Searching on the internet you can find a lot of articles on how to play the opening gap of the S&P 500. Gap trading strategies are popular.
What is an opening gap? (Gap Fill)
A gap is when the opening price (or print) is higher or lower than the previous close. A gap up indicates the opening is higher than the previous close and vice versa.
Other traders might define gaps more stringent: a gap up is when the opening is higher than yesterday’s high, and a gap down when the opening is lower than yesterday’s low.
Types of gaps and gap fill
There are many types of gaps, however, the three most common are runaway gaps (breakaway gaps), exhaustion gaps, and common gaps.
Common gaps
As the name implies, these are gaps that are “common” and frequent. For example, the S&P 500 opens up or down more or less every day. Most of the days this is just noise and hardly worth to write about (in the news). Typically, the gaps are in the range of plus/minus 0.25%.
Runaway gaps
This gap is often called breakaway gaps. This gap usually leads to higher or lower prices in the same direction of the gap. If it gaps up, we can expect higher prices in the future.
However, it’s easy to explain with hindsight.
Exhaustion gaps
Exhaustion gaps happen after an already extended move in one direction.
For example, if the S&P has had a sudden move over several days upwards, we have a potential exhaustion gap if it one day gaps up more than normal (average).
An exhaustion gap signals the end of the move: it’s the climax.
Do gaps get filled?
It depends on the size of the gap and time. Most small gaps are filled the very same day, while bigger gaps need more time (days) to get filled. You can read more about gaps in this article. We have previously also written about unfilled gap.
Some gaps need many many days to fill, some even months, and some never (applies more to single stocks – not indices).
Can you predict a gap opening?
The activity in the market before the official opening is easy to spot. All liquid ETFs and futures contracts indicate where it’s gonna open, of course, it might vary from minute to minute.
You can also use statistics to indicate the probability of a gap up or down opening the next day based on statistics.
Opening gap strategy in the S&P 500 (SPY Gap Fill)
Today I did my personal twist on this strategy. Over the last two months, I’ve been trading a similar strategy, but not exactly the same as the one I’ve tested here.
Here are the details (for long):
- If SPY gaps down lower than -0.15% but higher than -0.6%, go long at the opening print/cross. The reason I use -0.6% as the maximum is that SPY shows a lot less mean reversion if opening lower. To me that makes sense. Usually, there is not that much “news” if SPY opens for example -0.4% down compared to for example 1%. However, if SPY opens more than 1% down it’s a good short, vice versa for long if it opens above 1%.
- Target is 0.75 of the gap. If it opens down -0.5%, the target is 0.375% higher than the fill price. If the target is not reached exit is at the close. No other stops.
- Yesterday’s close must be lower than 0.25 of this formula: (close-low)/(high-low). The reason I use this is because of SPY’s mean-reversion tendencies. It means fewer fills, but a higher average per fill. The tighter I set these criteria, the better average per fill (but obviously less fills).
The test period is from 1. January 2010 until August 2012. In total there are 110 fills and 98 winners. The average per fill is a respectable 0.19%. Here is the equity curve:
Here is the distribution:
Small winners and occasionally a big loser.
The data is adjusted for dividends and collected from Yahoo! and IQFeed. I have tested on both data sets with not much difference. I have used EOD quotes, ie. only open, high, low and close.
I wrote this article on the 20th of September 2012. A perfect day for this strategy. SPY opened down about 0.47% and filled the gap all the way up until yesterday’s close.
The strategy seems very robust and yields very good numbers. Perhaps too good to be true? Yes, it’s probably too good to be true. The reason is that some of the high and low quotes are wrong which boosts the numbers. That’s why I’ll write a second article on this strategy and test it on intraday data from IQFeed. Then we’ll find out if there is a discrepancy in the data sets (which I believe it is).
Any thoughts about this strategy? I know this strategy didn’t perform very well some years ago. However, markets always change and we have to adjust. You won’t find a strategy that lasts year after year.
The opening gap strategy above showed promising returns. However, can we trust the data? The test was performed on EOD data from Yahoo! (open, high, low, and close per day).
Today I have downloaded 30 mins data from IQFeed. The test period is the same: 1. January 2010 until 1st of July 2012. All the other parameters are the same. The result is still quite good:
In total there are 89 fills, 21 less than on the EOD test. The average gain for long is 0.22% and 0.08% for short.
I have no idea why the numbers are so different. This proves that backtesting is just an indication, you need to test live to get a grasp of the strategy.
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I decided to look more into opening gaps in SPY (S&P 500) to look for fade the gap strategies. After all, a lot of traders claim to make good money on this strategy, at least according to my search on the web.
For me, this is unknown territory as up until this date I have only been day trading stocks, and my experience in trading indices is close to zero.
My database in this sample is from January 2005 until October 2012. I’m using EOD data on SPY downloaded from Yahoo! Finance. This means I only check the SPY’s Open, High, Low and Close for the day. There is no intraday data. I suspect the results are a good deal better than to expect in live trading, keep that in mind.
In my first post about opening gaps, I faded (going against the gap) gaps under 0.6%. In my findings below I’m fading every gap between 0.1% to 0.6% (and vice versa). Target is 75% of the gap size from the close.
