Post New

I have discovered a new investment strategy that I've been using for the past six months, and it has proven to be very effective. This approach is grounded in two key concepts. First, it's essential to learn how to determine the intrinsic value of a stock. Once you grasp what a stock should be worth, you can then select the appropriate strike price when selling puts and calls.

In my experience, I have executed approximately 80 trades, with each one yielding a profit. However, I do have an unrealized loss on one trade. Essentially, I sold a put option, but when the stock plummeted, $40 was deducted from my account, and I ended up with a stock valued at only $30. Fortunately, I understand the intrinsic value of this stock, which enables me to sell call options while I wait for its price to recover to its intrinsic value. If the stock were to drop so drastically that no call options were available for me to sell, I could simply hold on until it returns to its intrinsic value.

The concepts behind this strategy are thoroughly detailed in the book "Wealthy and Wise" by David Chenier.

From your limited description, it sounds like the wheel strategy

In my experience, I have executed approximately 80 trades, with each one yielding a profit

Interesting, but what was your return and timeframe?

80 trades in 6 months is a lot.
Lot lot.
What matters is not how many trades are wins, but how much money you have made. This is the trap that neophytes at options get clobbered with. 9 of 10 trades win but the 10'th trades loses more dollars than the 9 trades gained.


How about this?
"Imagine a trading strategy so simple it takes just five minutes a year to manage, yet it has outperformed the Nasdaq for over a decade."

https://www.quantifiedstrategies.com/a-simple-2-et...
A Simple 2-ETF Strategy That Outperforms the Nasdaq

Backtest: https://testfol.io/?s=eeBYH1YIKgi


Or if you are okay with buying pallets of Tums & sleeping pills: TQQQ.
https://testfol.io/?s=7B7x3bkw2K8

Massive -82% (!!!) drawdown
Drop from $2,050,000 to $420,000
While at the same time of that $2,050,000 QQQ was $103,500 and SPY was $55,000.
The bottom of $420K was higher than the peaks of $103K & $55K

Here's a possible strategy, just made it up.

Observation: Berkshire Hathaway stock stays fairly close to fairly valued (the range is smaller for most other things), which is relatively easy to estimate and trends pretty well. This is a graph of a smoothed valuation metric. (basically a 16 quarter WMA of inflation adjusted book per share, scaled to match the average valuation multiple in the last 20 years. (smoothed line moved up to minimize RMS errors versus price line)
http://stonewellfunds.com/SmoothedRealValuePerShar...

The ratio of current market price to that trend line has a standard deviation of 11.8% in the last 20 years.

The strategy:
Put 50% of your portfolio into Berkshire stock, hold the other half in cash.
Each month or quarter,
* Write a call option (covered call) backed by your stock, at the net exit price (strike + premium) that is one standard deviation above the current value of the trend line.
* Write a put option backed by your cash, at the net entry price (strike minus premium) that is one standard deviation below the current value of the trend line.

Every time the call you've written is exercised and your stock is called away, simply use the cash to buy back stock equal to half your portfolio value.
Every time the put you've written is exercised and you're "forced" to buy the stock cheaply, simply sell the stock (whatever brings you back to half stock) and write a new put.
So, your portfolio will be quite close to 50/50 stock and cash most of the time, with the occasional brief blip to 0% stock or 100% stock.

That's it.

Note that often the put or call that you are writing will be in the money. (big premium, almost certain to be exercised). That's normal for this strategy.

Over time you should get a return equal to the sum of:
* Half the average return from BRK, since you're averaging half long, around inflation + 3.5%. That's half of Berkshire's expected return of about inflation + 7%. That estimate is about 1% lower than history, but hardly a big stretch.
* The return of short term interest rates on half your portfolio. If you want maximum return, you'd back your options with an ever-renewed ladder of actual 3-month T-bills, which good brokers are fine with.
* A few percent from the average time value erosion of the short calls you're forever writing, on half your portfolio.
* A few percent from the average time value erosion of the short calls you're forever writing, on half your portfolio.
In a typical month, one of those two will raise a fair bit of cash.

I don't have the data to test this strategy. But I've essentially done it off and on by the seat of my pants, so I have a strong feel for what it does.

Jim

80 trades in 6 months is a lot.
Lot lot.
What matters is not how many trades are wins, but how much money you have made. This is the trap that neophytes at options get clobbered with. 9 of 10 trades win but the 10'th trades loses more dollars than the 9 trades gained.

I just counted: 85 trades of buying/selling puts this year. Many more than just 1/10 lost money, 28, but apart from 6 only pennies, not at all changing that the other around 60 made the huge profits I wrote about on the Berkshire board.

Not with a mechanical strategy, but the simple observation that Berkshire was extremely expensive. So I dared to "bet the bank", in line with what Charlie&Warren were saying, that when you see THE opportunity you have to bet big***.

But I invested always roughly the same amount in any of those puts. So how should "the 10'th trades loses more dollars than the 9 trades gained" happen? That can only happen when falling for "doubling down" when losing --- and that has nothing to do with "neophytes at options" but with a limitless and therefore hopeless gamblerīs mentality (which apparently I have - but luckily with limits).


***Probably never again because with any other stock or index I would never be sooo convinced of an unsustainable mispricing, see my post about intending to buy S&P puts now --- and the next one that I quickly changed my mind.

