Benchmark agnosticism, the practice of declaring yourself a manager without benchmark, is a trendy subject. Acknowledging that you pay no attention to standard and replicable indices in the market apparently makes you a more desirable (if not better) manager.
The way data are presented should help understanding, not engender serious doubts.
At my request I was recently provided by an advisor with an analysis of two investment alternatives: a fund investing in private markets (that is, in non-public market opportunities, with limited liquidity) which the advisor was proposing to a client and an alternative in the form of a listed ETF.
I had a useful conference call with five other investors on the pros and cons of private equity investments (PE). The following is a list, in no particular order, of what we concluded were important elements to consider [with my personal comments in brackets]. As always, all errors and omissions are mine.
The question is: should you ever have sold out of this investment?
If you knew in 1980 what you know today you should have bought a lot of Apple stock. But there is something fascinating and yet very dangerous in the wonderful sense of security and misguided confidence an ex-post picture can give us.
A couple of months ago this article appeared in The New York Times.
My daily job is to convince people that investing is a little like watching grass grow without fiddling with it. It is not easy; it requires conviction, discipline and an unnatural ability to shut your amygdala e fire up your cortex at the same time.
In the late 1800s, Native Americans told naturalists working in Alaska that the marbled murrelet, a small seabird that flies underwater when fishing, breeds in the ancient forest. Apparently they weren’t listening.
Intelligence is what helped humans thrive over time and through adversity. It’s what distinguishes us from the rest of the living creatures on the planet. But while this may be so in general, I’m not sure it’s true in every field.
A couple of months ago this article appeared in The New York Times.
Exponential versus linear: why bother? See this wonderful BBC article, Exponential growth bias: The numerical error behind Covid-19.