Following through in the S&Ps”

by Thom Hartle (Active Trader, Dec. 2003).

44 “Getting in on follow-through days”

by Thom Hartle (Active Trader, Jan. 2004).

49 “Follow-through in the E-Mini Nasdaq 100”

by Thom Hartle (Active Trader, Aug. 2004).

54 “Up-down volume and next-day follow-through”

by Thom Hartle (Active Trader, Dec. 2004).

60 “E-Mini morning reversal and afternoon breakout patterns”

by Gomu Vetrivel (Active Trader, Jan. 2006).

66 “The telltale spread”

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T

he TICK indicator measures intraday momentum in New York Stock Exchange (NYSE) stocks by tracking the difference between upticking stocks (last price higher than previous price) and downticking stocks (last price lower

than previous price). The TICK subtracts the number of downticking stocks from the number of upticking ones to gener-ate a momentum snapshot of the market at any given time.

For example, if at 10 a.m. 2,000 stocks were trading higher than their previous

prices while 1,500 stocks were trading lower than their previous prices, the TICK value would be +500 (2,000-1,500). Traders typically use the TICK indicator to gauge the level of buying or selling pressure throughout the day. If the TICK reading is high, the market is showing “internal” strength, which is different from the “outward” price movement.

According to popular interpretation, TICK levels that correspond with price action help confirm the market’s direc-tion, but TICK values that diverge from price can warn of possible reversals. For example, a typical bullish signal occurs when the S&P 500 is climbing when the TICK is positive (or trending higher). However, if the S&P 500 is rising but the TICK turns negative (or trends lower), the rally could be nearing its end. (For more information on the TICK, see “TICK basics.”)

From analysis to trading

This kind of analysis depends on logical-ly defining “high” or “low” TICK read-ings. The following study analyzed intraday TICK behavior in the past five years to find potentially bullish and bearish TICK levels. However, the resulting trade strategy also relied on NYSE volume analysis and price action to confirm the intraday trend and

gener-2 www.activetradermag.com • May 2006 • ACTIVE TRADER

The second-largest NYSE volume occurred in the first 15 minutes of trading, which is a good time to determine the daily trend because price moves are more meaningful when backed by large volume.

FIGURE 1 FIVE-YEAR AVERAGE NYSE VOLUME (15-MINUTE INTERVALS)

Using the TICK

TO IDENTIFY THE INTRADAY TREND

Analyzing TICK readings over the past five years provides

the foundation for an intraday trend strategy.

BY DAVID BEAN

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ate trade signals.

The focus was on the first 15 minutes of the daily trade session because over the past five years the NYSE’s second-largest volume has occurred during this period. Above-average TICK readings generate buy signals at 9:45 a.m. ET. By contrast, sell signals require below-aver-age TICK readings along with down-ward price moves (gaps or weakness) within the first 15 minutes.

The logic of this approach is that high-volume periods combined with price moves and TICK readings in the same direction help determine the trend for the rest of the day.

Trend clues at market’s open Figure 1 shows the NYSE’s average vol-ume of more than 3,700 stocks in 15-minute intervals from 9:30 a.m. to 4 p.m. ET over the past five years. While vol-ume is highest in the last 15 minutes of trading, the second-highest volume occurred in the first 15 minutes of the regular session — from 9:30 a.m. to 9:45 a.m.

The day’s open and close stand out because institutional traders must exe-cute large amounts of market-on-open and market-on-close orders; the price moves that occur during these periods can leave clues about the market’s likely direction. Although you can trade stocks and stock-index futures in the after-hours electronic market, those markets offer very little volume to offset posi-tions against overnight breaking news while the U.S. stock market is closed for 17.5 hours.

Defining TICK thresholds

Table 1 shows statistics behind the TICK indicator’s historical behavior over the past five years. Overall, the TICK had a bullish bias. The average daily TICK high was nearly twice as large as the daily low (+1,007 vs. -673). Also, the TICK’s average close after 15 minutes was not only above zero (+201) but exceeded +300 almost six times as often as it fell below -300. Buy and sell signals

must take this upside bias into account. The strategy’s bullish and bearish thresholds are based on the TICK’s aver-age close of +201 after 15 minutes. There are thresholds for both high and low readings as well as for where the TICK closes. The high and low thresholds are +750 and -350, which are approximately +/-550 from the average close of +201; the closing TICK thresholds are +500 and -100, which are approximately +/- 300 from the average close of +201.

This means the TICK is bullish if it either reaches +750 within the first 15 minutes of trading or closes above +500 at 9:45 a.m. Similarly, the TICK is bearish if it drops below -350 within the first 15

ACTIVE TRADER • May 2006 • www.activetradermag.com 3

TICK basics

T

he TICK is a very short-term (intraday) indicator that measures the bullish (upticking) or bearish (downticking) activity in NYSE stocks throughout the day. TIKI is the symbol for the same indicator calcu-lated on Dow Jones Industrial Average stocks; some data services also supply the TICK calculated on Nasdaq stocks.

The TICK is a breadth indicator that gives traders an intraday look at the “inter-nal” strength or weakness of the market — that is, the strength or weakness beyond whether the overall market is up on a point or percentage basis. By com-paring the number of stocks advancing to stocks declining, the indicator reflects the market’s up or down momentum at a given moment.

For example, if the S&P 500 index is up marginally but downticking stocks are consistently outnumbering upticking stocks (and the number of downticking stocks is increasing, reflected by a downtrending TICK indicator), it is likely that only a relative handful of strong stocks are propping up the overall market. When buying completes in these stocks, a down move may result.

Two contrarian uses of the TICK indicator are to look for divergence between price and the indicator, and to use high or low TICK readings to identify momen-tum extremes (similar to how many traders use oscillators like the relative strength index or stochastics to locate overbought and oversold points).

A divergence occurs when price makes a new high (or low) but the TICK makes a lower high (or higher low), failing to confirm the price move and warn-ing of a slackenwarn-ing of momentum and potential stall or reversal. A similar phe-nomenon would be a steady trend in the TICK that runs counter to the trend of the market. Extreme high or low TICK readings sometimes accompany market climaxes.

Because the TICK is a snapshot of the market at a given moment (and is thus very volatile), it can be deceptive. Because of this, the TICK is commonly smoothed with a 10-period moving average to remove some of the “noise” and better reveal the indicator’s direction and patterns.

The TICK has had a bullish bias over the past five years. Its aver-age daily high is nearly double its daily low, its average close every 15 minutes was +201, and it exceeded +300 nearly six times as often as it dropped below -300 (based on 15-minute intervals).

TABLE 1 FIVE-YEAR TICK STATS

TICK value

Five-year high: +1,541 Five-year low: -1,495 Avg. daily high: +1,007 Avg. daily low: -673 Avg. closing value

after 15 minutes: +201 No. of 15-minute

closes above +300: 12,855 No. of 15-minute

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minutes or closes below -100 at 9:45 a.m. Trade rules

There are three long-entry and five short-entry rules. Although each rule is independent, meaning it could be tested individually, all eight rules are combined to make a single system designed to trade the S&P 500 E-Mini futures (ES). The rules were also tested on the Russell 2000 E-Mini (ER2), Midcap 400 E-Mini (EMD), Mini Dow (YM), and Nasdaq 100 E-Mini (NQ).

