Hello People at Stackexchange :)
First of all: Thank you so much for taking the time to answer my question!
I need to calculate weights of a time series which I planned to do by calculating the average or the arithmetic mean and weighting each return proportionally. As my time series contains negative numbers, however, the "typical" formula is not appropriate:
Typical Formula
My problem:
I want to overweight stocks with higher return and underweight stocks with lower return.
Stock 1: 5%
Stock 2: 3%
Stock 3: 1%
Sum: 9%
The weights would then be:
Stock 1: 5 / 9
Stock 2: 3 / 9
Stock 3: 1 / 9
In my data, however, I have negative values:
Stock 1: 0,1 %
Stock 2: -2,5 %
Stock 3: -0,3
Stock 4: 0,4
Applying the same strategy would result in non-sense results.
The highest returns have a negative weight, while negative returns have a postive weight:
Stock 1: 0,1 / -2,3
Stock 2: -2,5 / -2,3
Stock 3: -0,3 / -2,3
Stock 4: 0,4 / -2,3
Some other posts suggested the Root Mean Squared but in my case it did not result in any logical solution. The lowest (negative) returns still have the highest weights and vice versa: Root mean squared
Thank you so much for any help on how to calculate the weighting including negative values!
It is highly appreciated!
Best regards, Anni