The 5-Day Low And Low of The Range Trading Strategy (S&P 500 Mean Reversion)

Last Updated on April 18, 2023

The 5-Day Low And Low of The Range Trading Strategy

Here is the strategy in plain English:

  1. IBS must be lower than 0.25.
  2. The close must be lower than the lowest the previous 5 days.
  3. If those two simple criteria are met, go long at the close.
  4. The exit is at the close 5 days later.

This is a very simple strategy. No fancy tools and hardly any calculations. This is the result from January 2005 until October 2012: 102 trades, 68 winners and average of 0.98% per fill. This is way above the average return for any 5 day period which is 0.11% in the same period. The win ratio is 66.6% and the average winner is bigger than the average loser (617 USD vs 498 using 5000 USD per trade).

Here is a table including the profit factor. I was recommended to include the profit factor by one of the readers (although in my opinion, one can see that this strategy has high profit factor due to low max drawdown(?)):

Avg per trade #trades #wins Profit factor Annualized %
1 day 0.45 143 88 2.19 7.28
2 days 0.36 127 77 1.65 5.42
3 days 0.73 120 81 2.39 9.54
4 days 0.7 106 68 1.99 8.26
5 days 0.98 102 68 2.48 10.76
7 days 1.11 96 63 2.26 11.28
10 days 1.26 82 56 2.2 11.06
20 days 0.85 57 36 1.57 5.7

As we can see its profitability climaxes at around 3-7 days. If exit at 5 days this strategy has 10.76% annualized return by just staying in the market for 510 days compared to 2826 days for buy and hold!

Here is the equity curve using exit after 5 days (due to a bug in my software the calculations is done using just 50% of the capital, thus total gain is twice as much as shown):


Here is another illustration showing buy and hold vs the strategy (from January 2005 until July 2012):


The blue line is the strategy and the pink is buy and hold. (This strategy also works very well without the requirement of having to end lower than 0.25 on today’s range. But it works better to include the requirement.)

What happens if we turn it upside down and go short? Using 0.75 as criteria on today’s range gives a lot more fills compared to long. I need to increase it to 0.9 to get a similar number of fills. Over the same period, this has yielded almost 10%. It’s a lot harder to find good short strategies than long strategies.


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  • Equity curve looks good. My current thinking is to do an MR test building on this and the series I am doing by adding a volatility filter and see if it improves. Regards.

  • Have you looked at Big Time Swing System by Rob Hanna. Also mean reversion. have you heard from his blog quantifiable edges? But it is subscription, it format the same like this blog.

    • Hi,

      Yes, I read his blog from time to time. He does a lot of research, but I rather use my own research.

      • Oddmund yes I am subscribed, the only thing I really use is the CBI (seems like a hax??) and the Big Time Swing. All the other edges are good or mediocre or bad and i have seen some fail spectacularly. Currently trying out overnight edges, have no clue if it works, will take another year.

        I was just wondering whether you knew him because your study style is very similar, I like it. Except I don’t understand a few stuff.

        • His blog is good, but to me it’s information overload. He’s looking for patterns everywhere, and to me a lot of this is noise. I’m not sure if he trades on all this. I trade SPY now, but only 4-5 strategies. More than enough.

          • True that, newbies will probalby not realize that his best tool is the CBI if they blow up on his subpar edges that would be a shame. Ofcourse it’s the only thing he keeps propietary. That tends to happen with vendors.
            I do like the format of some of his graphs a bit better, compared to yours (no offense hehe). For example this system you exit after 5 closes. Sometimes he makes a table what would the results be after X=1 to X=10 closes instead of just 5 and see if results are robust. But I am spoiled because I am now too much used to his tables, that has max loss, max profit, profit factor that isn’t apparent here.

  • Yes, you’re right, but I’m not a vendor either. I write to keep track of myself and hopefully get some valuable input from other bloggers. But I do look at all things you mention before I start trading a strategy, but it takes time to publish it. But probably a good idea to publish all?

    • Well if it detracts from trading I wouldn’t. Only if it’s easy to implement.
      The one thing I am most interested in is profit factor, if other is not easy to publish.
      I can’t say I have alot valuable input. The stuff I trade now is mostly propietary unfortunately. I can say that BTS has 25% similar system to this. And Rob does have a twitter where sometimes CBI signals are given for free (imo not very smart if I was the vendor, but w/e), if you wish to trade without paying. Actually, I find it surprising you make money daytrading, I tried that and failed. And mechanical based swingtrading is better for me. So this is quite an interesting blog to read.

      • Lots of opportunities in daytrading. But I rather not share that since it can detoriate my strategies. I’m not trading GOOG or AAPL 🙂

      • Jon, are you still trading using BTS? Wanted to know if there is still an edge after so many years. Thanks.

