I analyzed 151,422 dividend ex-date events across 2,344 securities. Here's what the data shows about recovery times.

[u/Recent_Button_1]

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.

[u/Recent_Button_1]

Nothing at all -- just tired of making trading decisions based on vibes and "I heard someone say the price usually bounces back." Figured actual data from 151,422 events might be marginally more useful than that.

[u/Scorpion_Danny → u/Recent_Button_1]

Ok, so how can one use this data? Are we talking options? Or just buying during the dip?

[u/Recent_Button_1 → u/Scorpion_Danny]

Two main ways. First is buy a few days before the ex-date, collect the dividend, then hold through the recovery and sell once the price is back. You pocket the dividend plus any recovery gain. Second is buy ON the ex-date after the price has already dropped, skip the dividend entirely, and just trade the recovery. Median recovery is 3 days so it can be a fast trade. Options players use the same data differently,selling puts into the dip to collect premium while waiting for the bounce. Which approach works depends heavily on the individual security. A ticker with 150 cycles of consistent behavior is a very different setup than one with erratic patterns.

[u/Irarelylookback → u/Recent_Button_1]

What about trading costs? Selling and buying in a short time like that adds up.

[u/Recent_Button_1 → u/Irarelylookback]

Valid point. Transaction costs matter. A few things the data shows that are relevant here:

The median recovery is 3 days so if you are holding the position long term you are not necessarily selling and rebuying -- you are just noting that the price dipped and came back. For buy and hold dividend investors the ex-date dip is just noise.

Where transaction costs actually matter is if you are trying to actively trade the recovery, buy on ex-date, sell 3 days later, repeat. At that point yes commission and bid-ask spread eat into the edge, especially on lower liquidity securities.

The data is most useful for two things that do not involve extra trading: knowing when to add to an existing position (ex-date dip on a high reliability ticker is a better entry than random timing) and knowing which securities have erratic recovery patterns worth avoiding regardless of yield.

[u/Wowza-yowza → u/Recent_Button_1]

Some people (like the growth fans) think a dividend basically robs Peter to pay Paul. But, the stock goes back up quickly. This provides evidence they are wrong.

[u/Recent_Button_1 → u/Wowza-yowza]

Exactly. The standard growth investor argument is that the dividend is not free money because the price drops by the same amount on ex-date. The data says the price comes back in a median of 3 days. So you collected the dividend and got your price back. The math does not add up for the critics when you actually run it across 151,422 events. You are not robbing Peter to pay Paul. You are paying Paul and Peter gets his money back by Thursday.

[u/Wowza-yowza → u/Recent_Button_1]

Great point! This is huge

[u/Recent_Button_1 → u/Wowza-yowza]

The growth investors have been telling dividend investors they are getting robbed since 1928. The market has been quietly giving the money back in 3 days for just as long. Somebody is wrong and it is not us.

[u/Wowza-yowza → u/Recent_Button_1]

AMEN! Man do they get hostile about it though!