Day of week
Mondays:
| Total in % | #fills | #wins | Avg |
| 12.05 | 200 | 160 | 0.060 |
Tuesdays:
| Total in % | #fills | #wins | Avg |
| 11.76 | 231 | 182 | 0.051 |
Wednesdays:
| Total in % | #fills | #wins | Avg |
| 22.68 | 239 | 202 | 0.095 |
Thursdays:
| Total in % | #fills | #wins | Avg |
| 18.94 | 213 | 181 | 0.089 |
Fridays:
| Total in % | #fills | #wins | Avg |
| 17.99 | 210 | 172 | 0.086 |
The equity curve looks the best on Fridays, a lot steadier on that day. The later in the week, the better. I don’t know why. But it opens opportunities to trade other twists earlier in the week.
Period of month
Day 1 to (and including) 10:
| Total in % | #fills | #wins | Avg |
| 22.05 | 349 | 277 | 0.063 |
Day 11 to 20:
| Total in % | #fills | #wins | Avg |
| 27.11 | 366 | 303 | 0.074 |
Day 21 to 31:
| Total in % | #fills | #wins | Avg |
| 34.27 | 378 | 317 | 0.091 |
Worth noting is that the 1st day of the month is horrible. The last two days of the month are very good.
Gaps inside yesterday’s bar
When SPY either opens below yesterday’s high or above yesterday’s low:
| Total in % | #fills | #wins | Avg |
| 43.56 | 734 | 610 | 0.059 |
Gaps outside yesterday’s bar
When SPY opens above yesterday’s high or below yesterday’s low:
| Total in % | #fills | #wins | Avg |
| 39.88 | 359 | 287 | 0.111 |
The equity curve looks a lot better for gaps outside yesterday’s bar than those gaps inside. The average is also a lot better.
Gaps outside 3 days range
Gap up must open higher than the high of the previous 3 days and vice versa for longs.
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 24.14 | 197 | 158 | 0.123 | 6.65 | 17.50 | 56 | 141 |
This equity curve looks really nice! These days we can even trade gaps up until 0.75% with very good results.
Yesterday unfilled gap down
If yesterday gapped down (when high of yesterday is lower than low two days ago):
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 5.21 | 33 | 30 | 0.158 | 3.21 | 2.00 | 12 | 21 |
Very good results, but not surprisingly it’s long which is best. All longs hit the target. A good example of reverting to the mean.
Yesterday unfilled gap up
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 8.97 | 66 | 58 | 0.136 | 6.48 | 2.49 | 34 | 32 |
If it’s a gap up the day before, both directions are good. In general, if unfilled gap yesterday, the better chances to fade the gap.
Gaps after a high range day
What happens if yesterday had a higher range (HIGH-LOW) than the 15 days average?
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 34.30 | 439 | 363 | 0.078 | 19.57 | 14.73 | 168 | 271 |
Gaps after a low range day
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 48.86 | 640 | 527 | 0.076 | 18.52 | 30.34 | 297 | 343 |
Gaps when yesterdays close was above 10 day moving average
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 56.94 | 682 | 561 | 0.083 | 23.85 | 33.09 | 326 | 356 |
Gaps when yesterdays close was lower than 10 day moving average
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 26.32 | 404 | 332 | 0.065 | 14.24 | 12.08 | 141 | 263 |
Gaps when yesterdays close was at least 2% above 10 day moving average
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 11.23 | 94 | 84 | 0.120 | 6.87 | 4.36 | 59 | 35 |
Gaps when yesterdays close was at least 2% below 10 day moving average
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 15.89 | 86 | 82 | 0.185 | 9.14 | 6.75 | 34 | 52 |
Gaps when the close is above 0.5 in yesterday’s range
Here I’m using the formula (CLOSE-LOW)/(HIGH-LOW) to decide yesterday’s range:
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 34.98 | 612 | 485 | 0.057 | 12.90 | 22.08 | 280 | 332 |
Gaps when the close is below 0.5 in today’s range
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 47.98 | 479 | 410 | 0.100 | 25.06 | 22.92 | 189 | 290 |
Gaps when the close is above 0.75 in yesterday’s range
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 27.67 | 359 | 299 | 0.077 | 11.21 | 16.47 | 167 | 192 |
Gaps when the close is below 0.25 in today’s range
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 32.76 | 264 | 229 | 0.124 | 14.77 | 17.99 | 98 | 166 |
Why is gaps much better when yesterday’s close is lower than 0.25? Both long and short are better with a nice and steady upward sloping equity curve.
Gaps when yesterday’s open is lower than yesterday’s close
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 39.44 | 556 | 451 | 0.071 | 17.55 | 21.89 | 261 | 295 |
Gaps when yesterday’s open is higher than yesterday’s close
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 43.71 | 528 | 439 | 0.083 | 19.57 | 24.14 | 203 | 325 |
Yesterday gapped down and closed below 0.33 on the daily range
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 10.30 | 160 | 134 | 0.064 | 4.39 | 5.91 | 62 | 98 |
Yesterday gapped up and closed above 0.66 on the daily range
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 17.20 | 262 | 217 | 0.066 | 11.01 | 6.19 | 132 | 130 |
Gaps on the day of the monthly jobs report
This is the most important macroeconomic news in the month and might be worth considering. It’s on the first Friday of the month. Friday is the best gap day of the week. Here is the result on those days:
| Total in % | #fills | #wins | Avg | % long | % short | #fills long | #fills short |
| 3.40 | 44 | 36 | 0.077 | 2.20 | 1.20 | 13 | 31 |
The win rate is pretty good, but the average is below other Fridays. So this is perhaps worth mentioning.
Developing a fade the gap strategy is not easy, but hopefully, the numbers provided in this article help you get started. Gap trading strategies have been around for a long time, but the window of opportunity is getting smaller with the increased computer power that arbs away the anomalies.
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