Tracking error and information ratio explained (Excel)

[@NEDLeducation]

You can find the spreadsheets for this video and some additional materials here: drive.google.com/drive/folders/1sP40IW0p0w5IETCgo464uhDFfdyR6rh7 Please consider supporting NEDL on Patreon: www.patreon.com/NEDLeducation

[@joeaoun6321]

Another great video. Really appreciate your content and efforts to make the calculations understandable. Also appreciate the context and qualitative considerations that are discussed after doing all the math. Thanks for all you do.

[@Diegoblismartmedpengar]

Great video and very easy explained! Thank you for these videos they are very helpful. I was thinking if it is still possible to attain Jensens alpha or the tracking error by only using annum return for both the mutual fund and the s&p500 or does it have to be monthly data? Thank you for you answer!

[@j.r.w.devisser6030]

Great video, very informative!

[@SachinGKulkarni30]

Where can one get the tracking error information for the last 1 year, 3 years, or 5 years for any index mutual fund?

[@takshilkanekar8006]

thanks such a great explanation!

[@fonzie2668]

Hey, I've done my calculations on 3 funds. The fund with the highest return and alpha has given me the highest tracking error but lowest Information Ratio from the 3 funds. The opposite is true for the fund with the lowest return and alpha. Would you be able to offer an interpretation on this? Thank you!

[@sahiljain5094]

just have one doubt, if the outperformance is more in this case, the tracking error is decreasing and when it is closer to "zero" it is increasing, it should be the opposite right?

[@S4tanMW3]

Great video! If I have monthly returns, I just change the formulas from e.g. SQRT(252) to SQRT(12) right?

[@NEDLeducation]

Hi, and glad you liked the video! Yes, exactly, to annualise monthly standard deviation you can simply multiply by SQRT(12).

[@BOSprodz]

Would a larger lookback period provide a more accurate/useful Information Ratio? Or is it better to have a more "relevant" IR of only a few years back? Thanks

[@paulgiles9637]

you have 1 year's data so not sure why multiplying by SQRT 252 necessary? One multiplies by SQRT(time) if less than 1 year's data. So one month date = *(SQRT) 12

[@NEDLeducation]

Hi Paul, and thanks for the question! I have got five years worth of daily data, so to determine annualised standard deviation, multiplying by SQRT(252) is needed as the original data is daily and we would like to have it on an annual basis.

[@EduLife_Chronicles]

Hi @@NEDLeducation , could you please let me why you took 252 instead 365 or 366?

[@MrFXtrem]

Hi, that's because there are only 252 trading days, or 252 observations per year if you prefer. Week-end does not count. @@EduLife_Chronicles

[@Jughead79]

QQQ = NASDAQ 100 index fund INZ = Stock of Invesco, investment management company (and manager of QQQ) BLK = Stock of Blackrock, investment management company SCHW = Stock of Charles Schwab, brokerage/wealth management/investment management company

[@bustaaal]

from where come 252 ?

[@NEDLeducation]

Hi, and thanks for the question! 252 is a typical number of trading days (when markets are open) in a year.

[@bustaaal]

@@NEDLeducation where can i contact you in private please ?