Double Seven Strategy

[jswanson 10]

It's time to look at another simple trading system which can be found in the book, ”Short Term Trading Strategies That Work” by Larry Connors and Cesar Alvarez. In this article we are going to look at the Double 7 strategy. This is a simple strategy that can be applied to the major market indices such as DIA, DOW and QQQ. It can also be applied to the futures markets.

 

The rules of this system are very simple.

 

• The instrument must be above its 200 day moving average.
  
• If the instrument closes at a 7-day low - buy.
  
• If a long position is open and the instrument closes at a 7-day high - sell.
  

The trading system follows two basic concepts we have talked a lot about on this website. Namely when trading the major market indices, like the S&P, an effective strategy is to buy pullbacks in a major up trend. This system does just that. The major up-trend is defined by price being above the 200-day moving average. A pull-back is defined as a close below the lowest-low over the past seven days. Once a trade is entered, we simply look for a new seven day high to exit. Super simple. Below is an example of some trades on the S&P Cash Index. Click the image for a larger view.

 

 

 

 

Looking at the trading rules, you will also notice it's a long-only system. Later in this article I will also reverse the rules and test it on the short-side. But for now, let's look at the performance for the long-only system. At this point I'm going to test it on the S&P cash index ($SPX.X for TradeStation).

 

Unless otherwise stated, all the tests performed in this article will be based on the following assumptions:

 

• Starting account size of $100,000.
  
• The number of shares traded will be based on volatility estimation and risking no more than $2,000 per trade.
  
• Volatility is estimated with a five times 20-day ATR calculation. This is done to normalize the amount of risk per trade.
  
• The P&L is not accumulated to the starting equity.
  
• There are no deductions for commissions and slippage.
  
• There are no stops.
  

 

Here is the position sizing formula used:

 

Shares=$2,000 per trade / ( 5 * ATR(20) * Big_Point_Value )

 

 

 

This looks very promising. Keep in mind, the system has no stops.

 

Is The 7-Day Optimized?

Let's look at changing the 7-day look-back period for two reasons. First, I would like to see if the default seven value is optimized. Secondly, I would like to know if other nearby values are used, would the system remain viable. In short, I would like to test the robustness of the look-back period. For example, if we change the 7-day low value to six, I don't want to see the system's equity curve drastically change. Likewise, if we increase the 7-day low value to eight, I don't want to see a drastic change in results. The neighboring values around seven should still produce positive results. In fact, it would be great to see the system remain profitable over a wide range of values.

 

I will use TradeStation's optimization feature to optimize the look-back period over the values 2-20 in increments of one. Keep in mind this single input value controls two look-back periods. The first is the entry look-back and the second is the exit look-back. As the trading system is defined, both these variables use the same value. The results of the test are in the graph below. You can click the image to see a larger view. The x-axis contains the look-back period while the y-axis contains the trading systems total P&L.

 

 

This looks great. Any value you choose produces positive results. Each change in the look-back period also does not drastically change from neighboring values. The default value of seven is near the peek, which is six, but it's not the most optimal number. It's also important to keep in mind we will be using the default value of seven for other instruments as well and it's highly unlikely the bar graph for those instruments would look exactly like what we have here. In any event, I think this brings a lot of confidence to the look-back period.

 

 

Is The Regime Look-Back Optimized?

Just as we did for the look-back period for our entry trigger, let's perform the same type of test on the regime look-back period. Again, I will use TradeStation's optimization feature to optimize the look-back period over the values 20-200 in increments of ten. The results are in the graph below. You can click the image to see a larger view. The x-axis contains the look-back period while the y-axis contains the trading systems total return.

 

 

This looks great as well. All values produce positive returns. In general, the longer the look-back period the more profit the system generates. While I did not study the numbers just beyond 200, I feel confident that a 200-period look-back is not optimized.

 

Taken both these tests we can feel confident that this system does not appear to be optimized and it's robust given a wide variety of input values.

 

 

Going Short

The original system is a long-only system. Let's try to use the current rules to short the market. We can do this by simply reversing the rules. In other words, we will modify the regime filter to only open trades when price is below the 200-day moving average. Trades will then open when price makes a new 7-day high and close when they make a new 7-day low.