(Realising that while I THINK the S&P being this high is unsastainable I am thinking this since many years now, being wrong all those years, and therefore finally admitting to myself that in fact I know nothing about what the S&P will do tomorrow or next year, that all I know a bit about is Berkshire).

My guess is 40% annualized, but I am not counting the unrealized loss. I say that, because my spreadsheet annualizes the return on each option and they were about 40%.

From your limited description, it sounds like the wheel strategy

It is similar, but it is based on valuations. You need to be good at calculating the intrinsic value of the stock. Also, it is set up, so you never lock in a loss. The only way to lose money is if you sell a put, and the stock plunges, which did happen to me. However, I can sell calls at the strike price of the put, so no loss is locked in. You do need to find just the right stock for it to work.

You need to be good at calculating the intrinsic value of the stock.

Well, that's the goal all the time, isn't it? If you _accurately_ know the intrinsic value of stocks you don't need to play these games. You can just buy the stock(s) that are priced too cheaply.

But that's the whole thing. It is *impossible* to know the intrinsic value of stocks. If it was, all the big guns at Blackrock & Goldman would buy them and there'd be nothing left for us.

Says a person (me) who didn't buy BRK at $2000 a share, since it was obviously overvalued.


... my spreadsheet annualizes the return

Annualizing the returns of a short range of dates gives numbers that are essentially meaningless. Like today's Nasdaq gain of 0.94% is 2561% annual.
So you gotta be careful not to get swayed by seeing large numbers.

Well, that's the goal all the time, isn't it? If you _accurately_ know the intrinsic value of stocks you don't need to play these games. You can just buy the stock(s) that are priced too cheaply.

But that's the whole thing. It is *impossible* to know the intrinsic value of stocks. If it was, all the big guns at Blackrock & Goldman would buy them and there'd be nothing left for us.

Says a person (me) who didn't buy BRK at $2000 a share, since it was obviously overvalued.

I spent a lot of effort studying it, and I can get a range, but not an exact number.

This is an interesting strategy.
As is something akin to 50/50 TYD TQQQ etc.
I think a lot of what's happening in some of these screens is chasing large cap tech returns.
My bet is the next leg down unduly punishes them, and these magical strategies look rugged for 5 - 10 years.
Just a guess.
The TYD strategy performs a lot worse than your's but it eats 2022 (I think), one of the worst treasury years of all time.
Maybe that's a good thing as it's more realistic over a long period of time.

Hi Jim,

While this probably belongs on the BRK board, as it is a strategy based around BRK, I wanted to dive into the exact calculations required to generate the plot:

This is a graph of a smoothed valuation metric. (basically a 16 quarter WMA of inflation adjusted book per share, scaled to match the average valuation multiple in the last 20 years. (smoothed line moved up to minimize RMS errors versus price line)

Let me see if I understand these steps:

(1) Get previous 16 quarters of inflation adjusted book per share
(2) Get previous 20 years of PE multiples
(3) WMA = triangular weighting of (1)/(sum of weights) * average(2) for each quarter
(4) Do a least squares match of offset of (3) to price over same timeframe (any smoothing)?
(5) Calculate the standard deviation of the offset line in (4) vs price (assume gaussian spread).

Is that correct? Or did I mess something up. This seems like something that changes rather slowly. Maybe only redo the calcuation every quarter?

--G

(1) Get previous 16 quarters of inflation adjusted book per share
(2) Get previous 20 years of PE multiples
(3) WMA = triangular weighting of (1)/(sum of weights) * average(2) for each quarter
(4) Do a least squares match of offset of (3) to price over same timeframe (any smoothing)?
(5) Calculate the standard deviation of the offset line in (4) vs price (assume gaussian spread).

More or less.



(1) Yes. An elaboration I didn't mention but isn't material: I assumed that any book-per-share drop of more than 4% below peak to date was transient, so I replace big book dips with 4% less than peak to date. The assumption is that even though book per share isn't rising, the actual value is rising. Or at the very least it isn't actually falling. This means the smoothed line is (to date) always rising, never falling.
(2) doesn't apply, not needed anywhere.
(3) right
(4) yes, but it's just the final scale factor to minimize the error between the smoothed line and the historical prices. Book per share, especially smoothed book per share, is a whole lot lower than the average price.
(5) I didn't do a step like this.

So, my process could be revised as what I did to create the graph:
(1) Get previous 16 quarters of inflation adjusted book per share
(2) Replace any low book values (dips during bear markets) with 96% of the peak-to-date real book-per-share.
(3) WMA of the prices. (most recent book*16 + previous quarter's book * 15 + ... + oldest book * 1))/136. Using the "no big dips" book values adjusted by step 2.
(4) Find the scale factor to apply to the smoothed line which makes the best fit to the real price history. I used 20 years of history for this, to get a single simple single multiplier factor.
...and optionally:
(5) For each day in the last 20 years, calculate the ratio of then-current real price to the then-current point on that scaled smoothed line. The average of this ratio is by construction 1. Look at the correlation between that ratio and the forward stock returns. Unsurprisingly, a high ratio of current-price-to-smoothed-value-line has usually given low average returns for the next year or two, and vice versa.
Step 5 just gives the typical returns from my post at the Berkshire board:

In the last 20 years,
Cheapest 15% of the time: Two year forward real total return average 17.8%/year
Next 15% of the time: Two year forward real total return average 14.8%/year
Next 20% of the time: Two year forward real total return average 10.0%/year (just a little cheaper than average)
Next 20% of the time: Two year forward real total return average 8.7%/year (just a little more expensive than average)
Next 15% of the time: Two year forward real total return average 0.6%/year
Most expensive 15% of the time: Two year forward real total return average -5.4%/year

Jim

So, my process could be revised as what I did to create the graph:
...
In the last 20 years,
Cheapest 15% of the time: Two year forward real total return average 17.8%/year
Next 15% of the time: Two year forward real total return average 14.8%/year
Next 20% of the time: Two year forward real total return average 10.0%/year (just a little cheaper than average)
Next 20% of the time: Two year forward real total return average 8.7%/year (just a little more expensive than average)
Next 15% of the time: Two year forward real total return average 0.6%/year
Most expensive 15% of the time: Two year forward real total return average -5.4%/year


PS

In the context of my suggested mechanical strategy using a value line like this:

When things are expensive, and returns have been on average negative, you'd be selling at the money or even in the money calls for quite high premiums, while selling very low strike puts for very low premiums. (still, it's money, and pretty much risk free). So long as the price remains high your high strike calls would probably get exercised, perhaps repeatedly, but you'd be gathering time value each time. When the stock eventually falls in valuation level, you'd keep the whole premium, which would sometimes include some in-the-money premium and be quite lucrative. That's more or less the situation I've found myself in these last couple of months.

As the list above shows, when valuations are high the subsequent *average* return is likely pretty low. The price and valuation level might stay high for a while, but sooner or later you're likely to see "the usual".

Jim

Jim, I like it of course.
It's always easy to for someone to suggest that someone else do extra work, but if you do get a moment some time then it'd be interesting to see the associated scatterplot of two year forward real return vs the value measure.

it'd be interesting to see the associated scatterplot of two year forward real return vs the value measure.

Here is a scatterplot not "value", but ratio of 4 year SMA vs. CAGR of the next 2 years.

https://ibb.co/qLq4YSBj

It's from something I'm working on but not quite ready to release.

Thanks RayVT.
I made a similar plot when replying to a question in the original thread, this should get you there
https://www.shrewdm.com/MB?pid=-2&previousPostID=2...

FWIW, I'd expect a plot using a value measure e.g. book value or related value measure, to look a little bit cleaner.
A table provides an accurate summary, but looking at the raw data itself can be informative.

if you do get a moment some time then it'd be interesting to see the associated scatterplot of two year forward real return vs the value measure.

Geek note:
In this sort of situation, I think it's important to reduce the noise resulting from the randomness of the valuation on the specific end date anniversary. So to calculate forward returns, I don't do (price two years from now)/(price today). Instead I do (average price 1.75 to 2.25 years from now)/(price today). It's amazing how much this helps your models: it still looks at the short term squiggles of price and valuation on purchase date which is what matters, but doesn't get thrown off by the quirks of a specific end day.

This is a scatter plot of ratio of price to my smoothed and scaled-up value line, over the last 20 years, daily figures. The forward two year returns are an annualized rate, after inflation.
http://www.stonewellfunds.com/PriceToTrendAndForwa...

With today's price of $713670 ($475.78 per B), today's smoothed line level is about $613570 and the ratio is about 1.163. Using that ratio, the formula fit from the graph suggests one might expect a forward two year return around -1.62%/year after inflation. The standard deviation of the ratio in the last 20 years has been 11.8% with mean (by construction) of 1.

Jim

With today's price of $713670 ($475.78 per B), today's smoothed line level is about $613570 and the ratio is about 1.163. Using that ratio, the formula fit from the graph suggests one might expect a forward two year return around -1.62%/year after inflation. The standard deviation of the ratio in the last 20 years has been 11.8% with mean (by construction) of 1.

PS, -1.6%/year doesn't sound so bad. The forecast on May 2 was -10.2%/year. Price goes down, likely forward return goes up. Magic!

Jim

Does anyone have (a perferably free) source for inflation adjusted book per share? Or just quarterly book per share? I can find CPI adjustments and correct later. Also, need daily historical price data for BRK-B (could scrape the Yahoo pages).

Thanks,

--G

Does anyone have (a perferably free) source for inflation adjusted book per share? Or just quarterly book per share?

Here are the unadjusted figures and the CPI figures I have.
Better to adjust them yourself, since you probably want to multiply by whatever CPI is the day you do it.

The CPI figure is the most recent KNOWN figure at the end of the fiscal period.
Some of the early book figures are approximate. I think I used annuals and interpolated the March, June and September figures. And even the early annual figures are back converted from rounded annual growth figures.

But you won't get much in the way of reasonable results on the extremely old figures anyway. The rate of growth of value per share had a big kink in 1998 on the acquisition of General Re, but has been pretty constant since then. The valuation multiples were crazy till 1999, a dip in 2000, a little high 2001-2007, and in a relatively bounded range 2008 to date. You can get pretty good (numerically stable) analysis starting around 2003.

