New Forum

Visit the new forum at

Sunday, June 15, 2014

Average Return by Trading Day of Month

Often people will say that the first of the month tends to be positive. By the above analysis (SPY from 07/01/2000 to 06/13/2014), that has--on average--been the case. You could also say go long for the 9th trading day of the month and short for the 14th. And if there are 23 trading days in the month, go long the close of the day before--well, if it happens to be in August.

Good luck and good trading. Please do not use the above for trading. Prepare your own analyses (the above could be flawed) and do in-depth investigations. I am not giving financial advice. I'm merely playing with numbers.


  1. Thanks for sharing. Question for you:

    How would you use above data for future months with a different number of trading days than shown in your matrix above?

    For instance in 2015, Jan has 20 trading days, and March has 22 trading days.

    For Jan 2015, would you only use Column 1 values in cells 1 through 20?

    Or will the matrix values change for the (2015) months ahead?

    Thanks in advance for the consideration of a reply.

    Regards, Jim P.

  2. Hey Jim,

    Thank you for the question. That's exactly the kind of question that should be asked; and I'm sure there are more than a handful of ways to answer it.

    One way to answer your question (probably what I would initially test) would be to normalize every month to 20 days of data. I'd recalculate the returns based on this.

    e.g. if a month had 22 days, you'd want to normalize by using results from the first day, then 1/10 of the second day (i.e. 22/20 = 1.1). Then you'd want to take the remaining .9 days of the second day and add it to .2 of the third day and so on and so forth (i.e. normalized day 1 = ((day1%)*1 + .1*(day2%)); normalized day 2 = ((day2%)*.9 + .2*(day3%)); normalized day 3 = ((day3%)*.8 + .3*(day3%); ... ; ... ; normalized day 20 = ((day21%)*.1 + 1*(day22%)))

    Kinda complicated looking...but basically you're just divisioning the days into standardized "days". Not sure what the outcome would be, but I would surmise as good or better than the above graph.

    You could also test out your own suggestion.

    Also, as a recommendation, I would say you should probably take into consideration holidays, major economic releases, and other similar information when trying to utilize something like the above.

    Hope you find something interesting :) Let me know how it goes!

  3. Normalizing each month to 20 trading days makes sense, and is an idea I had not thought of. Thanks also for the formula details, very helpful. Looking forward to future blog posts. Thank you sincerely for sharing your work. Regards, Jim P.

  4. Thank you, Jim. It's comments like yours that make having a site like this worth it :)