Weighted Average Calculation
Hi,
I'm working with a dataset and am wanting to make sure I am going to get a weighted average of our mortgage rates.
We have loans that range from 100k400k and each loan has an associated mortgage rate. As an example, we have two loans that go into the same security that are 5% and 5.5%
Loan A is worth 200k and loan B is worth 100k. I need to make sure when I am grouping them into their pools, I am not getting an average of the mortgage rate (5.25%) and am instead getting a weighted average (5.165%)
Any suggestions?
I am working with a MagicETL as well.
Loan A 200k 5% poolC
Loan B 100k 5.5% poolC
If this helps, feel free to agree, accept or awesome it!
Best Answer

For this you'll need to get the Value of the rate rather than the %, and then calculate the new percentage as the ratio between the two.
At the row level you'll need to have a value that is the Worth of the Loan times the Mortgage Rate of it. In your example for Loan A = 10K and for Loan B = 5.5K. Instead of averaging the % (which is almost never a good idea) you'll work with these values. (10 + 5.5)/(200 + 100) = 5.167% which is what you want. In a single beast mode this can be written as:
SUM(`Worth` * `Mortgage Rate`)/SUM(`Worth`)
Which will work on the aggregation level used for your data.
1
Answers

For this you'll need to get the Value of the rate rather than the %, and then calculate the new percentage as the ratio between the two.
At the row level you'll need to have a value that is the Worth of the Loan times the Mortgage Rate of it. In your example for Loan A = 10K and for Loan B = 5.5K. Instead of averaging the % (which is almost never a good idea) you'll work with these values. (10 + 5.5)/(200 + 100) = 5.167% which is what you want. In a single beast mode this can be written as:
SUM(`Worth` * `Mortgage Rate`)/SUM(`Worth`)
Which will work on the aggregation level used for your data.
1 
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