 

• The instrument must be below its 200 day moving average.
  
• If the instrument closes at a 7-day high - sell short.
  
• If a position is open and the instrument closes at a 7-day low - buy to cover.
  

 

I created a separate trading system to study only the short-side. The results of the system can be seen in the equity graph below.

 

 

This is not so great. Most of the time the equity curve is below the zero line. It's choppy and ugly. Clearly the market participants' psychology during a bear market is different than simply a mirror image of those found in a bull market. One would think shorting new highs in a bear is a good idea, and maybe it is, but this system is not successful at capturing profit. Taking a wild guess simply from past experience, I have found that exiting quickly during bear markets tends to work better than in bull markets. Thus, maybe a modification of the exit rules to only hold a trade until the first profitable day or only hold for a maximum of three days may produce significantly better results. However, such modifications are best left for another day.

 

To further test our shorting idea, let's now look at testing a range of look-back periods just like we did during our bull market. If our shorting concept is truly flawed, I would expect to see not much improvement in modification of our look-back period. In fact, since my wild guess is we need to exit quickly to remain profitable, I would expect to see greater losses as we continue to increase our look-back period. Likewise, I would expect to see greater profit as we shorten our look-back period. I will optimize the look-back period over the values 2-20 in increments of one. The results are in the graph below. You can click the image to see a larger view.

 

 

Just as I expected. In general the shorter the look-back period, the more profitable. However, since this is our first look at the Double Seven Strategy, I don't want to over complicate it by introducing a shorting component. We'll keep it simple for now and apply our long-only strategy to several major market ETFs.

 

Double Seven Strategy

Confident the long-only trading rules are robust and appear to hold potential, let's now test this system on several major ETFs. Let's test, SPY, QQQ, DIA, and IWM. For this test we are going to use all the same trading assumptions and position sizing as we did above except for the following modifications.

 

• $50,000 starting account
  
• Risk 2% of account equity per trade
  
• P&L is not reinvested
  

 

 

Conclusion

The Double Seven Strategy does produce positive results across the four major market ETFs we tested. Is this system tradable with real money as is? Probably not. Remember, there are no stops. However, this does appear to be a great start to a viable system. I would imagine if some of the larger losing trades could be eliminated by some type of stop method, this system could be viable with real money.

 

Downloads

 

You can download the source code here.

[natureboy1618 10]

have to consider costs though..

[SIUYA 11]

additionally, what is the buy and hold return for the same period?

or what is the get set long only, and use a stop of 7 days below the entry, but not an exit above the entry....ie; you let things run once in an established position that trends.

 

Comparing these might give an insight into costs as well as risk return costs of purely day trading.

(Otherwise I am sure everyone appreciates the ideas jswanson - thanks)

[jswanson 10]

have to consider costs though..

 

I would if it was a trading system, but it's not a trading system. Note, it does not even have stops! What this article demonstrates is a potential market edge.

 

However for the sake of commissions and slippage, below are the SPY results of adding...

 

1. 2% Stop Loss
   
2. Deducting $20 + $.01 per share per round trip.
   

 

Net Profit: $33,232

Profit Factor: 1.96

Avg. Trade Net Profit: $216.37

Total Return: 33.32%

Annual Rate of Return: 1.50%

[natureboy1618 10]

Nice. Thank you for this. I'm checking it out now.

[jswanson 10]

additionally, what is the buy and hold return for the same period?

or what is the get set long only, and use a stop of 7 days below the entry, but not an exit above the entry....ie; you let things run once in an established position that trends.

 

Comparing these might give an insight into costs as well as risk return costs of purely day trading.

(Otherwise I am sure everyone appreciates the ideas jswanson - thanks)

 

Going back to the start of SPY (1993) a buy-and-hold strategy based upon the same risk position sizing would produce...

 

Net Profit: $165,933

Profit Factor: N/A

Avg. Trade Net Profit: $165,933

Total Return: 165%

Annual Rate of Return: 5.09%

 

Clearly much better results if you entered in 1993 and rode those bear markets where you will see 40% drawdowns. Also, dividends are not included.