These are of course the figures for A shares. B shares are 1/1500 the economic value.

period end    release date    book       CPI
1989-12-31    1990-02-26        4,293    126.10
1990-03-31    1990-04-28        4,163    128.70
1990-06-30    1990-07-28        4,671    129.90
1990-09-30    1990-10-28        4,229    132.70
1990-12-31    1991-02-26        4,611    133.80
1991-03-31    1991-04-28        5,289    135.00
1991-06-30    1991-07-28        5,458    136.00
1991-09-30    1991-10-28        5,940    137.20
1991-12-31    1992-02-26        6,437    137.90
1992-03-31    1992-04-28        6,275    139.30
1992-06-30    1992-07-28        6,763    140.20
1992-09-30    1992-10-28        7,356    140.90
1992-12-31    1993-02-26        7,743    142.00
1993-03-31    1993-04-28        8,079    143.10
1993-06-30    1993-07-28        8,280    144.20
1993-09-30    1993-10-28        8,675    144.80
1993-12-31    1994-02-26        8,851    145.80
1994-03-31    1994-04-28        8,521    146.70
1994-06-30    1994-07-28        9,104    147.50
1994-09-30    1994-10-28       10,148    149.00
1994-12-31    1995-02-26       10,081    149.70
1995-03-31    1995-04-28       11,155    150.90
1995-06-30    1995-07-28       12,233    152.20
1995-09-30    1995-10-28       13,271    152.90
1995-12-31    1996-02-26       14,025    153.60
1996-03-31    1996-04-28       15,180    154.90
1996-06-30    1996-07-28       16,528    156.60
1996-09-30    1996-10-28       17,500    157.30
1996-12-31    1997-02-26       19,011    158.60
1997-03-31    1997-04-28       19,631    159.60
1997-06-30    1997-07-28       22,732    160.10
1997-09-30    1997-10-28       22,694    160.80
1997-12-31    1998-02-26       25,488    161.50
1998-03-31    1998-04-28       28,021    161.90
1998-06-30    1998-07-28       29,743    162.80
1998-09-30    1998-10-28       24,838    163.40
1998-12-31    1999-02-26       37,801    164.00
1999-03-31    1999-04-28       38,097    164.50
1999-06-30    1999-07-28       38,189    166.20
1999-09-30    1999-10-28       36,384    167.10
1999-12-31    2000-03-11       37,987    168.30
2000-03-31    2000-04-28       37,013    169.70
2000-06-30    2000-07-28       37,853    171.30
2000-09-30    2000-10-28       38,934    172.80
2000-12-31    2001-03-10       40,442    174.10
2001-03-31    2001-04-28       38,241    175.80
2001-06-30    2001-07-28       38,458    177.70
2001-09-30    2001-10-28       37,387    177.50
2001-12-31    2002-03-09       37,920    177.40
2002-03-31    2002-04-28       39,452    177.80
2002-06-30    2002-07-28       40,660    179.80
2002-09-30    2002-10-28       40,814    180.50
2002-12-31    2003-03-08       41,727    181.30
2003-03-31    2003-04-28       42,580    183.10
2003-06-30    2003-07-28       45,987    183.50
2003-09-30    2003-10-28       46,860    184.60
2003-12-31    2004-03-06       50,498    184.50
2004-03-31    2004-04-28       51,855    186.20
2004-06-30    2004-07-28       52,307    189.10
2004-09-30    2004-10-28       52,456    189.50
2004-12-31    2005-03-05       55,824    191.00
2005-03-31    2005-04-28       56,159    191.80
2005-06-30    2005-07-28       57,208    194.40
2005-09-30    2005-10-28       58,127    196.40
2005-12-31    2006-03-04       59,377    197.60
2006-03-31    2006-04-28       61,863    198.70
2006-06-30    2006-07-28       63,301    202.50
2006-09-30    2006-10-28       66,292    203.90
2006-12-31    2007-03-01       70,281    201.50
2007-03-31    2007-04-28       71,221    203.50
2007-06-30    2007-07-28       74,499    207.90
2007-09-30    2007-10-28       77,482    207.90
2007-12-31    2008-03-01       78,008    210.20
2008-03-31    2008-04-28       77,072    211.70
2008-06-30    2008-07-28       76,163    216.60
2008-09-30    2008-10-28       77,558    219.10
2008-12-31    2009-02-28       70,530    212.40
2009-03-31    2009-05-04       66,248    212.20
2009-06-30    2009-07-31       73,806    213.90
2009-09-30    2009-10-29       81,247    215.40
2009-12-31    2010-02-27       84,487    216.30
2010-03-31    2010-04-30       89,374    216.70
2010-06-30    2010-07-30       86,661    218.20
2010-09-30    2010-10-29       90,823    218.30
2010-12-31    2011-02-26       95,453    218.80
2011-03-31    2011-04-29       97,081    221.30
2011-06-30    2011-07-28       98,716    226.00
2011-09-30    2011-10-28       96,876    226.50
2011-12-31    2012-02-25       99,860    226.20
2012-03-31    2012-04-27      106,588    227.70
2012-06-30    2012-07-26      107,377    229.80
2012-09-30    2012-10-25      111,718    230.40
2012-12-31    2013-03-02      114,214    230.20
2013-03-31    2013-05-03      120,519    232.20
2013-06-30    2013-07-25      122,898    232.90
2013-09-30    2013-10-24      126,764    233.90
2013-12-31    2014-03-01      134,973    233.10
2014-03-31    2014-04-24      138,420    234.80
2014-06-30    2014-08-01      142,481    237.90
2014-09-30    2014-11-07      144,540    237.90
2014-12-31    2015-02-28      146,186    236.20
2015-03-31    2015-04-24      146,959    234.70
2015-06-30    2015-08-07      149,697    237.80
2015-09-30    2015-11-08      151,085    237.90
2015-12-31    2016-02-27      155,501    237.30
2016-03-31    2016-05-07      157,329    237.10
2016-06-30    2016-08-05      160,009    240.20
2016-09-30    2016-11-04      163,782    240.90
2016-12-31    2017-02-25      172,108    241.40
2017-03-31    2017-05-05      178,071    243.60
2017-06-30    2017-08-05      182,814    244.70
2017-09-30    2017-11-04      187,427    245.50
2017-12-31    2018-02-24      211,750    246.70
2018-03-31    2018-05-05      211,178    249.00
2018-06-30    2018-08-04      217,675    251.60
2018-09-30    2018-11-03      228,794    252.15
2018-12-31    2019-02-23      212,497    252.04
2019-03-31    2019-05-04      225,575    252.78
2019-06-30    2019-08-03      234,109    256.09
2019-09-30    2019-11-02      243,927    256.60
2019-12-31    2020-02-22      261,417    257.21
2020-03-31    2020-05-02      229,358    258.68
2020-06-30    2020-08-08      245,836    256.39
2020-09-30    2020-11-07      264,323    259.90
2020-12-31    2021-02-27      287,031    260.23
2021-03-31    2021-05-01      293,636    263.00
2021-06-30    2021-08-07      311,276    269.20
2021-09-30    2021-11-06      316,443    273.60
2021-12-31    2022-02-26      342,621    277.95
2022-03-31    2022-04-30      345,469    283.72
2022-06-30    2022-08-06      314,090    292.30
2022-09-30    2022-11-05      310,652    296.17
2022-12-31    2023-02-25      311,995    299.60
2023-03-31    2023-05-07      347,932    300.84
2023-06-30    2023-08-05      372,966    304.10
2023-09-30    2023-11-04      363,413    307.03
2023-12-31    2024-02-24      389,372    307.05
2024-03-31    2024-05-04      397,627    310.33
2024-06-30    2024-08-03      418,806    314.10
2024-09-30    2024-11-02      437,580    314.80
2024-12-31    2025-02-22      451,507    315.49
2025-03-31    2025-05-03      455,055    319.10

