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THE CHARTIST


Using Price To Filter Seasonal Trades

08/22/11 12:51:53 PM PST
by Alan Peiris and Kay Peiris

Combining seasonality with price action can be a useful addition to the trader's arsenal of trading systems.

The use of time rather than price has largely been attributed to legendary chartist W.D. Gann. Noted traders such as Arthur Merrill and Larry Williams have used seasonal patterns to trade both stocks and stock index futures, and Stock Trader's Almanac has done a good job of identifying seasonal trends. It is clear, however, that merely using time as a trading tool may not lead to optimal outcomes. Using price to filter seasonal trends may have more potential, and it is widely believed that many large institutions use price action to utilize seasonal trends.

THE THEORY
Historically, the last few days of each month and the first few days of the following month have produced greater gains compared to other periods within every month. This has been ascribed to the movement of money into retirement funds. The stock indexes, unlike commodities, have an upward bias, and selling short profitably in this field is notoriously difficult. Our intent was to factor in this upward bias in developing a system.

The first week of the trading month contains exploitable seasonal tendencies. The aim is to develop a long-only model based on price action to trade this seasonal trend. The primary goal was to develop a model capable of trading the emini Russell 2000 futures.

THE MODEL
The entry:

We want to confine most of our trades into the first week and use a trend filter of the current close being greater than the close of 20 days ago. We also want to choose a day with low volatility in order to enter the market.

The exits:
Several exits are needed to accomplish different goals:

  • Price action dictates that the exit is needed for the market not behaving in a manner as anticipated. This is reflected in a percent decline of 1%, despite an open greater than the prior day's close.
  • The profit target exit is based on a very positive day yesterday (percent > 1) and the open of today is greater than the prior day's close in the first week of the month. We anticipate that the positive momentum will carry over to the next day and get out on the open tomorrow.
  • The disaster (intraday) stop is inserted at 0.96 of the maximum closing price in the current trade
  • The time-based stop is inserted if the trade does not show a profit after eight days.

We chose the system trading program BEHOLD! because we were familiar with its coding, its plethora of built-in time-based functions, and coding efficacy. The BEHOLD! code is provided here:

if wom[1]>3 and ranc[20] then buy today close;
if pct<-1 and o if pct[1]>1 and o>c[1] and wom=1 then exitlong tomorrow open;
exitlong tomorrow maxtradeclose*0.96 stop;
if barssinceentry>8 and tradeprofit<0 then exitlong today close;
wom=weekofmonth ran=range pct=((close-close[1])/close*100)

RESULTS
A segment of the trading system for a continuous daily futures contract of the emini Russell (TF) from December 11, 2001, to February 9, 2011, is shown in Figure 1. The first trade bar was set to $20. A commission of $7 with slippage of $20 was used with a margin of $4,000. The big point value is $100 for the emini Russell.



FIGURE 1: THE BEHOLD! SYSTEM. Here you see the buy & sell signals on the emini Russell continuous futures contract. A commission of $7 with slippage of $20 was used with a margin of $4,000. A big point value is $100 for the emini Russell.

The performance summary table in Figure 2 indicates average trades of $350 with a 52% win rate and a profit factor of 1.72. The average winner lasted nine days, with the average loser lasting only five days. More important, the maximum loser was only $2,455 with a maximum closed drawdown under $10,000. The model only trades about 10 times per year. The trend filter kept the model from trading, for example, from August to late December 2008. The emini Russell futures went from about 715 to about 430 during this period. The equity curve is shown in Figure 3 and illustrates the lack of major drawdowns.



FIGURE 2: PERFORMANCE SUMMARY OF THE EMINI RUSSELL FUTURES (DECEMBER 11, 2001-FEBRUARY 9, 2011). Here you see that average trades are $350 with a 52% win rate and a profit factor of 1.72. The average winner lasted nine days and the average loser lasted only five days. More important, the maximum loser was only $2,455 with a maximum closed drawdown under $10,000.



FIGURE 3: EQUITY CURVE OF THE EMINI RUSSELL FUTURES (DECEMBER 11, 2001-FEBRUARY 9, 2011). As you can see, there are very few drawdowns.

The emini Russell data reflects recent information to assess how this model would compare over a much longer term; we tested it on the cash Standard & Poor's 500 between 1971 and 2010, with the gain and loss set to percent rather than cash values.

Over 256 trades, the model proved profitable, although the holding periods were longer and accuracy slightly lower. The maximum drawdown was 28%. The model mostly avoided trading during the 1987 and 1990 market declines. The performance summary is displayed in Figure 4 and the equity curve is shown in Figure 5.



FIGURE 4: PERFORMANCE SUMMARY OF S&P 500 CASH (1971-2010). Over 256 trades, the model proved profitable, although the holding periods were longer and accuracy slightly lower. The maximum drawdown was 28%.



FIGURE 5: EQUITY CURVE OF THE S&P 500 CASH (1971-2010). Over this time period, the system proves to be very profitable.

DISCUSSION
Price action filtering does appear to produce profits in the seasonally favored first week of the month, although some trades may last longer if profitable, adhering to the dictate of closing losing trades early. The addition of price action other than the range function on the day of entry appeared to degrade model results.

Using the model on the big five stock index futures may increase the number of annual trades, although diversification may be an issue. However, the availability of emini contracts would work well in this regard, and the user could diversify among the five index futures for the price of one big contract. The success achieved in the Russell could be reproduced in the other major indexes.

We were pleased with its utility in trading the EFA (iShares MSCI EAFE index fund). Moreover, the basic premise appears to hold true not only for recent data but also for data going back several decades. While we do not suggest that readers trade this in its current form since our intent was merely to show how to combine price action with seasonality, they may wish to explore improving the model. These modifications could include using an opening range breakout rather than exiting on close as well as exiting based on a range function rather than percentage.

Combining seasonality with price action can be a worthwhile addition to the trader's arsenal of trading systems. Other seasonal trading patterns are well discussed by B. Thackray and B. Lindsay and offer the potential for similar price action modifications.

SUGGESTED READING

  • Williams, Larry [1999]. Long-Term Secrets To Short-Term Trading, John Wiley & Sons.
  • Hirsch, Yale, and Jeffrey Hirsch [2004]. Stock Trader's Almanac, John Wiley & Sons.
  • Thackray, Brooke, and Bruce Lindsay [2000]. Time In, Time Out, Upwave Media Inc.





Alan Peiris and Kay Peiris

Alan Peiris and Kay Peiris are independent traders and investors who favor a system-based philosophy and trade stocks, options, and futures. They may be reached at Kayay@embarqmail.com.

E-mail address: Kayay@embarqmail.com


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