 

Since the year 2000 things would look like this for the buy-and-hold:

 

Net Profit: $3,220

Profit Factor: N/A

Avg. Trade Net Profit: $3,220

Total Return: 3.2%

Annual Rate of Return: .24%

 

Since the year 2000 things look like this for the Double Seven

 

Net Profit: $13,732

Profit Factor: 1.49

Avg. Trade Net Profit: $140.12

Total Return: 13.7%

Annual Rate of Return: .96%

[jswanson 10]

I've updated this strategy based upon reader feedback. I created a new post here.

[metalhead 10]

Does this give as good of gains as dogs of the dow?

[metalhead 10]

Is this something that can be done intraday? Initiate a long position when the index closes at a 7 bar low.

[JohnyIve 0]

Wel, gonna check it)

[CrazyCzarina 17]

Too old to reply but It looks like a good strategy to be tested at least ones so that we can improve our skills for strategy.

[Laser1000 0]

PLS reupload the code….thanks in advance

[fxeconomist 11]

On 4/9/2013 at 4:59 PM, jswanson said:

It's time to look at another simple trading system which can be found in the book, ”Short Term Trading Strategies That Work” by Larry Connors and Cesar Alvarez. In this article we are going to look at the Double 7 strategy. This is a simple strategy that can be applied to the major market indices such as DIA, DOW and QQQ. It can also be applied to the futures markets.

 

The rules of this system are very simple.

 

 

• The instrument must be above its 200 day moving average.
• If the instrument closes at a 7-day low - buy.
• If a long position is open and the instrument closes at a 7-day high - sell.

 

The trading system follows two basic concepts we have talked a lot about on this website. Namely when trading the major market indices, like the S&P, an effective strategy is to buy pullbacks in a major up trend. This system does just that. The major up-trend is defined by price being above the 200-day moving average. A pull-back is defined as a close below the lowest-low over the past seven days. Once a trade is entered, we simply look for a new seven day high to exit. Super simple. Below is an example of some trades on the S&P Cash Index. Click the image for a larger view.

 

 

 

 

Looking at the trading rules, you will also notice it's a long-only system. Later in this article I will also reverse the rules and test it on the short-side. But for now, let's look at the performance for the long-only system. At this point I'm going to test it on the S&P cash index ($SPX.X for TradeStation).

 

Unless otherwise stated, all the tests performed in this article will be based on the following assumptions:

 

 

• Starting account size of $100,000.
• The number of shares traded will be based on volatility estimation and risking no more than $2,000 per trade.
• Volatility is estimated with a five times 20-day ATR calculation. This is done to normalize the amount of risk per trade.
• The P&L is not accumulated to the starting equity.
• There are no deductions for commissions and slippage.
• There are no stops.

 

 

Here is the position sizing formula used:

 

Shares=$2,000 per trade / ( 5 * ATR(20) * Big_Point_Value )

 

 

 

This looks very promising. Keep in mind, the system has no stops.

 

Is The 7-Day Optimized?

Let's look at changing the 7-day look-back period for two reasons. First, I would like to see if the default seven value is optimized. Secondly, I would like to know if other nearby values are used, would the system remain viable. In short, I would like to test the robustness of the look-back period. For example, if we change the 7-day low value to six, I don't want to see the system's equity curve drastically change. Likewise, if we increase the 7-day low value to eight, I don't want to see a drastic change in results. The neighboring values around seven should still produce positive results. In fact, it would be great to see the system remain profitable over a wide range of values.

 

I will use TradeStation's optimization feature to optimize the look-back period over the values 2-20 in increments of one. Keep in mind this single input value controls two look-back periods. The first is the entry look-back and the second is the exit look-back. As the trading system is defined, both these variables use the same value. The results of the test are in the graph below. You can click the image to see a larger view. The x-axis contains the look-back period while the y-axis contains the trading systems total P&L.

