Do Some Sector Math

Both Barron's and the WSJ wrote about private equity/credit funds over the weekend. Barron's picked the idea floating around that somehow, investors who put money in to private assets didn't realize the difficulty they would have getting money out and offered a few ideas to help. 

Apparently if someone has to take required minimum distributions then the fund companies need to honor those redemption requests. Also there are secondary markets where someone might be able to sell but do so at a discount. It's not so much markets to do this as companies that can facilitate this sort of trade. 

The WSJ reported that private equity is a the larger asset class but that most of the trouble is in private credit. I asked Copilot to weigh in.

First I asked it to quantify the risks. How many funds might go under.

Category	Realistic Failure Estimate	Notes
Private Equity (company‑level)	20–30% fail to meet expectations	Well‑documented; bankruptcy spikes in 2024.
Private Equity (fund‑level)	5–10% may return <1.0x	Depends heavily on vintage and leverage.
Private Credit (loan‑level)	10–20% impairment in downturn	IMF/OFR highlight fragility and opacity.
Private Credit (fund‑level)	0–5% severe distress	True failures rare so far; untested at scale.
Gated vehicles (interval, evergreen)	5–15% material stress; 1–3% structural failure	Liquidity mismatch is the key risk.

Then I asked about systemic risk.

There is no systemic crisis coming from private markets in the classic sense. But there will be real pain, especially in semi‑liquid vehicles and highly levered sponsor‑owned companies. The risks are not existential — they are structural, slow‑moving, and unevenly distributed.

I don't know a whole lot here but have studied it some. I don't know a whole lot because I don't need to. This space was so clearly and obviously headache and hassle at a minimum or maybe "severe distress" waiting to happen that it was easy to avoid. If you think there is a way to replicate private assets via a wrapper with daily liquidity and want that exposure, go for it. If it goes poorly but you sized it correctly, ok, you can get out. 

These things usually need to be accessed via an advisor of some sort so I am trying to wrap my head around an advisor letting a client get to the point where the fund company must accommodate the redemption request so the client can take their RMD.

The Journal also had an article about emerging market ETF picks from various types of participants. The group seemed to favor South Korea and Taiwan ETFs. I have no opinion either way on adding those two countries but make sure you do some sector math so you don't get caught off guard. iShares Taiwan (EWT) has 39% in technology and iShares South Korea (EWY) has 47%. The S&P 500 has 44% in tech plus communications. 

We just wrote about country funds a couple of weeks ago. 

It looks like nothing, but the drawdown in domestic tech represented by XLK was more than 10%. You can see EWY and EWT starting their declines at the same time but with much bigger drops and then the lift from the last few days is also much bigger. 

This isn't automatically a problem if you have done some sector math to know how much tech you are actually carrying and you have the right expectations and understanding about volatility. An extra layer here is that these dynamics change over time. In the 2000's EWY and EWT outperformed XLK by a lot with more volatility as foreign generally did better. Then in the teens, XLK did much better as foreign lagged badly. And the 2020's have been more of a mixed bag.

I am far from a don't use country funds guy but using them effectively is not a set and forget endeavor.

The other day, when we looked at CPZ I said that combining long/short equity with an income overlay might be an interesting combo. Well the Neos Long/Short Equity Income ETF (NLSI) does just that and guess what? It's not interesting. No yet anyway.

Testfol.io doesn't always account for income correctly. So far, NLSI has paid out a little over 200 basis points so even if the chart doesn't account for the distributions correctly (low probability), the result would still be pretty rough.

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