Long entries (at 9:45 a.m. ET): 1. If the TICK’s high > +750 and the

TICK’s low > -350, buy at the market.

2. If the TICK’s close > +500 and the

TICK’s low > -350, buy at the market.

3. If the close of the first 15-minute bar > the open + the average range (high - low) of all 27 of yesterday’s 15-minute bars, and the TICK’s low > -350, buy at the market. Short entries (at 9:45 a.m. ET): 1. If today’s open > yesterday’s low -

(2 * the average range of all 27 of yesterday’s 15-minute bars), the TICK’s low < -350, and the TICK’s high < +750, sell short for the next 15 minutes (until 10 a.m.) at today’s open (limit).

2. If today’s open > yesterday’s low - (2 * the average range of all 27 of

yesterday’s 15-minute bars), the TICK’s close < -100, and TICK’s high < +750, sell short for the next 15 minutes (until 10 a.m.) at today’s open (limit).

3. If the close of the first 15-minute bar > the previous day’s close, the TICK’s low < -350, and the TICK’s high < +750, sell short for the next 15 minutes (until 10 a.m.) at yesterday’s close (stop).

4. If the close of the first 15-minute bar > the previous day’s close, the TICK’s close < -100, and the TICK’s high < +750, sell short the next 15 minutes (until 10 a.m.) at yesterday’s close (stop).

5. If the close of the first 15-minute bar < the open - the average range of all 27 of yesterday’s 15-minute bars and the TICK’s high < 750, then sell short at the market. Exit:

1. Stop-loss = R * contract’s point value * average range of all 27 previous 15-minute bars since the same time yesterday. (R = multiplier that can be optimized for each market or risk preference; default = 5.)

2. Exit on close if still in market. Trade logic

All eight signals are based on TICK behavior and price direction within the first 15 minutes of trading. Two of the three long rules focus solely on exceed-ing TICK’s bullish thresholds and stay-ing above its bearish ones. Also, four of the five short rules require TICK to pen-etrate the bearish levels as it stays below the bullish ones.

The other two rules don’t wait for either TICK threshold to be met. To trig-ger a buy signal, price must climb fur-ther than the average range of all of yes-terday’s 15-minute bars (long rule 3), or price must drop the same distance before selling short (short rule 5).

4 www.activetradermag.com • May 2006 • ACTIVE TRADER

Strategy code

Tradestation EasyLanguage Code

{Data1 is @ES.D or any of the following: @ER2.D, @YM.D, @NQ.D, @EMD.D Data2 is $TICK. Both Data1 and Data2 are 15 minute charts – a custom ses-sion should be built for @YM.D to trade between 8:30 am CST and 3:15 pm CST instead of starting at 7:20 am CST.

*there are 27, 15 minute bars in the trading day} Inputs: R(5), L1(27);

If Time=945 and H of data2 > 750 and L of data2 > -350 Then Buy Next Bar at market;

If Time=945 and C of data2 > 500 and L of data2 > -350 Then Buy Next Bar at market;

If Time=945 and Open > LowD(1) - 2*Average(Range,27) and L of data2 < -350 and H of data2 < 750 Then Sell Short Next Bar at OpenD(0) Limit;

If Time=945 and Open > LowD(1) - 2*Average(Range,27) and C of data2 < -100 and H of data2 < 750 Then Sell Short Next Bar at OpenD(0) Limit;

If Time=945 and C > C[1] and L of data2 < -350 and H of data2 < 750 Then Sell Short Next Bar at CloseD(1) Stop;

If Time=945 and C > C[1] and C of data2 < -100 and H of data2 < 750 Then Sell Short Next Bar at CloseD(1) Stop;

If Time=945 and C>(O + Average(Range,27)) and L of data2 > -350 Then Buy Next Bar at market;

If Time=945 and C<(O - Average(Range,27)) and H of data2 < 750 Then Sell Short Next Bar at market;

SetStopLoss(R*BigPointValue*Average(Range,L1)); SetExitonClose;

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However, these rules still require the TICK to remain above its average low (-350) or below its average high (+750), respectively.

The first four short rules must be exe-cuted using stop or limit orders. For

example, if price climbs above yester-day’s close by 9:45 a.m., it must drop back to that point before the system sells short with a stop order in the second 15 minutes of the trading session (until 10 a.m.). Also, if the opening price gaps

below yesterday’s close, the strategy sells short with a limit order at today’s open in the second 15 minutes. That gap, however, must be smaller than twice the average range of yesterday’s 15-minute bars.

The stop-loss depends on the average range of yesterday’s 15-minute bars, the contract’s point value, and a multiplier (R) to adjust the stop size. If that stop-loss isn’t hit, the sys-tem holds the trade until the end of the day to let profits run.

Trade example

Figure 2 shows a 15-minute chart of the March 2006 S&P 500 E-Mini futures (ESH06) on Feb. 2. The market dropped slightly at the open, and the TICK readings at 9:45 a.m. were low (-383), high (+125), and close (+99). The S&P 500 had a short bias because the TICK’s low was below the bearish threshold of -350 and its high was below the bullish level of +750.

The system placed a limit order at 9:45 a.m. at the E-Mini’s opening price (1,284.00), and the S&P 500 The S&P 500 E-Mini fell slightly on Feb. 2, and the TICK low (-383) was bearish by 9:45

a.m. because it dropped below the lower threshold (-350). The system sold short at 1,284, and the S&P E-Mini sold off throughout the day — a gain of 12.75 points.

FIGURE 2 TRADE EXAMPLE

Source: Tradestation 8.1

The strategy was profitable across the major indices in different time periods. All markets had a favorable percentage of gains, and all but one had average profits per trade of at least $54.72. However, the Nasdaq 100 didn’t perform as well.

TABLE 2 OVERALL TEST RESULTS

Start No. of Profit Drawdown Percentage Avg. Profit Avg. Avg. Ratio

date trades profitable profit per factor winning losing avg. win/

trade trade trade avg. loss

E-Mini S&P 500 9/11/97 1,128 $67,237.50 $10,637.50 53.90% $59.61 1.33 $444.10 -$400.74 1.11 E-Mini Russell 2000 11/7/01 726 $42,990.00 $6,280.00 52.75% $59.21 1.33 $454.73 -$393.90 1.31 E-Mini Midcap 400 1/28/02 709 $38,800.00 $4,760.00 52.47% $54.72 1.35 $401.53 -$338.13 1.19 E-Mini Nasdaq 100 7/1/99 1,006 $14,160.00 $23,760.00 51.29% $14.08 1.05 $529.22 -$549.72 0.96 Mini Dow 7/28/02 579 $37,910.00 $3,520.00 56.82% $65.47 1.60 $307.39 -$259.10 1.19

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hit this price between 9:45 a.m. and 10 a.m., going short 0.25 points from the day’s high. The market sold off through-out the day, and the system exited at the close (1,271.25) for a 12.75-point gain.