  • I suppose all of your SPY strategies ends up making the same trades about the same dates? So you end up having a big exposure at some dates and no positions at some points. And the diversification into different strategies is a bit of an illusion.

      • Very interesting comments. I don’t agree about all diversification into strategies and trading only one market being an illusion though.

        IMO strategy and time diversification are very useful. Unfortunately asset diversification gets all the media bytes. Part of the reason being the field is dominated by quant and investors and their portfolios depend a lot on asset diversification to control risk. This in turn is because unlike TA folks, quant finance and investors define risk in terms of volatility or other N number of measures (like MAR, downside deviation etc). Just my 2cents.

        • Yes,one can trade S&P500 using different entries, for examples enter at open or on close. That reduces risk. Also, time diversification: daytrades vs. swingtrading. Lots of opportunities. The best thing is to have a lot of trades.

  • I tried this on a handful of ETFs and got consistently good results (though just using last two years of data). One change I made, entirely by accident, was to buy the next open rather than the close of day 5. But then I tweeked it a bit more and on day 6 instead of buying the open I set a limit price equal to the one-quarter point of day 5’s range. So its ((high – low)*.25) + low.

    • Hi Richard,

      I’m I correct with the following assumption: you buy on the 6th day if SPY falls 0.25 ATR from the open? Yesterday’s 5 day average ATR being High – Low?

      • I was not thinking or writing very clearly in my previous comment. By “day 5” I meant the day that generated a 5-day low. Just to make up numbers, say the range that day was 31 to 32 with a close at 31.10. It’s a 5-day low and closed in the bottom quarter of that day’s range. Then I would generate a limit order the next day at 31.25, the one-quarter point of the previous day’s range.

        The results were better than just buying the open. Testing it on SPY for the last two years generated 29 trades if buying the next open. Setting a limit gave me 27 trades – I lost one winner and one loser – but generally gave me lower entry prices. Maybe I will get the numbers together and stick it on my blog.

        Anyway, after I did all that I realized you were buying the close of the 5 day low and not the next open.

  • […] This is quite impressive. Why? Probably because the market is short term oversold and get a quick bounce up from a bad day. Buying if close is above 50 day average is no good at all using these criterias. Quite a difference from the above strategies that went long if above 200 day moving average. If holding to the close instead of selling at the open, the total P/L increases to 80% but the equity curve is a lot more erratic. So buying on a 5 day low is a lot better for holding several days. […]

  • Hi Oddmund,

    I tried to recreate your results in this strategy. I did not get the same results as you. Did you use data from yahoo!Finance?

      • Yes, I use adjusted close for calculating the returns. here is the year by year profit using 0.25 C-L/H-L limit, 5 day low and 5 day hold:

        (5 jan 05 – 5 dec 12)
        trades 110

        2005 -1.1%
        2006 2.1%
        2007 17.4%
        2008 21.6%
        2009 -3.3%
        2010 -0.9%
        2011 12.1%
        2012 -2.9%

  • I got 8/11 (-1.7%), 24/10 (0.4%), 9/10 (0.9%), 25/9 (0.3%) and 23/8 (-0.1%).

    I would have gotten 10/10 as well, but the 9/10 trade obviously “blocked” it. Im curious why you did not get 24/10 and 9/10?

    Here is the open high low close vol adjusted:

    24/10/2012 141.93 142.10 140.80 141.02 120179400 141.02
    09/10/2012 145.53 145.65 144.15 144.20 148872900 144.20

      • Here is the closes according to Yahoo!Finance. I suppose you dont use the same…?

        24/10/2012 141.02
        23/10/2012 141.42
        22/10/2012 143.41
        19/10/2012 143.39
        18/10/2012 145.82
        17/10/2012 146.20


        09/10/2012 144.20
        08/10/2012 145.64
        05/10/2012 146.14
        04/10/2012 146.13
        03/10/2012 145.09
        02/10/2012 144.50

        • Yes, I have exactly the same quotes. But as I said in my previous post, I only go long when the CLOSE is below the 5 day low (the 5 days previous today). If yesterdays 5 days low was 141, and today SPY closes at 141,01, there is no trade, even though if low was below 141. If it closes at 140.9 today, then I go long.

          • There you go, I thought it was lowest “close” previous 5 days. 🙂

            However, Im still not getting as good results as you.

            2005 -9.3%
            2006 10.1%
            2007 13.2%
            2008 0.7%
            2009 -5.2%
            2010 2.5%
            2011 11.6%
            2012 5.0%

            It seems like 2010-2012 is the same as your equity curve (which is not correct using 100% of capital??), but 2005-2009 is totaly different. I do not know if this is due to different datasets or just wrong programing from my behalf.