Here is a scatterplot not "value", but ratio of 4 year SMA vs. CAGR of the next 2 years.

One thing interesting about the scatterplot is that BRK-A doesn't have very much time, overall, with a negative CAGR and being above its 4-yr SMA, and none at all when it's below its 4-yr SMA.

Maybe BRK-A has been a good buy for a while....

Eric Hines

This is a scatter plot of ratio of price to my smoothed and scaled-up value line, over the last 20 years, daily figures. The forward two year returns are an annualized rate, after inflation.

For fun, here is almost the same graph, but looking forward four years instead of two.
Differences: only the period since mid 2009, and it's four year forward real returns rather than two years forward. As before, the end date is smoothed. In this case, the smoothed endpoint is the average price 3-5 years after purchase date. So, rate of return is ((average real price 3-5 years later)/(real price today))^(1/4)
http://www.stonewellfunds.com/PriceToTrendAndForwa...

This start date is chosen to be an era with an extraordinarily good fit! Start dates in the 2005-2009 range gave lower returns for the same starting apparent valuation level, because of the step change downwards in valuation levels that happened around the credit crunch.

Valuation is mostly useless as a timing indicator, but pretty good for getting an idea of likely longer term returns for anything that has a relatively predictable trend of future value.

Jim

Thanks Jim!

Below is a link to the devil's plot of the two year CAGR, now based on an 'average two year price' as Jim defined it in his Geek note, versus the SMA 'valuation' measure.
https://www.dropbox.com/scl/fi/h2g07ldh4xmyef4qgd5...
A point is plotted for each trading day.

Here's the associated summary table

Bin | Min value1 | Max value1 | Avg CAGR (%)
----|---------------|---------------|-------------
  1 |        0.6609 |        1.0119 |        17.9
  2 |        1.0120 |        1.0791 |        15.4
  3 |        1.0793 |        1.1137 |        13.8
  4 |        1.1137 |        1.1416 |        11.1
  5 |        1.1417 |        1.1738 |        12.6
  6 |        1.1739 |        1.2100 |        12.5
  7 |        1.2101 |        1.2501 |         8.0
  8 |        1.2503 |        1.3069 |         5.7
  9 |        1.3070 |        1.3689 |         5.7
 10 |        1.3690 |        1.5694 |         3.8

Jim used a weighted moving average (WMA) on his valuation measure while this plots uses a simple moving average (SMA). Inflation adjustment was not used in this plot.

Ted
(for the devil)

Also, need daily historical price data for BRK-B

I have it. email me and I'll email it back.

One thing interesting about the scatterplot is that BRK-A doesn't have very much time, overall, with a negative CAGR and being above its 4-yr SMA, and none at all when it's below its 4-yr SMA.

Yes. The sweet spot for this 4yr/2yr screen is 0% to about 70% above the 4 year SMA. Very few negative returns. There have been a lot of high returns in the +20% to +30% range.

I had never thought about it, but this plot shows that when the price is way way above the SMA it is a very bad time to own BRK. I had to recheck some of those datapoints to verify them.
What that is, is times when BRK shot to the moon, like doubling in 4 years, and it headed for a comeuppance and a drop down to more rational prices.