The Russell 2000 E-Mini, Midcap 400 E-Mini, and mini Dow all took similar trades as each of these markets climbed back to the open and then dropped. No trade was triggered in the Nasdaq 100 E-Mini because this market didn’t trade back to the open.

Test results

The TICK strategy was tested on histori-cal intraday price data going back at least three years in the S&P 500 E-Mini futures, Russell 2000 E-Mini, Midcap 400 Mini, Mini Dow, and Nasdaq 100 E-Mini. Table 2 (p. 5) shows results for each index in different time periods from Sept. 11, 1997 to Feb. 1, 2006.

For comparison purposes, each index was also tested over the same time peri-od — Jan. 1, 2003 to Feb. 1, 2006 (Table

3). Comparing Tables 2 and 3 shows that although the average profit per trade dropped in recent years, the average trade is still large enough (at least $39.79) to make money after slippage and commission costs. (The Nasdaq 100 E-Mini’s average profit of $15.21 was the exception to this rule.) Average prof-its fell because the markets’ daily ranges have decreased in recent years.

The system trades often — roughly three times a week in each market over the past three years, or 500 trades in 750 trading days.

Overall, the system caught roughly 10 percent of the S&P 500’s 50-day aver-age daily trend. For example, if the S&P E-Mini has a 10-point daily range, and the system captures 10 percent of it, then its average profit is one point ($50). This roughly matches the sys-tem’s average profit in the S&P 500 in both time periods. (As of Feb. 1, the S&P E-Mini’s 50-day average range was 9.84 points.)

Further research

One idea that deserves additional atten-tion is to sell rallies short when the TICK signals a downtrend, or buy dips after it signals an uptrend at 9:45 a.m.

Instead of trading just one contract after any of the eight rules signal a trade, you could trade multiple contracts (e.g., one for each signal). However, you’d have to limit short positions to three to balance the size of long and short trades in the market.

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Counterpunch stock

index futures system

determined by the following formula:

CT = AC * PR / 4TR where

AC = Available capital PR = Percent risked

4TR = Four times the true range for the day preceding the entry Test period:January 1993 to July 2002.

Test data:Daily prices for the S&P 500, Nasdaq 100 and Dow Jones Industrial Average futures contracts. $25 deducted for slip-page and commission per contract traded.

Starting equity:$1 million (nominal).

Test results: The system did not fare as well on futures as it did on individual stocks. However, there are a few reasons for this that, when examined, make the results more understandable. (For

SAMPLE TRADES

Source: Omega Research ProSuite

Dow Jones Industrial (DJ), daily

Go long Go long

Go long Go long _{Go long} Go long

Go long Go short L-trail L-trail

L-trail L-trail L-trail

L-trail L-trail L-trail L-trail S-trail S-target Go short Go long Go long 20 27 June 10 17 24 July 8 15 22 29 August

10,400.00 10,200.00 10,000.00 9,800.00 9,600.00 9,400.00 9,200.00 9,000.00 8,800.00 8,600.00 8,400.00 8,200.00 8,000.00 7,800.00 7,600.00 Ac cou nt b ala nc e ( $) EQUITY CURVE 1/1/93 1/1/94 1/1/95 1/1/96 1/1/97 1/1/98 1/1/99 1/1/00 1/1/01 1/1/02

Trading System Lab

&

FUTURES OPTIONS

3,000,000 2,500,000 2,000,000 1,500,000 1,000,000 500,000 0

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ACTIVE TRADER • November 2002 • www.activetradermag.com 8

aggressively, which also would have created smoother equity growth.

Speaking of drawdown, note that both the maxi-mum drawdown and flat time for the test period are

not related to the current bear market. Instead, they are

both a function of the limited trading opportunities in the first part of the test period. Currently, the system is in a 20-percent drawdown, and although that is signif-icant, and much more than most traders can tolerate, it is a far cry from the 80-plus percent decline in equity for a buy-and-hold strategy in the Nasdaq 100 index.

Another way to improve the results could be to trade it on other futures markets as well, such as the currencies, energies and interest rates. Because of the system’s short-term nature, it is not suitable for agri-cultural commodities, which usually need longer trends to produce profits large enough to justify trad-ing (for non-professional traders).

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Disclaimer: The Trading System Lab is intended for educational purposes only to provide a perspective on different market concepts. It is not meant to recommend or promote any trading system or approach. Traders are advised to do their own research and testing to determine the validity of a trading idea. Past performance does not guarantee future results; historical testing may not reflect a system’s behavior in real-time trading.

LEGEND: End. equity ($) — equity at the end of test period • Total return (%) — total percentage return over test period • Avg. annual ret. (%) —

average continuously compounded annual return • Profit factor — gross profit/gross loss • Avg. tied cap (%) — average percent of total available cap-ital tied up in open positions • Win. months (%) — percentage profitable months over test period • Max. DD (%) — maximum drop in equity •

Longest flat — longest period, in months, spent between two equity highs • No. trades — number of trades • Avg. trade ($) — amount won or lost by

the average trade • Avg. DIT— average days in trade • Avg. win/loss ($) — average winning and losing trade, respectively • Lrg. win/loss ($) — largest winning and losing trade, respectively • Win. trades (%) — percent winning trades • TIM (%) — amount of time there is at least one open posi-tion for entire portfolio, and each market, respectively • Tr./Mark./Year — trades per market per year • Tr./Month — trades per month for all markets

LEGEND: Cumulative returns — Most recent: most recent return from start to

end of the respective periods • Average: the average of all cumulative returns from start to end of the respective periods • Best: the best of all cumulative returns from start to end of the respective periods • Worst: the worst of all cumulative returns from start to end of the respective periods • St. dev: the standard devia-tion of all cumulative returns from start to end of the respective periods Annualized returns — The ending equity as a result of the cumulative returns, raised by 1/n, where n is the respective period in number of years

Send Active Trader your systems

If you have a trading system or idea you’d like tested, send it to us at the Trading System Lab. We’ll test it on a portfolio of stocks or futures (for now, maximum 60 markets, using the last 2,500 trading days), using true portfolio analysis/optimization. Most system-testing software only allows you to test one mar-ket at a time. Our system-testing technique lets all marmar-kets share the same account and is based on the interaction within the portfolio as a whole.

Start by e-mailing system logic (in TradeStation’s

EasyLanguage or in an Excel spreadsheet) and a short description to [email protected], and we’ll get back to you.

Note: Each system must have a clearly defined stop-loss level

and a suggested optimal amount to risk per trade.

