Price-to-Peak Book>>>Future performance?

Price-peak-BV is about 1.15x now? Future performance, historically, fantastic?

Back-up the truck time?

If not now>>>when?

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I think Jim had said this metric had been as low as a little under 1.00 a few times. But 1.15 is pretty good in the grand scheme of things.

Also, I think all of Jim’s old posts are still readable (but not for long, according to TMF), in case you or anybody else wants to copy and paste them into a file for later reading. He was quite free with data and his expectations for subsequent results, based on this metric and others.

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I have P/BVpeak of 1.08. Our peak date may be different since I’m adjusting for inflation.

Either way, according to history, this seems to be a good time to buy Berkshire. It’s worth mentioning, @tedthedog would be very much correct in stating the current P/BV uses a very stale BV with a fresh BV to be delivered here in a couple/few weeks. Some correction could be done to the current stale BV to get a closer approximation to next reported book value.

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Thanks. MUNGOFITCH liked using p/peak BV as the best predictor of future 12 most returns. Appears we are at back-up the truck levels. However, increasing talk of systemic risk and sovereign debt bubbles bursting?

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Thanks very much for the. data. Very helpful. I had peak book at $231/B share?

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1.15 - 1.18 0.5 Year 1 Year 2 Year 2.33 Year
Low -8.3% 2.4% 12.2% 14.3%
25 %ile 5.2% 13.1% 47.6% 47.5%
Median 8.4% 27.5% 52.9% 60.4%
75 %ile 14.4% 33.4% 57.3% 65.3%
High 32.4% 41.2% 73.7% 78.8%

Rounding up to 1.15 book, that’s what I have as historical returns at this figure, with my somewhat rough dataset, late 2008 - recent. As indicated, the “bucket” is Price / PeakBook of 1.15 - 1.18.

Not inflation adjusted and non-annualized returns are shown.

Future won’t be like the present, of course, but this has been a good entry point in recent history.

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My peak book value occurred in Q1 2022 and is about 5% higher than reported Q1 book value due to the inflation adjustment.

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@cwags02, love that graphic!

The ‘Frequency’ row is cumulative frequency, i.e. cumulative proportion of the data falling in bins up to and including the bin of each column entry (it tops out at 100%)?

So, e.g. the entry in the “Frequency” row with “6.5%” means that 6.5% of the data has fallen into bins holding data equal or less than P/BV=1.05?
Said differently, 6.5 - 1.4 - 0.1= 5%, so 5% of data falls in the bin with P/BV between 1.05 and 1.1?

In general, if subtract the sum of previous bin values from the present bin value then this is the proportion of data falling into the present bin?
That’s an interesting value.

I’m starting to look into services that provide historical fundamental data. But perhaps someone has experience with one that provides good data at a semi-reasonable price?

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My buys in Feb/March 2020, price to then known (peak) book:
1.15
1.12
1.12
1.12
1.12
1.12
1.02
1.00
0.99
0.92

It can always go lower.

CAGRs
11.5%
12.7%
12.7%
12.7%
12.7%
12.8%
16.9%
18.1%
18.7%
22.2%

But it worked out satisfactorily so far.

If I had little Berkshire I’d buy some here. I already have too much, so I’ll wait.

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BRKB looking $260/B share pre market

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Wow, what a recovery. It’s not often we see a 3% gain in a day!

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@tedthedog - yes, that’s cumulative frequency, not just frequency. Sorry about the confusion! Your math and results on the frequency of the bins is entirely correct too. I’ve updated the table to reduce the confusion.

It’s also worth mentioning I was able to get the daily stock price data, quarterly book, and monthly CPI data all sorted going back to Jan 1 2006. The table below includes all the data ~ 4,200 data points between today and Jan 1 2006. It went together a lot faster than I thought.

For those with a decent memory - mungofitch mentioned selling JAN 2023(ish) covered calls in mid/late March 2022. The P/BVcurrent was around 1.5 where higher P/BV multiples occurred only ~6% of the time. I was busy coattailing so I didn’t realize why it was such a good idea at the time.

I’ve started laying out a similar analysis for my favorite simple companies I like to follow (FAST, GGG, ECL, KMX, etc) and the results are fascinating and further lend credence to @tedthedog’s comment about the hard part of all of this is picking the right company.

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I wasn’t being pedantic, just thought that knowing what percentage of data was in each bin seemed interesting. The table is beautiful!

Seems like we have two threads on the same issue, on the other thread I mentioned a free way to get some of the fundamental data like price to book (I haven’t investigated the source, and make no representation that the data is good, buyer beware, it’s free data).
the other thread

You mentioned you pulled Price to Book from BRK annual reports before, are you doing that for the other tickers or have you identified a good, not too expensive, data feed?
Totally agree, looking at other tickers will be extremely interesting, you’re way ahead of me.

Also, if one thinks back to Greenblatt’s ‘magic formula’ and his attempts to define how to buy ‘good’ companies ‘cheaply’, then conceivably other fundamental ratios could make sense too, the appropriate one might vary depending on the nature of the companies e.g. services vs goods.

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