The 4 years beginning 5/1994 it went from $16,000 to $78,000.
Then fell to $51,000.

Maybe BRK-A has been a good buy for a while
So it would seem. It's been right in the range where there have been quite good returns.

OK, I think I have this, though there are a few small details I want to clarify:

(1) The Book data is adjusted by CPI (that is, Book is divided by CPI) and then the WMA is calculated.
(2) The mean (price data) / mean( CPI adjusted WMA book data) should provide multiple to have two lines track
(3) For the variance, are you using close/WMA or close - WMA?
(4) You use the previous 20 years worth of daily data for variance?

Should the closing prices of BRK *also* be adjusted for CPI data? If not, why not? Also, since both lines (the adjusted WMA and the closing prices of BRK) exhibit linear or even exponential trends, should we be taking the log of both of the data and removing the linear part of the log line on each and then comparing the variance from the line?

Thanks, G.

(1) The Book data is adjusted by CPI (that is, Book is divided by CPI) and then the WMA is calculated.
(2) The mean (price data) / mean( CPI adjusted WMA book data) should provide multiple to have two lines track
(3) For the variance, are you using close/WMA or close - WMA?
(4) You use the previous 20 years worth of daily data for variance?


(1) yup
(2) yup. This just shifts the WMA up or down so that it kind of aligns with the price
(3) realclose/realbookwma -1. (percentage error, in effect)
(4) yup.

Re #4, you could use any time frame. Berkshire's valuation had sort of a step change downwards around the credit crunch end 2007 right after the price spiked, which seems to have been pretty lasting so far. So using the history from the start of 2008 corresponds to the "modern era" of valuation. That would be a pretty reasonable choice. (almost the same, but my 20 years uses 2.5 years of the era when prices were higher).

As mentioned, the method I used was a bit more elaborate, but not meaningfully different. The same, but using two different value yardsticks. It goes like this:
(a) Book per share data is adjusted by CPI, then 16-quarter WMA is calculated to get BookWMA
(b) Scale the BookWMA to minimize error versus real price in the last 20 years to get ScaledBookWMA
(c) Value metric per share data is adjusted by CPI, then 16-quarter WMA is calculated to get ValueWMA
(d) Scale the ValueWMA to minimize error versus real price in the last 20 years to get ScaledValueWMA
(e) Take the simple average of ScaledBookWMA and ScaledValueWMA. That's what's on the graph.

So what is the value metric in (c)? The method I use is a bit complicated, but the difference versus using book value is (to date) so small that you needn't worry about it, you could just use book. The main difference is that is it a pinch more pessimistic lately because operating earnings have not been great lately.

In case anybody is interested, my valuation method goes like this:
* Calculate market value of all investments. Cash, equities, fixed income, equity method investments.
* Reduce the investments by 30% of insurance "float" (provisions for claims yet to be paid), to approximate the amount of investments which will forever earn nothing after tax and inflation -- insurers have to have a lot of ready cash on hand.
* Optional: Reduce the investments by the amount of any big stock positions trading over 21 times earnings (replace market value with 21 times earnings). Apple got pretty expensive for a while there, and it was a BIG position.
* Calculate the trailing-four-quarter net after-tax income from operating subsidiaries, being rails, insurance, and manufacturing/service/retail. These are stated at the start of the management discussion and analysis section of each quarterly and annual report.
* Adjust the operating earnings by replacing the actual trailing-four-quarter underwriting profit/loss with a cyclically adjusted figure. I use the average of (1.3% of float) and (2.7% of premiums earned).
* Multiply the operating earnings by a constant P/E to get some estimate of value of those businesses. I use a multiple of 15, but it isn't critical.
* Add the adjusted total investments from above to the proxy value of the operating earnings to get a total value for the firm.
* Divide by shares outstanding at end of reporting period to get value metric per share.

This result is not the true value of a share...what does that even mean?...but the idea is that it rises at the same rate as true (but unknowable) value per share. So, it can be used to look at the rate of increase of value, or to look at the historical relationship between price and value metric to get an idea of over/undervaluation relative to history.

This method has some quirks which are not obvious. For example, it ignores debt. I will continue to use the model only so long as I consider the debt level to be sustainable and in effect trivial. Another quirk is that it implicitly assumes that, if the cash pile is unusually large as it is right now, most of it will eventually get deployed as part of the normal average mix of portfolio allocations. i.e., it doesn't look at the current cash as the stuff earning nothing, it just assumes that an *average* amount of stuff will earn nothing over time.

Jim

Hi Jim,

Thanks for the info, that helped quite a bit. For some reason when I start with Jan 2008 I can't quite get 0 for the mean of the spread from the line, I get -1.5% (which is weird, since I am dividing by the mean of both the WMA and the adjusted close).

Using the data since 2008, I have the following results:

For 7/22/2025, I have BRK-B close at 478.13, and a CPI adjusted close at 149.84. The CPI Adjusted WMA is 1278, and the ratio to match is 9.77, thus the matching WMA is 130.86

The standard deviation of pricing is 11.47%

If I then reverse the CPI calculation, the trendline is 417.6, and the CALL is at 465 and the PUT at 370.

This seems to match what you had, but the last thing I need to keep track of this in realtime is the source of CPI data you are using.

Thanks, G.

PS: When I do a histogram of the deviation from trendline from 2008 to now, it isn't a great gaussian fit, it has a peak at -15-18%, and much peakier around 0 than a gaussian would be. Doing a plot of the CPI adjusted WMA and closing prices (logy) very much shows the price going up and down around the trendline.