Profitability Trade statistics

End. equity ($): 2,067,431 No. trades: 1,258 Total return (%): 107 Avg. trade ($): 849 Avg. annual ret. (%): 7.87 Avg. DIT: 3.4 Profit factor: 1.17 Avg. win/loss ($): 15,166 (7,894) Avg. tied cap (%): 3 Lrg. win/loss ($): 105,730 (57,373) Win. months (%): 48 Win. trades (%): 36.3

Drawdown TIM (%): 70 28.1

Max. DD (%): 30.4 Tr./Mark./Year: 21.9 Longest flat (m): 44.6 Tr./Month: 10.9

ROLLING TIME WINDOW RETURN ANALYSIS

Cumulative 12 24 36 48 60

months months months months months

Most recent: -8.30% 20.77% 26.18% 75.15% 89.69% Average: 9.10% 19.44% 31.22% 43.14% 55.41% Best: 52.95% 86.74% 101.76% 135.61% 147.21% Worst: -15.56% -22.47% -25.96% -17.60% -6.38% St. dev.: 15.03% 26.07% 37.05% 44.71% 46.18% Annualized 12 24 36 48 60

months months months months months

Most recent: -8.30% 9.90% 8.06% 15.04% 13.66% Average: 9.10% 9.29% 9.48% 9.38% 9.22% Best: 52.95% 36.36% 26.36% 23.89% 19.84% Worst: -15.56% -11.95% -9.53% -4.72% -1.31% St. dev: 15.03% 12.28% 11.08% 9.68% 7.89% STRATEGY SUMMARY

one thing, the amazing results from the stock test make compar-isons a little unfair.)

The equity chart reveals the results for the futures markets real-ly didn’t start to take off until late 1997 — almost halfway through the testing period. The big reason for this is that up until late 1996, the S&P 500 was the only tradable market. Trading in the other two contracts didn’t begin until late 1996 (Dow) and late 1997 (Nasdaq). If you look at only the second half of the test period, the estimated average annual return would probably be almost twice the 7.87 percent the complete system produced.

Adding other (foreign) stock indices to the mix probably would have enhanced results even more by adding a bit of diversification, which would have kept the drawdowns lower. Trading more mar-kets would also have allowed us to trade each market a little less

DRAWDOWN CURVE 0% -5% -10% -15% -20% -25% -30% -35% 1/1/93 1/1/94 1/1/95 1/1/96 1/1/97 1/1/98 1/1/99 1/1/00 1/1/01 1/1/02

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TRADING Strategies

9 www.activetradermag.com • April 2005 • ACTIVE TRADER

T

raders are always looking for clues regarding when a price move is likely to follow through vs. stop in its tracks. Short-term traders especially watch price behavior during a given trading system to deter-mine whether to hold existing positions overnight or get out

before the close. The relationships between open and close prices is often used to gauge the momentum during a given trading peri-od. For example, a bar that opens and closes at roughly the same price in the middle of a trading bar reflects balanced trading during that period. A bar that follows several bars with higher highs and lows and opens at a low price, trades much higher, and then closes back near the open, might imply the upside momentum has evaporated and a downturn could be imminent.

The patterns we will analyze here occur when price opens near one end

of the day’s trading range (the high or low) and closes near the other extreme of the day’s range. We’ll refer to these as strong-closing and weak-strong-closing bars. We’ll test these patterns to see what kind of price action typically follows them, and if they

Upper band — top 10% of bar

Lower band — bottom 10% of bar

The upper band is the top 10 percent of the bar and the lower band is the bottom 10 percent of the bar. An open or close that occurs in either of these bands can be considered to be in an extreme of the bar’s range.

FIGURE 1 EXTREME BANDS

Source: TradeStation

Russell 2000 index (RUT.X), daily

Strong close days

16 23 550.00 545.00 540.00 535.00 530.00 525.00 520.00

A strong-close day (SCD) opens in the lower band (the bottom 10 percent of a price bar) and closes in the upper band (the top 10 percent of the bar).

FIGURE 2 STRONG CLOSE DAYS

Extreme

OPEN-CLOSE

days

Bars that close near their highs or lows can sometimes trick

traders into thinking follow-through price action is likely.

The following analysis incorporates the opening price and

a few simple risk-control and exit rules to capture

follow-through moves when they are most likely.

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ACTIVE TRADER • April 2005 • www.activetradermag.com 10

can be used as the basis for a trading strategy.

Defining strong and weak bars The first step is to define what consti-tutes strong- and weak-closing bars. To do this, we’ll use “bands” that capture the top and bottom 10 percent of a price bar. The upper band is the top 10 per-cent of the bar and the lower band is the bottom 10 percent of the bar (see Figure 1). An open or close that occurs in either of these bands can be considered to be in an extreme of the bar’s range.

A strong-close day (SCD) opens in the lower band and closes in the upper band (Figure 2). Similarly, a weak-close day (WCD) opens in the upper band and closes in the lower band (Figure 3). These days can be defined as follows:

Strong-close day (SCD) = Open < (Low + Range/10) and Close > (High -Range/10)

Weak-close day

July 7 14 21

A weak-close day (WCD) opens in the upper band and closes in the lower band.

FIGURE 3 WEAK-CLOSE DAYS

Short

Exit

Exit Exit Exit

ExitExit Exit Exit Short Buy _Buy Buy Buy Buy Buy 21 28 Aug. 4 11 18 25 500.00 495.00 490.00 485.00 480.00 475.00 470.00 465.00 460.00 455.00 450.00

In most cases, SCDs and WCDs were followed by price movement in the expected direction.

FIGURE 4 BASIC TRADE SIGNALS

Strategy code

The following EasyLanguage code can be downloaded from the Active Trader Strategy Code page at www.activetradermag.com/code.htm. Code for other software platforms is also available.

Initial system test:

VAR:X(0),Y(0),R(0); R=RANGE;

IF C>H-((R/10)) AND O<L+((R/10)) THEN X=1 ELSE X=0; IF C<L+((R/10)) AND O>H-((R/10)) THEN Y=1 ELSE Y=0; IF X=1 THEN Buy Next Bar AT H+.05 STOP;

IF Y=1 THEN Sell Short Next Bar AT L-.05 STOP; Sell This Bar AT C;

Buy to Cover This Bar AT C; Revised system test: VAR:X(0),Y(0),R(0); R=RANGE;

IF C>H-((R/10)) AND O<L+((R/10)) THEN X=1 ELSE X=0; IF C<L+((R/10)) AND O>H-((R/10)) THEN Y=1 ELSE Y=0; IF X=1 THEN Buy Next Bar AT H+.05 STOP;

IF Y=1 THEN Sell Short Next Bar AT L-.05 STOP; Sell This Bar AT C;

Buy to Cover This Bar AT C;

Sell Next Bar AT MEDIANPRICE-.05 STOP;

Buy to Cover Next Bar AT MEDIANPRICE+.05 STOP; Sell AT ("P1") Next Bar H+10 LIMIT;

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Weak-close day (WCD) = Open > (High - Range/10) and Close < (Low + Range/10)

Strong-close days suggest demand was high from the begin-ning of the trading session and continued to be robust until the closing bell; weak-close days indicate selling pressure was dominant from the start of the day until the close.

Let’s hypothesize that because demand or supply was solid through the end of the day, there will be some follow-through movement the day after an SCD or WCD.

Trade rules

Now we can design some simple rules based on this pattern to test our hypoth-esis:

1. Go long the day after an SCD with a buy-stop order one tick above the high of the SCD.

2. Go short the day after a WCD with a sell-stop order one tick below the low of the WCD. 3. Exit all trades on the close.

The logic is simple: An extremely strong or weak close implies further movement in that direction the follow-ing day, and a move beyond the range of the SCD or WCD confirms the up or down momentum.

