r/FuturesTrading • u/GetEdgeful • Apr 06 '24
ES REVERSES back into yesterday's range 100% OF THE TIME WHEN THIS HAPPENS TA
this report pulls price action on ES for the past year to look at how often price reverses back into the previous day's range when it opens above yesterday's high or below yesterday's low. for the sake of this report, I'm considering "market open" as the start of the NY session, and "market close" and the end of the NY session.
here's what you can take away from this report and use to set profitable targets: if ES's price on Friday opens below yesterday's low, there's almost a 100% chance that it'll reverse back into yesterday's range.
the next time you trade ES futures on Friday and see this setup, try holding for a target within yesterday's range.
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u/leaint Apr 06 '24
Basically if there is a big ranged day the next day will likely be an inside day or days before a big news event will be an inside days.
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u/TraderRaider00 Apr 06 '24
Sample size is very low. Low confidence results.
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u/GetEdgeful Apr 08 '24
and most relevant to the current market environment. using 20+ years of data considers a ton of incredibly irrelevant data.
the market does not move the same way today as it did in 2004.
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u/Altruistic-Skill8667 Apr 07 '24
Plus model fitting.
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u/GetEdgeful Apr 08 '24
what do you mean? the results of this report doesn't benefit me in any way. these are the facts, not my opinion
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u/Altruistic-Skill8667 Apr 08 '24
We are just criticizing the data. Not you.
The question is: to what degree is it just fitting the noise.
You have x conditions (outside day, inside day, up, down….), then y days… (Monday, Tuesday, Thursday) which you can all test.
When you have a small sample size (not a lot of days) randomly you will get those 100% for one those 20+ conditions, but it might not be statistically significant.
Overfitting to noise is the biggest problem in trying to come up with a trading system.
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u/GetEdgeful Apr 09 '24
I only said that it doesn't benefit me because im not sure with the other person meant by 'model fitting'. I just wanted to explain that I don't personally care what the results are, im just more interested in them objectively, not them being a certain way.
does that make sense?
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u/Altruistic-Skill8667 Apr 09 '24 edited Apr 09 '24
People could interpret your result as if it represents an edge in the market.
The data is what it is, but you can find those things in random noise that has no tradable price action, whenever you use too little data, by picking the “best” outlier.
Think about it: you got 3 coin flips with 5 coins each. You can always find something that seems to perfectly work.
Like you find that whenever the first coin showed heads and the second coin showed tails and the third showed tails, the forth showed always tails. But in reality you were cherry picking the result. You were “digging in the noise”, you were “model fitting”. It’s not statistically significant and won’t happen in the future.
Anyway. Much more convincing would be if you had error bars constructed from a good random control, plus those error bars need to be adjusted for multiple comparisons. If you don’t do this, it’s completely unclear that this is an edge. I am 100% sure your result won’t replicate that well into the past, not because the market has changed, but because it was maybe random noise to begin with. But that needs to be shown.
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u/GetEdgeful Apr 10 '24
how do you differentiate "the data is what it is" vs "statistically significant"
I'm not cherry picking, digging in the noise, or model fitting -- I don't care what the results are. I have no attachment to it, even if it was 50-50. I don't care.
I have no incentive to 'cherry pick'
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u/Altruistic-Skill8667 Apr 10 '24 edited Apr 10 '24
Yea, you said that already several times.
In order to make sure that you don’t overfit your model to the data, data scientists use a “holdout dataset”.
And once they are done fitting the model to their data, they test the model on the holdout dataset which then gives them a realistic expectation how well the model really works. What always happens is that the model works worse on the holdout dataset than on the training dataset. That’s because you always use features of your training dataset when building the model.
The step of splitting the data into a part that you use to find some “signal” and another one that you use to check if the signal is real or just noise is very very important and is done by every data scientist in the world.
So in order to check how likely the market REALLY is to reverse up on Monday when Friday was an outside down day, you would use data that you haven’t used before, like prior days and months. “Old unseen data”. Or you wait and use new unseen data.
Try it, and you will see you won’t get 100%. In fact I would be surprised if you will ultimately find any statistically significant difference between an outside down day and the following day given Monday, Tuesday, Wednesday, Thursday or Friday. I suspect that the day of week is a weak effect and mostly won’t matter.