This seems to match what you had, but the last thing I need to keep track of this in realtime is the source of CPI data you are using.

I tend to use my subscription from Pinnacle for a lot of things, including CPI.

But if you want the official CPI release, it's free but they don't make it easy! It seems they want to force you to see the year-on-year increase, not the index level.
Go to this link and search for CUUR0000SA0, ignoring any line tagged M13 (which is annual average)
https://download.bls.gov/pub/time.series/cu/cu.dat...

Jim

Thanks for the link!

Perhaps you can explain something. I had always thought that the CPI was based on 1967=100 but these data are based on an average 1982-4 being 100. Did something change? Are the multiple CPIs out there?

Thanks,
HH/Sean

I had always thought that the CPI was based on 1967=100 but these data are based on an average 1982-4 being 100.

Dumb question. Yes, it was changed in Jan 1983. There have been several rebasings over the years. Part of it is to allow for new widgets to be included in the index (e.g. PCs) and others (typewriters) to be removed. They chain it based on the things that are constant (food, clothing) but there would seem to be some SWAGs involved in the chaining. I guess taking econ 101 in the years between those two rebasings just branded the first of the two in my ur-neurons.

Rgds,
HH/Sean

Wow, that is a pain in the butt! For anyone interested, I was trying for a google sheet that could import it and filter it automatically, but the URL is too large for an import. I can do it from pasting the data in, but it is a bit of a pain.

Right now I am working on a python script that will import it and filter it and reconstruct the date, so that I can use it going forwards.

--G

OK, I now have a python file to extract the CPI data. Here is the full python if anyone wants to replicate it:

import requests

def import_filtered_cpi():
    # URL for BLS CPI data
    url = "https://download.bls.gov/pub/time.series/cu/cu.dat..."
    # Set User-Agent to avoid 403 errors
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36"
    }

    # Fetch data
    try:
        response = requests.get(url, headers=headers)
        response.raise_for_status()  # Raise exception for non-200 status codes
    except requests.exceptions.RequestException as e:
        print(f"Error fetching data: {e}")
        return

    # Split data into rows
    data = response.text
    rows = data.strip().split("\n")

    # Map period to month (M01 -> 01, M02 -> 02, etc.)
    period_to_month = {
        "M01": "01", "M02": "02", "M03": "03", "M04": "04",
        "M05": "05", "M06": "06", "M07": "07", "M08": "08",
        "M09": "09", "M10": "10", "M11": "11", "M12": "12"
    }

    # Prepare output file
    output_file = "cpi_filtered_data.txt"

    # Filter rows and write to file
    with open(output_file, "w", encoding="utf-8") as f:
        # Write headers
        f.write("date\tvalue\n")

        # Filter for series_id = "CUUR0000SA0" and period != "M13"
        filtered_rows = []
        for row in rows[1:]:  # Skip header
            columns = row.split("\t")
            series_id = columns[0].strip()
            year = columns[1].strip()
            period = columns[2].strip()
            value = columns[3].strip()
            if series_id == "CUUR0000SA0" and period != "M13":
                # Convert period to month and format date as YYYY-MM-01
                if period in period_to_month:
                    date = f"{year}-{period_to_month[period]}-01"
                    filtered_rows.append([date, value])
                    f.write(f"{date}\t{value}\n")

    # Print summary
    print(f"Filtered {len(filtered_rows)} rows written to {output_file}")

if __name__ == "__main__":
    import_filtered_cpi()

OK, now that I have *currently* all the data, I'm trying to understand the strategy.

As of close today (7/25/25), we have BRK-B at 484.07, given the WMA trendline, we have the "trend price" at 415.3, and the standard deviation over the past 20 years at 11.4%, thus our CALL target is 463 and our PUT target is 368.

That is, the CALL is DITM, and the PUT is DOTM. When looking at the entire options table for Sept 19, 25 (two-months out), I cannot find a CALL + PREMIUM that is that low, the STRIKE+PREMIUM is petty much flat at ~490 from a strike of 250 to 460 (it starts to go up slowly from there).

My understanding of the strategy is that when the stock is that high above the trendline, you are expecting the stock to revert to the trendline and thus the calls get cheaper to buy back as the price falls, at least on average over repeated covered call sales.

On the put side, the target is achievable at a strike of 365, but the time premium is essentially nothing (< 1%) Again, it seems the idea of the put is to harvest the time premium while it stays well above the trendline, but this seems like there is nothing to harvest at this level of out of the moneyness.

Am I interpreting this correctly?

Thanks, G.

Following up here, for 29-July-25, looking at options expiring on 19-Sept-25:

BRK-B at 476.56, Current trendline at 129.8753, CPI at 319.799, thus target price 415.34, stdev at 11.41% (over 20 years). With that, we have out CALL target at 462.75, and our PUT target at 367.93

There are no calls with strike + premium < 479 from a strike of 250 all the way to 700. Would the right thing here be to choose a strike of 460 or 465?

The put at 370 is a bit high, but has a time value of only 0.22/share (that is,0.06%, or annualized 0.4%). It is waaaaaay out of the money.

Would these be the right ones to sell?

Thanks, G.