Figure 4 (p. 10) shows the signals gen-erated based on the strategy for the Russell 2000 index (RUT.X). Notice this period is dominated by rising prices, and there were more SCDs than WCDs. For the most part, there was follow-through in the expected direction after both types of bars.

Initial test

These basic rules were tested on the Russell 2000 and S&P 400 Midcap (MID.X) indices over 10 years of daily data, from Jan. 1, 1994 to Aug. 29, 2003. The results for the Russell 2000 are shown in Table 1 and the S&P 400 results are in Table 2.

The strategy yielded profit factors (gross profits divided by gross losses) of 2.29 and 1.94 for the respective indices. The total number of trades generated were 637 for the Russell and 482 for the S&P 400, or approximately six and five trades per month, respectively. The win-ning percentage was around 70 percent for the Russell 2000 and 64 percent for the S&P 400 Midcap, respectively. These performance figures are quite respectable for such a simple, easy-to-execute strategy — especially considering that the parameters were unoptimized. Now let’s see if this basic performance can be enhanced with additional risk-control and profit-taking rules.

Augmenting the approach

We conducted a second test using simple stop-loss and price target rules. The stop-loss will be the midpoint of the SCD or WCD, and the profit target will be 10 index points above the For such a simple set of trading rules, the test results were surprisingly

good. Each market produced an average of six trades per month.

TABLE 1 INITIAL TEST: RUSSELL 2000

Performance summary: All trades Total net profit $361,845.97

Gross profit $641,972.50 Gross loss ($280,126.53)

Total # of trades 637 Percent profitable 70.49 Number winning trades 449 Number losing trades 188 Largest winning trade $10,275.00 Largest losing trade ($12,200.00)

Average winning trade $1,429.78 Average losing trade ($1,490.03)

Ratio avg. win/avg. loss .96 Avg. trade (win & loss) $568.05 Max. consec. winners 13 Max. consec. losers 5 Avg. # bars in winners 0 Avg. # bars in losers 0 Max. intraday drawdown($21,050.02)

Profit factor 2.29 Max. # contracts held 500 Account size required $21,050.02 Return on account (%) 1,718.98

The S&P 400 produced fewer trades than the Russell 2000 (482 vs. 637). It had a lower (but still quite good) profit factor of 1.94 and a winning percent-age of 64 percent.

TABLE 2 INITIAL TEST: S&P 400

Ratio avg. win/avg. loss 1.09 Avg. trade (win & loss) $457.00 Max. consec. winners 11 Max. consec. losers 5 Avg. # bars in winners 0 Avg. # bars in losers 0 Max. intraday drawdown($24,525.00)

Profit factor 1.94 Max. # contracts held 1 Account size required $24,525.02 Return on account (%) 898.17

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high of an SCD or below the low of a WCD:

Stop-loss for long trade = Midpoint minus one tick Stop-loss for short trade = Midpoint plus one tick Long target = High plus 10 points

Short target = Low minus 10 points As was the case with the basic trading rules, these values are representative and have not been optimized. The definitions and logic for the complete strategy are:

D1 = Current day (the SCD or WCD) D2 = Next day

H1 = High of current day L1 = Low of current day

M1 = Midpoint, or median price, of current day

1. Long Entry: On an SCD (D1) place a buy-stop order for the next day (D2) at the high (H1) plus one tick.

2. Short Entry: On a WCD (D1) place a sell-stop order for the next day (D2) at the low (L1) minus one tick.

3. Long Exit: Place a stop-loss order at the median price (M1) minus one tick.

4. Short Exit: Place a stop-loss order at the median price (M1) plus one tick.

5. Long Target: Place a limit sell order at the high (H1) plus 10 points.

6. Short Target: Place a limit buy order at the low (L1) minus 10 points.

The performance for the two indices after incorporating these stop-loss and target rules are shown in Tables 3 and 4. Notice that although the winning per-centages for each index declined (but both remained about 60 percent), their respective profit factors increased to 3.08 and 2.21, indicating the strategy became more efficient. Also notice the maximum drawdowns decreased in both cases. The number of trades remained the same. Simplicity and room

for experimentation

As is often the case, a simple trading idea produced some favorable results.

This trading approach could be applied without any help from a computer, and it lends itself to further modification and experimentation.

Testing across a wide range of markets and experimenting with different upper and lower bands, stop-loss levels and profit targets are excellent departure points.

Ý

The winning percentage declined for the Russell 2000 (as it did for the S&P 400), but the profit factor increased.

TABLE 3 ENHANCED SYSTEM TEST: RUSSELL 2000

Despite the lower winning percentage for both indices, the strategy was more efficient: It produced more profit with lower drawdown.

TABLE 4 ENHANCED SYSTEM TEST: S&P 400

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BY G. VETRIVEL

P

rices move every second of every day, which means many, if not most, market fluctuations rep-resent random “noise” rather than meaningful price moves. No matter how short the time frame a trader operates on, some price action is simply irrelevant.

The challenge is finding a way to filter out noise and identi-fy tradable price moves in your chosen time horizon. There are many ways to accomplish this. Some traders require an initial trade setup to be validated by a secondary rule, or filter, before acting upon the signal. Other traders approach the problem at the source and attempt to smooth price data itself, so they apply trading approaches to data that has already had its “noise” removed.

The method outlined here presents a way to smooth data using Fibonacci-based price moves. This process consists of defining a price-swing structure that filters out shorter-term price fluctuations so you react only when a trend of significant magnitude changes direction.

This Fibonacci-swing technique will be illustrated using a simple stop-and-reverse (SAR) strategy, which means when a long position is exited a new short position is simultaneously estab-lished, and vice versa. The strategy will then be tested on eight years of daily price data in four stock indices. Defining price swings with Fibonacci ratios

The most common tool for smoothing price data is the moving average, which traders use to define trends and issue trade signals. For example, if price moves above a moving average, the trend is considered up, while the oppo-site is true when price falls below the moving average.

The degree to which the data is smoothed and the length of the trend depends on how long the moving aver-age is: The longer the lookback period (e.g., 100 bars), the longer the trend the average represents and the more

short-term price fluctuations are removed from the data; the shorter the lookback period (e.g., 10 bars), the shorter the trend the average reflects.

Similar logic applies to defining Fibonacci price swings. A breakout above or below the range of a Fibonacci-defined price swing — for example, a 38.2-percent retracement of a previous move — can be considered the end of an existing trend or the beginning of a new trend, the magnitude of that trend being dependent on the size of the price swings. This logic allows us to objectively determine market tops and bottoms.

This technique does not attach any particular significance to a single Fibonacci ratio and it does not have a fixed lookback period, as does a moving average. The ratios (which can change for each bar) are determined by the current market conditions, which makes the Fibonacci-swing approach an adaptive smoothing technique. Also, this approach avoids the problem of lag that affects all moving averages (the longer the average, the longer it takes to respond to changes in price direction).

13 www.activetradermag.com • February 2005 • ACTIVE TRADER

Russell 2000 E-mini (ER), daily 38.2% 50% 1 2 0 9 23 March 8 15 22 29 595 590 585 580 575 570

Bar 1 is the new high and a short trade is triggered when the current bar (Bar 0) falls below the 50-percent level of Bar 2.

