How to calculate Annualized tracking error of an Index fund given daily historical data?

Let’s say I have Fund A (A) and Benchmark (B) and the daily closing value of both, stretching back 5 years.

To find the Annualized Tracking Error (ATE), would this method be correct:

1. Compute percentage change of A’s daily value relative to its previous day’s value
2. Compute same for B
3. Compute the difference between 1 and 2
4. Do this for all 5 years worth of daily data. Step 3 will look like a column with ~1250 rows of data
5. Compute the standard deviation of this whole column (stdev.s). Per my understanding this would be the Tracking error for the entire 5 years. Let’s call it K
6. To find the Annualized tracking error, annualize the above i.e. Annualized TE= (1+k)^(1/5) – 1

Questions:

• My confusion is in the annualizing step. Instead of my formula in step 6, should I be using k * sqrt(250)?
• Let’s say the result is 0.000142. Does this mean TE is 0.01%?
• Would I be right in assuming that calculating all this with daily data would yield a far more accurate TE than with monthly data?