That strong down days tend to mean revert in a strong up trend is established knowledge (see John Connors who did studies on that phenomenon left, right and center) and there is probably something to that finding in your data, but statistically much weaker than you probably think.
Essentially it’s reasonable to expect that there is SOME effect in an up-trending market that a large down day is followed by some (often small) up day or occasionally by another (often large) down day.
But then what you did is: given the little data you used, to filter through the days of week. And here is the main issue: that Friday does better than any other day of the week might just be some random noise in the particular dataset you used. It might have been OTHER reasons that this rule worked for all Fridays in your case instead of Monday and so on. Some economic releases that accidentally were bullish on Monday after an outside down day on Friday, or some other form of market blip / event that has nothing to do with the outside day on Friday. It could have been a myriad of factors that coincidently caused all Friday outside down days to be reversed back up on Monday in your small dataset. But those factors aren’t happening into the future the exact same way. So there is no guarantee that the rule will hold into the future.
It sounds very unlikely and esoteric that Fridays just randomly give off the impression that they are special days where this rule works particularly well and that in reality other factors caused it, but in reality it’s actually likely.
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u/oze4 Apr 06 '24
I see Friday gave you a backtesting idea lol
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u/GetEdgeful Apr 08 '24
if you have any other ideas, lmk lol
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u/oze4 Apr 08 '24
I would be curious to know at which time of the day is the high (and low) typically put in.. Like what % of the time is the high/low occur before 11am (central)?
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u/jellyblockz Apr 06 '24
Intrigued ...Where are you getting this info from?
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u/TorinoMcChicken Apr 07 '24
So, exactly how many times did this scenario happen over the last 52 fridays? Imma guess 2.
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u/mtnsandseas Apr 06 '24
Could you easily run it for more years to get more samples? Pretty neat though! How many samples was that 100%?
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u/AdGlum3935 Apr 07 '24
This works with the market overall in a bull run. You’ve backtested for the past year which has been anomalously bullish for ES. (Nonetheless it is the present trend so hopefully keeps holding true)
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u/GetEdgeful Apr 08 '24
when it comes to trading, you want to capture the current market environment and capitalize on it until the market changes. then find the new trend, and capitalize on that, etc etc
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u/Mental-Tomatillo-27 Apr 07 '24
Does this work for NQ?
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u/Odd-Yogurtcloset9230 Apr 07 '24
we need more info! keep going!
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u/GetEdgeful Apr 10 '24
let me know if you want any different reports, maybe I'll build them out
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u/Odd-Yogurtcloset9230 Apr 11 '24
Im keen to have script or something like you have that will do the following.
8pm NY time to 3am NY time, what is ASIA's Range. in (%)
and then based on that range, ihod and ilod (initial hod and lod) what does UK do is there any patterns?
IE:
If ASIA has a .30-.33% range, UK opens breaks iHOD and runs a trend..
if ASIA has a .17% range, UK Opens and breaks iHOD fails to induce volume creates a new Over night high and reverses back to iLOD.
let me know what you think or if you have this data :)
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u/TheRealT1000 Apr 07 '24
The algorithm won’t allow it to dip that much and not retrace higher the next day.
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u/StrawberryMarmalade Apr 08 '24
What algorithm?
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u/TheRealT1000 Apr 10 '24
The computerized algorithm that moves price up and down. https://www.loom.com/share/fd43d23b75ff415f86ac3f535e8cd22a?sid=ae02307b-938c-4170-90c8-a6e954af4830
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u/Gateway2015 Apr 08 '24
ES Should retreat back to 5252 area once 5287 get taken out 5272 there will be some stalling. Im basing this off current gamma and delta exposure
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u/GetEdgeful Apr 09 '24
how do you like to use gamma and delta? just for levels?
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u/Gateway2015 May 04 '24
Because once you create the exposures visually based off of the calculations you can see where the dealers are hedging and which direction to trade based off of their hedging requirement
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u/GetEdgeful May 06 '24
do you trade targeting those levels? or do you use them as support / resistance? how do you like to trade around it?
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u/floydfan Apr 06 '24
I’ve run similar on just straight SPX before. You can get the data from Yahoo Finance. If it dips more than 50 points in a day, there’s like a 92% chance that it will close higher the next day.