FIGURE 1 DEFINING A TOP AND GOING SHORT

The Fibonacci

SWING FILTER

One way to filter market noise and focus on tradable price

moves is to gauge price swings in terms of retracement

percentages. This approach creates an adaptive trading

system that adjusts to the market’s behavior.

TRADING Strategies

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Calculating Fibonacci price swings The rules for calculating Fibonacci swings for determining tops and bot-toms use the following definitions:

• Current bar = Bar 0; previous bar = Bar 1, etc.

• Fibonacci ratios used: 23.6 percent, 38.2 percent, 50 percent, 61.8 percent, 78.6 percent and 87.5 percent.

• Pairs of consecutive retracement percentages are always used to define price swings — i.e., 23.6 percent and 38.2 percent, 38.2 percent and 50 percent, etc. Pairing 23.6 percent and 50 percent would be incorrect, for example.

Defining a top/beginning of a down swing: If Bar 1 retraces between 38.2 and 50 percent of Bar 2’s range (measured downward from Bar 2’s high), and the low of Bar 0 is below the 50-percent level (the midpoint) of Bar 2’s range, then the highest high between the previous bot-tom and Bar 0 (including Bar 0) is a top. Other retracement ratios are applied in a similar fashion. For example, if Bar 1 retraces between 50 and 61.8 percent of Bar 2, and the low of Bar 0 is below the 61.8-percent level of Bar 2’s range (meas-ured downward from Bar 2’s high), then the highest high between the previous bottom and Bar 0 is a top. The same approach would be used for 23.6 percent and 38.2 percent, and so on.

Figure 1 shows how a top is defined using this technique. The low of Bar 1 retraces between 38.2 and 50 percent of Bar 2’s range, and Bar 0’s low is below the level of a 50-percent retracement of Bar 2. The top is the highest high

between the previous bottom and Bar 0 (including Bar 0), which means Bar 1’s high is the top.

These rules are reversed to define lows.

Defining a bottom/beginning of an up swing: If Bar 1 retraces between 38.2 and 50 percent of Bar 2’s range (meas-ured upward from Bar 2’s low), and the high of Bar 0 is above the 50-percent level of Bar 2’s range, then the lowest low between the previous top and Bar 0 is a bottom.

Similarly, if Bar 1 retraces between 50 and 61.8 percent of Bar 2, and the high of Bar 0 is above the 61.8-percent level of Bar 2’s range (measured upward from Bar 2’s low), then the lowest low between the previous top and Bar 0 is a bottom.

Figure 2 (p. 14) shows the identification of a bottom using 23.6 and 38.2 Fibonacci percentages: The high of Bar 1 retraced between 23.6 percent and 38.2 percent of Bar 2 and the high of Bar 0 retraced more than 38.2 percent of Bar 2. The bottom is the lowest low between the previous top (Bar A) and Bar 0. As a result, the low of Bar 1 is the bottom.

Note: There cannot be two consecutive bottoms or tops.

Entry and exit rules

The following rules are for the Fibonacci-swing trading system we will test on different stock indices:

1. Enter long/exit short if Bar 0’s high is above the 38.2-per-cent level but below the 50-per38.2-per-cent level of Bar 1’s range. Place a buy-stop order to exit the existing short position and enter long at the 50-percent level of Bar 1’s range.

Repeat these calculations for the different percentage pairs to determine the range that captures the current retracement.

2. Enter short/exit long if Bar 0’s low is below the 61.8-per-cent level but above the 50-per61.8-per-cent level of Bar 1’s range. Place a sell-stop order to exit the existing long position and enter short at the 50-percent level of Bar 1’s range.

Repeat these calculations for the different percentage pairs to determine the range that captures the current retracement.

3. Special outside bar condition: If there is an outside bar (a bar with a high above the previous high and a low below the previous low) or a gap bar (a low above the previous high or a high below the previous low), place the buy-stop order at the high or the sell-stop order at the low.

ACTIVE TRADER • February 2005 • www.activetradermag.com 14

Performance summary: All trades

Total net profit $662,375 Open position P/L $775 Gross profit $1,668,640 Gross loss $1,006,265

Total number of trades 771 Percent profitable 44.36% Number of winning trades 342 Number of losing trades 429 Largest winning trade $34,225 Largest losing trade $8,550.00

Average winning trade $4,879.06 Average losing trade $2,345.60

Ratio avg. win/avg. loss 2.08 Average trade (win and loss) $859.11 Max. consecutive winners 6 Max. consecutive losers 8 Avg. number of bars in winners 4 Avg. number of bars in losers 1 Max intraday drawdown $39,665

Profit factor 1.66 Max. number of contracts held 1 Account size required $39,665

The tests produced an average of nearly 700 trades per market over eight years of daily data, which lends credibility to the results.

TABLE 1 S&P 500 TEST RESULTS

Russell 2000 E-mini (ER), daily

38.2% 23.6% Bottom A Top 1 2 0 19 May 6 13 20 27 June 10 17 520 515 510 505 500 495 490 485

Bar 1 is the new low and a long trade occurs when Bar 0 rises above the 38.2-percent retracement level of Bar 2 (measured from the bottom of Bar 2).

FIGURE 2 DEFINING A BOTTOM AND GOING LONG

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If the stop-orders are not hit the next day, the appropriate percentage pairs are calculated on that day’s bar and new orders are placed accordingly. For each bar, the system checks to see which per-centage pair applies to the current retracement. As a result, the percentages can change from bar to bar — e.g., 38.2-and 50-percent one day, 50- 38.2-and 61.8-per-cent the next and so on.

When the price swing is moving up, ratios are calculated from the high to determine the long exits and short entries. Similarly, ratios are calculated from the low to determine the short exits and long entries.

Trade examples and test results

Returning to Figure 1 (p. 13), because the low of Bar 1 retraced between 38.2 and 50 percent of Bar 2 (measured from the top of Bar 2 down), enter a sell-stop order at the 50-percent level of Bar 2.

In Figure 2 (p. 14), because the high of Bar 1 retraced between 23.6 percent and 38.2 percent of Bar 2 (measured from the bottom of Bar 2 up), enter a buy-stop order at the 38.2-per-cent level of Bar 2.

Because this is a stop-and-reverse strategy, the reverse orders act as trailing stops for the current positions.

Tables 1, 2 , 3 and 4 show the results of tests conducted on the S&P 500 (SPX), Russell 2000 (RUTX), NIFTY (Indian NSE Index), and Dow Jones Industrial Average (INDU). The test

spanned eight years of daily price data –– from Jan. 1, 1997 to Oct. 25, 2004.

The performance in these tables indicates the strategy is robust: It has a winning percentage rate of at least 40 percent, an average win/loss ratio of 2 and profit factor (gross prof-it/gross loss) of 1.55 in all indices, except the Russell 2000, which had exceptionally good performance and a profit factor of 3.33. Slippage and commission charges were not included.

