Ah, I see what you’re saying now. Thanks so much for your help. It’s working fine now. - Yuval
I’ve been on vacation for a while.
Anyway, thanks for bringing this article to our attention. It just makes sense of so many things and mega-trends we are seeing regarding active and passive management.
FYI, link to article: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2900447
Another read that I found interesting;
“Why Indexing Works (J. B. Heaton, N. G. Polson, J. H. Witte)” https://arxiv.org/abs/1510.03550
Walter
This is a old chat, but there is a followup on his study from a global perspective here; https://wpcarey.asu.edu/department-finance/faculty-research/do-stocks-outperform-treasury-bills
" This study assesses compound returns to over 64,000 global common stocks from 1991 to 2020, showing that the majority, 55.2% of U.S. stocks and 57.4% of non-U.S. stocks, underperform one-month U.S. Treasury bills over the full sample. Further, the top-performing 2.4% of firms account for all of the $US 75.7 trillion in net global stock market wealth creation during the thirty-year period."
And this https://wpcarey.asu.edu/sites/default/files/2021-10/do-stocks-outperform-treasury-bills.pdf
the majority, 55.2% of U.S. stocks and 57.4% of non-U.S. stocks, underperform one-month U.S. Treasury bills over the full sample.
Why is this a problem? The upside is far greater than the downside, so the winners can more than make up for the underperformers.
I had a system that made 45% a year, but only about half the stocks were winners.
This is an interesting idea. I have been investigating Bayesian optimization and currently am mostly using alpha on the top 1% or so as my optimization target. One of the reasons I have used this vs something like spearman’s rank correlation is that generally speaking I don’t care about what the lower ranks are doing.
However, I think removing the losers could increase the robustness of the ranking system. So maybe we can look at the top 5% and the bottom 5% or top 5% and bottom 25%. At the very least it should help reduce over fitting as it should be a more generalized target.
My research list is getting very long, but something interesting to think about!
Can you share how to set up this strategy?
Thanks in advance!
If you take this approach, you have to be careful with size factors. The worst stocks and the best stocks will both rank very high on augmentative factors so a ranking system optimized for both the worst and the best will give a much lower weight to such factors than one optimized for only one or the other.
Yes, I agree, but does the study also give an indication that there are good arguments to have a (1) larger portfolio in terms of the number of stocks and (2) ensure diverification and (3) that these arguments about “buying and holding for life” are not very good:
