07-26, 10:00–10:30 (US/Eastern), Online talks and posters
Removing sources of large errors in financial data leads to an analytical solution for portfolio optimization that is more stable and performant than several tested alternatives
We are going to minimize portfolio risk after applying the following 3 simplifications:
• consider only 2nd moments (simplification 1)
• homogenize variances (simplification 2)
• algebraically reduce dimension (simplification 3)
We assume that we have chosen a list of 𝑛 assets that we want to invest into. Us
choosing these assets implies that we believe that each of these assets has a long
term positive return.
The above simplifications allow us to analytically derive a formula for the weights of each asset.
cyborg, technologist, mathematician, philosopher, artist
lover of julia since v0.3
been coding and doing math 30+ years
more at https://1m1.io