u/ejqt8pom — reddlx

https://youtu.be/Q6J2g4aVETM

Steven Baveria, author of "The Income Factory", pretty much the father of income investing, gives Adam Taggart an interview in which he reveals that ~25% of his personal portfolio is in high quality publicly traded BDCs.

During the interview he gives us some easy math. A 50% discount to NAV means that the market expects 100% of the loans in the fund's book to default (assuming a 50% recovery rate).

A 25% discount is pricing that half the loans default.

Neither option sounds reasonable does it?

He calls out Jamie Dimon for starting this trend with his cockroaches quote.

Overall a great interview, even if they ended up repeating some things that were already covered in previous interviews.

I've been building a dividend intelligence tool for the past few months and ended up with a database of 151,422 ex-date events going back 17 years across 2,344 securities — CEFs, ETFs, REITs, BDCs, and dividend stocks.

Figured I'd share what the data actually shows since most of the discussion around ex-date dips is based on gut feel.

Recovery by security type (average days to full price recovery):

Type	Avg Recovery	Events
Dividend Stocks	6.7 days	57,791
REITs	7.7 days	6,743
ETFs	8.1 days	37,384
CEFs	8.9 days	46,896
BDCs	12.4 days	2,608

Overall median across all 151,422 events: 3 days

The gap between median (3 days) and average (7.9 days) is the most important number — most securities recover fast, but a meaningful minority take much longer and drag the average up.

The BDC finding surprised me most. They have the largest average drop (2.08%) AND the slowest recovery. Only 45% recover within 5 trading days. If you're buying BDC dips expecting a quick bounce, the historical data says be patient.

Stocks recover fastest — 71.5% recover within 5 trading days, 81.8% within 10. Counterintuitive given how many income investors overlook stocks in favor of higher-yielding alternatives.

Individual CEF variance is huge. Among CEFs with 20+ cycles in the dataset:

BMN: 4.4 day avg across 38 cycles
IGI: 4.7 days across 186 cycles
BCX: 5.2 days across 133 cycles
PAI: 5.2 days across 201 cycles

Compare that to CEFs where recovery regularly takes 3+ weeks. Both show up as "CEFs" on any screener. The historical pattern data separates them.

The z-score frame matters more than raw price. A security trading 2.5+ standard deviations below its 252-day mean at ex-date is a fundamentally different situation than a routine dip near the mean. One has statistical room to recover, the other is just drifting lower.

Happy to answer questions about methodology or what the data shows on specific tickers.

Happy to share more of the data if there's interest in specific security types or individual tickers.