You are just wrong. Being unable to overcome bureaucracy or organizational tech debt is not a matter of stupidity, and various actors up and down the hierarchy can have misaligned incentives that ensure it remains contentious and political.
Furthermore, many boutique investment business exist for purposes of client services and plausible deniability on part of the client’s board.
I’ll give you a concrete example from when I worked in an asset management company. One client was a large pension fund for a state’s retired firefighters.
We showed them time and again a variety of enhancements to the basic portfolio construction product they bought from us, particularly in line with their overall goal of balancing investment in certain sectors across different asset managers to reduce risk.
They were not interested, not even on the basis of paying reduced fees for a simpler process. We also talked to them at length about why using a concentrated benchmark for that product (SP500) was a bad idea. Again, not interested.
After some months where our performance was pretty flat in that portfolio against SP500, pretty much as we told them we predicted it would be, they fired us.
In the client exit interview with two members of their board, they basically told us that each year they have to fire a certain number of the asset managers they do business with, in order to appear proactive and justify getting bonuses for taking action.
They obviously didn’t say this directly, but it was clear enough. They ended the call by saying they would be super excited to review re-investing with us later the next year, presumably at which time they have to do musical chairs with which asset managers they hired & fired to look proactive again.
Internally, some of my older mentors on the portfolio management team badically said this was the business. Nobody cares what math you use for investing at all. Everybody just uses super stupid linear regression based on outdated factor models from 40 years ago, all using the same data from the same big data vendors.
As long as you have hilariously over-credentialed PhDs selling linear regressions based on momentum or price-to-earnings, the clients are happy because you are cover-their-ass hire & fire insurance to them, nothing more.
It would not be hard at all for skilled amateurs to outperform these shops.
Furthermore, many boutique investment business exist for purposes of client services and plausible deniability on part of the client’s board.
I’ll give you a concrete example from when I worked in an asset management company. One client was a large pension fund for a state’s retired firefighters.
We showed them time and again a variety of enhancements to the basic portfolio construction product they bought from us, particularly in line with their overall goal of balancing investment in certain sectors across different asset managers to reduce risk.
They were not interested, not even on the basis of paying reduced fees for a simpler process. We also talked to them at length about why using a concentrated benchmark for that product (SP500) was a bad idea. Again, not interested.
After some months where our performance was pretty flat in that portfolio against SP500, pretty much as we told them we predicted it would be, they fired us.
In the client exit interview with two members of their board, they basically told us that each year they have to fire a certain number of the asset managers they do business with, in order to appear proactive and justify getting bonuses for taking action.
They obviously didn’t say this directly, but it was clear enough. They ended the call by saying they would be super excited to review re-investing with us later the next year, presumably at which time they have to do musical chairs with which asset managers they hired & fired to look proactive again.
Internally, some of my older mentors on the portfolio management team badically said this was the business. Nobody cares what math you use for investing at all. Everybody just uses super stupid linear regression based on outdated factor models from 40 years ago, all using the same data from the same big data vendors.
As long as you have hilariously over-credentialed PhDs selling linear regressions based on momentum or price-to-earnings, the clients are happy because you are cover-their-ass hire & fire insurance to them, nothing more.
It would not be hard at all for skilled amateurs to outperform these shops.