Four Down Days In A Row Trading Strategy

Last Updated on June 19, 2022 by Quantified Trading

What happens when SPY is down 4 days in a row? Let’s test 4 down days in a row trading strategy.

Entry is on the close and exit is on the first day with a close higher than the previous bar.

Four Down Days In A Row Trading Strategy

Why these rules? I believe you will benefit from buying when the risk premium rises and selling when the risk premium declines. In the long term, you should make money doing this.

Since the 1st of January 2005, this has happened 32 times in SPY. There are 25 winners. The total gain is 13.54%. Not the best strategy around, but quite good, IMO.

I also picked some other ETFs randomly:

Ticker #Fills #Wins Total in %
VEU 28 23 19.04
GDX 43 34 35.07
FXI 31 18 9.66
EWA 35 32 36.66
EEM 36 28 30.99

Pretty good results, if you ask me!

Here is the chart of SPY and the equity chart above:

 

 

 

 

 

 

 

 

 

 

As you can see, the 4 down days in a row strategy works reasonably well.


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  • Could this method be something what I call pulback? When there is 3 dark candles in a row, and there is a white candle on the fourth day, there is a buy signal.

    Target is the last top, and the stop is lower then the low of the white candle.

    In a book written by Tony OZ it says this was his favorite signal.

    • No, I have tested what you describe and as far as I can see it does not work. The most important thing with this strategy is to buy on a down day and sell on an up day. You can perhaps call it a pullback, but that is a definition that varies. Actually, this strategy worked best in 2008 and 2011, two years which experienced large legs down.

  • Interesting, but maybe it is too few observations to get good statistics? Could you do the same for the last 20 years, please? Even better: statistics hour-by-hour, and not day-by-day.

    • Perhaps to few, but enough to make me trade it. The reason I trust it is because it goes against the “crowd”. I like to buy on down days and sell on up days. Why? On down days the risk increases. In the long run one has to get paid for taking risk. On short term strategies I have yet to find something as good as this strategy when buying on up days.

      This strategy does not work daytradinh. However, perhaps other parameter is good. Feedback appreciated 🙂

    • It’s absolutely an interesting thought with the strategy 4+1, somehow it seems very sensible, and yet very simple.

      I think that a 20-year perspective is very well suited when it comes to significance level at investmentcompanies performance. To be able to claim that you can beat the market you need quite a lot of data-material to back it up.

      But when it comes to a strategy like this one, that most likely will change with the cycles, and as for all “arbitrage’ish” methods it will dry up as more and more traders join the club. I’m not sure if significance levels over many years will give the necessary information when trading it right now, in todays market. But that’s just my thougt about it.

      And another interesting point regarding statistical data is the fact that the measuring of probability for occurences in such a wide time horizont could be very vounerable for your stake.

      Like what happend in Japan 2011 in the stockmarket. A drop in the index at 10.55% on one singel day would statistically happen once every 12-16.000 years…. And sadly it happend in 2011.

      Anyway, I like the idea of this strategy, it got the simplicity, and still makes good sense.

      • Actually, the best period was in the fall of 2008. The start of bear markets is historically bad for this strategy, but later in the “bear market cycle” there usually are some huge winners.

  • Hi. I have utilised this strategy for a while and find that it works best if you have a scaled in entry. So if you have 7 consecutive down days, then after the 4th down day, you enter long 1 position, after the 5th down day another 2 positions etc and close them all out on the first long day.

    Have you tried different ways to refine/improve the strategy? Also do you know why it doesn’t work on FX very well? Is it the 24hour nature of FX? So as an alternative, have you tried it by narrowing the FX window to say start time 9.30am and close 4pm ….ie adjusting the day open/close times…or anything like this?

    Regards

    • Hi, I guess this works fine if you scale in slicing your original postion into smaller positions? Let’s say you have 100 units to trade. You divide this into 5 different strategies, ie 20 units for each strategy. If you get a signal to buy after 4 consecutive down days, you buy for example 5 units. If it continue falling, you buy 5 more etc. Is this what you mean?

      No, I have not tried to improve the strategy. Currently I’m in the process of finding about 10 different strategies on SPY/SP. I will start trading ES in september.

      The reason it does not work in FX is that they trend more. SP is very mean reversion. I’m looking at some numbers there right now and will write something about in the near future.

  • Hi. Its actually both scale in and increase in position sizing. So you scale in say 4 times but the 20 units you have would perhaps be 2 units first trade, 4units second trade etc

    If you want, I can send you a tradesation strategy report with and without ? ie flat stake versus scale in versus just one entry only etc?

    • Hi, thanks for your input. Yes, if you send me the report with the trades that would be nice! My e-mail is oddmund at quantifiedstrategies dot com.

      But aren’t you afraid to be involved in a trade that continues for example 10 days lower in a row. It’s low probability, but I always see the black swan in the back of my head.

      One more thing: do you trade other strategies as well? The “problem” is that most mean reversion strategies have a great deal of overlap. So if one gived a signal, another also at the same time. I have a lot of potential strategies but I want to focus on just a few and find other instruments to trade that correllates less/little with SPY/ES.