The strategy produced more than 700 trades on average in each index — more than 2,800 trades total. The high number of trades adds credibility to test results — confidence in future results is directly related to the number of samples in testing. By comparison, positive results for a long-term trend-following

15 www.activetradermag.com • February 2005 • ACTIVE TRADER

System code

The following TradeStation EasyLanguage code for the Fibonacci stop-and-reverse system can be copied at www.activetradermag.com/code.htm.

if l>=h[1] then Sell Short Next Bar at l-.05 stop;

if l<h[1] and l>=h[1]-(h[1]-l[1])*.236 then Sell Short Next Bar at h[1]-(h[1]-l[1])*.236 -.05 stop;

if l<h[1]-(h[1]-l[1])*.236 and l>=h[1]-(h[1]-l[1])*.382 then Sell Short Next Bar at h[1]-(h[1]-l[1])*.382-.05 stop; if l<h[1]-(h[1]-l[1])*.382 and l>=h[1]-(h[1]-l[1])*.5 then Sell Short Next Bar at h[1]-(h[1]-l[1])*.5-.05 stop; if l<h[1]-(h[1]-l[1])*.5 and l>=h[1]-(h[1]-l[1])*.618 then Sell Short Next Bar at h[1]-(h[1]-l[1])*.618-.05 stop; if l<h[1]-(h[1]-l[1])*.618 and l>=h[1]-(h[1]-l[1])*.786 then Sell Short Next Bar at h[1]-(h[1]-l[1])*.786-.05 stop; if l<h[1]-(h[1]-l[1])*.786 and l>=h[1]-(h[1]-l[1])*.875 then Sell Short Next Bar at h[1]-(h[1]-l[1])*.875-.05 stop; if l<h[1]-(h[1]-l[1])*.875 and l>l[1] then Sell Short Next Bar at l[1]-.05 stop;

if l<=l[1] then Sell Short Next Bar at l-.05 stop; if h<=l[1] then Buy Next Bar at h+.05 stop;

if h>l[1] and h<=l[1]+(h[1]-l[1])*.236 then Buy Next Bar at l[1]+(h[1]-l[1])*.236+.05 stop;

if h>l[1]+(h[1]-l[1])*.236 and h<=l[1]+(h[1]-l[1])*.382 then Buy Next Bar at l[1]+(h[1]-l[1])*.382+.05 stop; if h>l[1]+(h[1]-l[1])*.382 and h<=l[1]+(h[1]-l[1])*.5 then Buy Next Bar at l[1]+(h[1]-l[1])*.5+.05 stop; if h>l[1]+(h[1]-l[1])*.5 and h<=l[1]+(h[1]-l[1])*.618 then Buy Next Bar at l[1]+(h[1]-l[1])*.68+.05 stop; if h>l[1]+(h[1]-l[1])*.618 and h<=l[1]+(h[1]-l[1])*.786 then Buy Next Bar at l[1]+(h[1]-l[1])*.786+.05 stop; if h>l[1]+(h[1]-l[1])*.786 and h<=l[1]+(h[1]-l[1])*.875 then Buy Next Bar at l[1]+(h[1]-l[1])*.875+.05 stop; if h>l[1]+(h[1]-l[1])*.875 and h<h[1] then Buy Next Bar at h[1]+.05 stop;

if h>=h[1] then Buy Next Bar at h+.05 stop;

Total net profit $2,664.37 Open position P/L $5.06 Gross profit $3,807.75 Gross loss $1,143.38

Total number of trades 690 Percent profitable 52.03% Number of winning trades 359 Number of losing trades 331 Largest winning trade $84.44 Largest losing trade $16.53

Average winning trade $10.61 Average losing trade $3.45

Ratio avg. win/avg. loss 3.07 Average trade (win and loss) $3.8614 Max. consecutive winners 11 Max. consecutive losers 6 Avg. number of bars in winners 4 Avg. number of bars in losers 1 Max intraday drawdown $42.64

Profit factor 3.33 Max. number of contracts held 100 Account size required $42.64

The Russell 2000 posted the highest profit factor and winning percentage of all the indices.

TABLE 2 RUSSELL 2000 TEST RESULTS

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Total number of trades 767 Percent profitable 43.02% Number of winning trades 330 Number of losing trades 437 Largest winning trade $1,423.27 Largest losing trade $337.60

Ratio avg. win/avg. loss 1.99 Average trade (win and loss) $22.71 Max. consecutive winners 6 Max. consecutive losers 10 Avg. number of bars in winners 4 Avg. number of bars in losers 1 Max intraday drawdown $1,253.21

Profit factor 1.50 Max. number of contracts held 100 Account size required $1,253.21 Return on account 1,389.76%

The average winning trade/losing trade ratio was 2.00 for all four tests.

TABLE 4 DOW JONES INDUSTRIAL AVERAGE TEST RESULTS

Source: TradeStation strategy that produces only 50 trades

over eight years of data will not be near-ly as reliable as the statistics shown here. Smooth sailing

This technique is not the only way to smooth data, but all smoothing or filter-ing methods share the same goal — to isolate the tradable moves in a market on the time frame you wish to trade.

Ý

Total number of trades 729 Percent profitable 43.48% Number of winning trades 317 Number of losing trades 412 Largest winning trade $195.60 Largest losing trade $88.05

Ratio avg. win/avg. loss 2.05 Average trade (win and loss) $5.33 Max. consecutive winners 6 Max. consecutive losers 12 Avg. number of bars in winners 4 Avg. number of bars in losers 1 Max intraday drawdown $744.78

Profit factor 1.58 Max. number of contracts held 1,000 Account size required $744.78

One downside is that maximum consecutive losers outnumbered maximum consecutive winners in three of the four tests.

TABLE 3 NIFTY INDEX TEST RESULTS

T

he Fibonacci series is a number progression in which each successive number is the sum of the two immedi-ately preceding it: 1, 2, 3, 5, 8, 13, 21, 34 and so on. As the series progresses, the ratio of a number in the series divided by the immediately preceding number approaches 1.618, a number that is attributed significance by many traders because of its appearance in natural phe-nomena (the progression of a shell’s spiral, for example, as well as in art and architecture, including the dimensions of the Parthenon and the Great Pyramid). The inverse, .618 (.62), has a similar significance.

Some traders use fairly complex variations of Fibonacci num-ber to generate price forecasts, but a basic approach is to use ratios derived from the series to calculate likely price targets.

For example, if a stock broke out of a trading range and rallied from 25 to 55, potential retracement levels could be calculated by multiplying the distance of the move (30 points) by Fibonacci ratios — say, .382, .50 and .618 — and then subtracting the results from the high of the price move. In this case, retracement levels of 43.60 [55 - (30*.38)], 40 [55 - (30*.50)] and 36.40 [55 - (30*.62)] would result.

Similarly, after a trading range breakout and an up move of 10 points, a Fibonacci follower might project the size of the next leg up in terms of a Fibonacci ratio — e.g., 1.382 times the first move, or 13.82 points in this case.

The most commonly used ratios are .382, .50, .618, .786, 1.00, 1.382 and 1.618. Depending on circumstances other ratios, such as .236 and 2.618, occasionally are used.

