Buying near June lows has historically yielded incredible results in July

There is a popular belief in markets - " Sell in May and go away" - It seems like there are some more like this and I realised a new one today when I was discussing this with my friends. So, thought to share this cool data with you all.

Year June Lows July Highs % return
2006 2595.65 3208.85 23.62%
2007 4100.80 4647.95 13.34%
2008 3790.2 4649.85 22.63%
2009 4143.25 4669.75 12.07%
2010 4961.05 5477.5 10.41%
2011 5195.9 5740.40 10.47%
2012 4770.35 5348.55 12.12%
2013 5566.25 6093.35 9.47%
2014 7239.50 7840.95 8.3%
2015 7940.1 8654.75 8.99%
2016 7927.05 8674 9.42%
2017 9450 10115 7.04%
2018 10550 11335 7%
2019 11625 11946.75 2.76%
2020 9544 11300 18.39%
2021 15450 15924 3.06%

If we look at the historical data of june and july from last 16 years, We can find some interesting observations :

Some Findings

  • Average return from June lows to July highs is 11.19%

  • In last 16 years, 8 years (50% have given double digit returns)

  • 6 years (37.5% ) have given returns ranging from 7 to 9%, So, we have almost got close to 7-20% in 8.7 times out of 10 in last 16 years.

  • Only 2 years, the difference btwn highs and lows is 3% or below but those 2 years have come in the last 3 years.

Disclaimer and some other points :

  • This data may not mean much as there is no guarantee that past returns can be replicated. I have only checked june to july data. It needs to be seen what returns we have got if we compare 2 monthly returns for rest of the months (maybe we can do that in this thread for reference in the future)

  • Needless to say, It is not recommendation to buy.


Maybe i misunderstood, but this seems to be forward looking test. No one will tell you what is June low and what is July high. You could do that for any two consecutive months and probably you will see better than avg returns.

Now if this was buy June1 / June 30, Sell July X then maybe you can have something ( even that i doubt as seasonality has very low sample size).

What this does give you is range of the two months, so maybe you can do that for multiple pairs and see what is likely to be more volatile or less volatile. So maybe mid year is less volatile so range is lower. I have heard that march can be trending due to eoy flows, same with dec, so maybe those periods are more volatile.

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This needs to be done. Will try to do it and share it in this thread. will be interesting to see how the bi-monthly returns are for rest of the year.

Yeah…You are correct. :slight_smile: This data would make better sense at the end of june. :

At the end of the day, TA or even data analysis is a matter of probability. The whole task is to place ourselves in high probability low risk high reward setups.

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Yes but this is a mistake - TA or data analysis. This is not predictable as we are choosing lows and highs in hindsight. There is 0 predictive value from results derived by looking at the future. This kind of mistake happens to all and sometimes it can be devious. There might be other inferences possible looking at the range, but not in terms of returns as we cannot execute without a time machine.

Ways to mitigate

  1. While these results are ok, sometimes you might get something that seems too good to be true. In that case - it probably is, so must have some doubt and take extra effort in verifying. Has happened to me a few times.
  2. There is no edge in randomness. One nice way of testing for future data poisoning results is to run same test over randomized market data ( Just reorder % changes from actual market data). If your theory has an edge in random data - then you have likely made a mistake.
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I would say now that you have posted it, buy in june itself.


The intention is to keep an eye on june lows and see how the trade pans out from those levels. Buy nearing lows and selling near highs is something only Gods and twitter traders can do :slight_smile:

Rest of your points are absolutely spot on and are useful for anybody who wants to do some data crunching…

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Lowest of one month and highest of next month. What genius! Definitely useful for time travelers :stuck_out_tongue_winking_eye: Idea should go into the next edition of “Backtesting for Time Travellers” :sweat_smile:

Arre sir. Just testing waters with this type of data. It is just to get a broad picture as to how much our markets have bounced from lows in june in general historically.

Please understand the intention is not to buy low and sell at the top doing this analysis…I just wanted to check how the returns from a month’s low to next month’s highs are …I will check the data for rest of the year and share the findings here. :sweat_smile:

Understood @Prakashsingh

That would be interesting :wink:

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If you take any two consecutive months, you would get positive returns.

Only exception would be if the first day of the month opens gap down and that gap doesnt get filled for the rest of the month.


Seems some typo here, months should be read as decade

What am I missing here? Sorry. I didn’t get you.

Any 2 months will give the same result :slightly_smiling_face:

Nifty up from 15191 to 16550++ in July (9%++ returns)

As you all rightly mentioned, if we look at lows of previous months and compare with highs of next months, the returns are mostly going to look good)

I didnt yet check the average returns data for rest of the months…but july being a bullish month in general historically…I tried this unusual experiment.

This is at best a type of hindsight analysis

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If possible, post the data for other months too