 

 

This looks great. Any value you choose produces positive results. Each change in the look-back period also does not drastically change from neighboring values. The default value of seven is near the peek, which is six, but it's not the most optimal number. It's also important to keep in mind we will be using the default value of seven for other instruments as well and it's highly unlikely the bar graph for those instruments would look exactly like what we have here. In any event, I think this brings a lot of confidence to the look-back period.

 

 

Is The Regime Look-Back Optimized?

Just as we did for the look-back period for our entry trigger, let's perform the same type of test on the regime look-back period. Again, I will use TradeStation's optimization feature to optimize the look-back period over the values 20-200 in increments of ten. The results are in the graph below. You can click the image to see a larger view. The x-axis contains the look-back period while the y-axis contains the trading systems total return.

 

 

This looks great as well. All values produce positive returns. In general, the longer the look-back period the more profit the system generates. While I did not study the numbers just beyond 200, I feel confident that a 200-period look-back is not optimized.

 

Taken both these tests we can feel confident that this system does not appear to be optimized and it's robust given a wide variety of input values.

 

 

Going Short

The original system is a long-only system. Let's try to use the current rules to short the market. We can do this by simply reversing the rules. In other words, we will modify the regime filter to only open trades when price is below the 200-day moving average. Trades will then open when price makes a new 7-day high and close when they make a new 7-day low.

 

 

• The instrument must be below its 200 day moving average.
• If the instrument closes at a 7-day high - sell short.
• If a position is open and the instrument closes at a 7-day low - buy to cover.

 

 

I created a separate trading system to study only the short-side. The results of the system can be seen in the equity graph below.

 

 

This is not so great. Most of the time the equity curve is below the zero line. It's choppy and ugly. Clearly the market participants' psychology during a bear market is different than simply a mirror image of those found in a bull market. One would think shorting new highs in a bear is a good idea, and maybe it is, but this system is not successful at capturing profit. Taking a wild guess simply from past experience, I have found that exiting quickly during bear markets tends to work better than in bull markets. Thus, maybe a modification of the exit rules to only hold a trade until the first profitable day or only hold for a maximum of three days may produce significantly better results. However, such modifications are best left for another day.

 

To further test our shorting idea, let's now look at testing a range of look-back periods just like we did during our bull market. If our shorting concept is truly flawed, I would expect to see not much improvement in modification of our look-back period. In fact, since my wild guess is we need to exit quickly to remain profitable, I would expect to see greater losses as we continue to increase our look-back period. Likewise, I would expect to see greater profit as we shorten our look-back period. I will optimize the look-back period over the values 2-20 in increments of one. The results are in the graph below. You can click the image to see a larger view.

 

 

Just as I expected. In general the shorter the look-back period, the more profitable. However, since this is our first look at the Double Seven Strategy, I don't want to over complicate it by introducing a shorting component. We'll keep it simple for now and apply our long-only strategy to several major market ETFs.

 

Double Seven Strategy

Confident the long-only trading rules are robust and appear to hold potential, let's now test this system on several major ETFs. Let's test, SPY, QQQ, DIA, and IWM. For this test we are going to use all the same trading assumptions and position sizing as we did above except for the following modifications.

 

 

• $50,000 starting account
• Risk 2% of account equity per trade
• P&L is not reinvested

 

 

 

Conclusion

The Double Seven Strategy does produce positive results across the four major market ETFs we tested. Is this system tradable with real money as is? Probably not. Remember, there are no stops. However, this does appear to be a great start to a viable system. I would imagine if some of the larger losing trades could be eliminated by some type of stop method, this system could be viable with real money.

 

Downloads

 

You can download the source code here.

Looks great, thanks for sharing. I wonder, is it possible to adapt this EA for MT5 platform. I use one from Hotforex.

[aimhi 10]

I hope you might have got this EA working on your MT5 platform or have you been using any other profitable EA now.

[RJo 10]

IMHO, the best feature of the Double Seven entry strategy is that buys and does not sell in equity-based markets. Large scale selling short in the primary stock markets requires a financed loan of shares from a broker, so it's less common than buying. Therefore, selling in a stock-tracking market generally isn't profitable--even where derivative instruments provide cheaper access to selling.

Edited November 4, 2024 by RJo