Additional reading

The following articles have more information about Fibonacci num-bers:

“Technical Tool Insight: Fibonacci ratios”

(Active Trader, April 2002, p. 78). This is a more detailed primer on the

properties of Fibonacci numbers. “Absolute price projections” by Tom DeMark and Rocke DeMark (Active Trader, July 2004, p. 38). This article explores the authors’ unique application of Fibonacci ratios to determine potential price targets.

The Fibonacci series

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BY JOHN CARTER

O

pening price gaps — the distance between the reg-ular-session opening price and the previous day’s closing price — are stomach-churning events when the market makes a big move against you, but they represent low-risk trade opportunities if you know which gaps are likely to be followed by predictable patterns.

In terms of the price behavior that fol-lows opening gaps, not all markets are created equal. Gaps in individual stocks

and commodities do not act the same as those in “multi-item” instruments such as stock indices because a news item will control the entire market instead of just a portion of it. Earnings announcements, corporate scandals and other company-specific events can create gaps in a com-ponent stock’s chart that never get filled. Because of the unpredictable nature of various events that can impact the price of an individual stock, they make poor candidates for the opening-gap trade.

In contrast, stock index futures such as the E-mini S&P (ES) or the mini-sized Dow (YM) are better candidates for opening-gap plays because they consist of multiple components that respond dif-ferently to news. For example, although a stock index futures contract may gap up on a news item, there will be individual stocks within the index that will either ignore the news or sell off. This weighs the index down and creates a trade opportunity as the market fills the gap. The best markets for gap plays The S&P 500 and the Dow are the best

markets to trade the opening gap because of the diversity of their compo-nent stocks. Both indices represent collec-tions of stocks from different industries that are more likely to react independent-ly to news events. In the technology-heavy Nasdaq, opening price gaps can take longer to fill because the majority of the stocks will react similarly to news.

The key to trading opening gaps is being able to predict the likelihood a particular gap will be filled. Dissecting the market conditions that produce a gap is as important as analyzing a gap itself. For example, an opening gap fol-lowing high pre-market cash trading volume can take weeks to get filled because high volume increases the odds the market will continue to move in the direction of the gap.

Some of the biggest gaps are caused by major news events, such as the out-break of a war, but gaps caused by minor news items are much more common. Generally, such gaps are smaller, fill quickly (see Table 1) and can be “faded” (the act of trading against the direction

17 www.activetradermag.com • December 2004 • ACTIVE TRADER

Trading Strategies

&

FUTURES OPTIONS

Between Jan. 15, 2002, through February 2004 (528 occurrences), an average of 76 percent of all opening gaps closed at some point during the same day. This is the breakdown by day of week. Adding the pre-market volume filter increased the percentages.

TABLE 1 FILLING THE OPENING GAP: RAW DATA

Source: Tradethemarkets.com Percentage of

Day gaps filled

Monday 65%

Tuesday 77%

Wednesday 79%

Thursday 82%

Friday 78%

The higher the volume, the greater the likelihood the market will continue in the direction of the opening gap. As a result, no trade is taken when vol-ume is above 70,000.

TABLE 2 TRADE MANAGEMENT GUIDELINES

Source: Tradethemarkets.com Pre-market volume

in key stocks Position size Trade target

Less than 30,000 Full size Exit entire position at gap fill Between 2/3 size Exit half at 50 percent of gap 30,000 and 70,000 fill, half at gap fill

Above 70,000 No “fade” trade No “fade” trade

Trading the

OPENING GAP

Watching pre-market volume is a good way to determine whether

to trade or fade the opening move.

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of the gap) more effectively. Let’s look at the specific criteria for identifying those gaps with the best chances of reversing. The pre-market volume indicator The most important indicator for deter-mining which opening gaps can be faded is the pre-market volume in a spe-cific set of stocks.

Check the pre-market volume at 9:20 a.m. ET (10 minutes before the regular cash session opens) in the following stocks: KLA-Tencor Corporation (KLAC), Maxim Integrated Products, Inc. (MXIM), Novellus Systems, Inc. (NVLS) and Applied Materials, Inc. (AMAT). These representative stocks were selected through a trial-and-error process.

If the market is really set up to move, there will be significant volume in the cash market in pre-market trading. If the market is setting up for a “head fake” (a move in one direction that is quickly reversed), pre-market volume will be low, which reflects a lack of conviction in the move. This is the preferred setting for an opening-gap trade.

If the pre-market stocks have each traded less than 30,000 shares at this time, analysis of the prior 500 trading days shows the opening gap, up or down, had an 80-percent chance of fill-ing the same day. However, if the vol-ume for each stock is between 30,000 and 70,000, the gap only has about a 60-per-cent chance of filling that day, while the midpoint of the gap has an 85-percent chance of being hit.

Finally, if the pre-market volume for each stock is above 70,000, the chances of the gap filling that day drop to 30 per-cent. In these cases, you should ignore the news and follow the direction of the gap. Table 2 provides guidelines for using volume information to manage trades. As the volume increases, the position size shrinks and the profit-tak-ing becomes more conservative.

If one stock has volume above 70,000 but the others are below the threshold, check to see if the news pertains to this company alone. If it does, ignore it. If the news is not specific to the company, trade the more conservative position.

The strategy

Figure 1 is a five-minute chart of the mini Dow futures. You can use any time interval — a one-minute, five-minute or 15-minute chart, etc. — as long as you can view the opening. This means the chart must be set up to reflect the open-ing and closopen-ing of the regular tradopen-ing session, 9:30 a.m. to 4 p.m. ET (4:15 p.m. for stock index futures prices). Many traders are used to watching a separate chart of the continuous 24-hour futures session, but of course, opening gaps

won’t show up.

Figure 1 shows the first day in a set of back-to-back earnings announcements that caused opposite reactions in the market. On the morning of Oct. 15, 2003, the Dow gapped up 47 points as a result

of a positive earnings report from Intel (INTC). On this day, pre-market volume was below 30,000.

As a result, the appropriate trade is to immediately short the gap on the open using a full position size, as indicated in Table 2. To keep things simple, we’ll use nine contracts as a full position, which makes a two-thirds position six contracts and a one-third position three contracts. We will use a $100,000 account, which means we are trading one contract for each $11,100 in the account for a full posi-tion. Although you can trade a mini Dow

or E-mini S&P contract with only a few thousand dollars, this trading plan con-trols risk by limiting exposure relative to the amount of available capital.

Use a 1:1.5 reward/risk ratio (risking 1.5 points to make 1 point) for gap trades

ACTIVE TRADER • December 2004 • www.activetradermag.com 18

Mini Dow futures (YM), five minute Gap is filled for a 47-point

gain, or $235 per contract (47 points x $5 per point).

11:00 12:00 13:00 14:00 15:00 9:00 10:00 10/15/03 9,830 9,820 9,810 9,800 9,790 9,780 9,770 9,760 9,750 9,740 9,730 9,720 9,710 9,700

This 47-point-plus opening gap in the mini Dow futures was filled in the first hour of trading for a $235 per-contract profit.

FIGURE 1 THE OPENING GAP

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