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I have daily price data of hundreds of companies from 2010-01-01 to 2020-08-21, there are many missing values in my data frame. if I use na.omit, it deletes all my data. I try to use ROC(), but it does not work due to NA values.

How can I exclude N/A and calculate daily log returns?

Thank you guy, I know you are genius

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    $\begingroup$ which program language are you asking for $\endgroup$
    – develarist
    Commented Aug 23, 2020 at 18:38
  • $\begingroup$ Hi, I am using R to get the returns. $\endgroup$
    – Lee Site
    Commented Aug 25, 2020 at 3:43

1 Answer 1

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There are multiple solutions possible, depending on the situation.

What CRSP does is something like this:

If the price is "missing" on day t, you compute the return for day t as also "missing"

else if the price on day t exists, compute the return for today as the return from the most recent available price (which may not be $P_{t-1}$ if $P_{t-1}$ is missing) to the current i.e day t price. Store this value in a dataframe. Optionally you can also store a "return_days" counter which tracks the number of days for the return (1 when there is no missing data, in general $N$ where the return you computed is $\log(P_t/P_{t-N})$ because you skipped over $N-1$ missing days).

Like all programming techniques this solution of course has advantages and disadvantages.

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