Following up here, for 29-July-25, looking at options expiring on 19-Sept-25:

BRK-B at 476.56, Current trendline at 129.8753, CPI at 319.799, thus target price 415.34, stdev at 11.41% (over 20 years). With that, we have out CALL target at 462.75, and our PUT target at 367.93

There are no calls with strike + premium < 479 from a strike of 250 all the way to 700. Would the right thing here be to choose a strike of 460 or 465?

The put at 370 is a bit high, but has a time value of only 0.22/share (that is,0.06%, or annualized 0.4%). It is waaaaaay out of the money.

Would these be the right ones to sell?

Not to answer here, but to ask more questions. I haven't followed this discussion closely, but I'm interested in potentially selling cash secured puts on BRKB, at a strike price at which I'd be happy getting the stock assigned.

I don't understand your call and put target prices. The call target is below the current stock price. So you might get a high premium (21.80) from selling a covered call at that strike, but you're quite likely to have the stock called away. It seems in that case that you'd be wise to just sell the stock outright.

As for selling cash secured puts at a strike of 370, there's a very high likelihood that the puts will expire worthless. But as you note, you'd be tying up a substantial amount of cash in exchange for a measly annualized return of 0.4%. What good does that do?

It seems to me that if you think a 460 or 465 is a price at which you'd be happy to own the stock, then you'd be selling a cash secured put at that strike. The latest bid on the 465 is 7.05. That's about 1.5% of the stock price, which translates to an annualized return of about 9%, if I have it right. I think that would be a reasonable position to take, although it's an unimpressive return. BRKB options are cheap, in line with the stock's low volatility.

I hope I'm getting any of this right, and I'd be happy to stand corrected if I'm wrong.

Elan

I hope I'm getting any of this right, and I'd be happy to stand corrected if I'm wrong.

Elan, this is a Mungofitch idea from post 4021.

For all the reasons you point out, it becomes difficult to implement when the stock price is so high above its trend.

Mungofitch idea from post 4021.
...
For all the reasons you point out, it becomes difficult to implement when the stock price is so high above its trend.

I mentioned the strategy only in passing, as a more or less automated version of what I often do, so there hasn't been any deep analysis or backtesting.

But there is no problem writing an in-the-money covered call. I have done it recently. Just expect high odds that it will be exercised!

If you have reason to believe a stock is most likely to trade around (say) $100 three months from now when the option expires, and it is trading at $120, there is no problem writing a $100 call option. Obviously the odds are reasonably good that it will be assigned--if so you just sell the stock and write it again. The rate of return on the time value is not that great, but the flip side is that if the price goes to where you expect, you make the total premium, which is a big number, over $20 in this case.

For example, I wrote some Berkshire November $445 calls on July 9 when the stock price was around $477, for a premium of $47.93. Net exit price on those is about $493. A guess of "normal" stock price at that time might be around $435-460?? (My chosen strike this time was a bit lower than usual for situation-specific reasons, but should still be nicely profitable)

Jim

Hi Jim,

Correct me if I am wrong, but the underlying assumption is that the price is "mean-reverting" to the trendline based on a scaled version of book over the past ~20 years. The idea is that when it is very much above trend (as it is right now), then the stock is likely to trend towards the trendline price. As such, the future price should be less than the current one, which would make the in-the-money calls profitable.

My question becomes one of rules of thumb, when the price is so far out of trend, it seems that the trendline + standard deviation as a target is too low, and the put price likewise very far out.

Any recommendations on what to do in this case?

--G

Correct me if I am wrong, but the underlying assumption is that the price is "mean-reverting" to the trendline based on a scaled version of book over the past ~20 years. The idea is that when it is very much above trend (as it is right now), then the stock is likely to trend towards the trendline price. As such, the future price should be less than the current one, which would make the in-the-money calls profitable.

Yes, it's a pure mean reversion play. The in-the-money call will be profitable, including the in-the-money portion of its premium, if the stock goes back to its "normal" zone. But, a bit more subtly, you are going to be doing this repeatedly over time. Eventually the stock will get back to its normal zone, so (a) you will make that in-the-money part of the premium sooner or later, and (b) on every round you will be pocketing the time value in the option, which adds up. The only gotcha is that the fair value of the stock is rising over time, so the "normal" zone is rising, so your target strikes will be slowly rising too. Closing a call and replacing it with a new one could lose money if the new one has a smaller premium than the old one because fair value (and strike) have risen. This is unlikely, as value rises slowly.


My question becomes one of rules of thumb, when the price is so far out of trend, it seems that the trendline + standard deviation as a target is too low, and the put price likewise very far out.
Any recommendations on what to do in this case?

One strategy would be to always use prices far from the expected mean level.
There is a trade-off between high rate of return on the time value of the option you write, and how far it is from the current price. If one chooses options with very high or very low strike prices your chances of getting those options exercised is low, but (a) the return is so low that it's likely not worth the bother and (b) what's wrong with assignment? The strategy suggested has cash to back up the puts being written, and stock to back up the calls being written, so any time an option is exercised, celebrate! you got every last cent of the time value, and you got it early. Just sell (for the exercised puts) or buy back (for the exercised calls) the stock, open a new option position, and repeat. The system does not rely on simply writing options all the time which are going to expire worthless. There will be lots of contracts that get exercised, it's part of the normal set of trades to be done.

The +/- 1 standard deviation number was chosen a bit arbitrarily, simply to get the idea that it will be in that zone a certain percentage of the time. You could use +/- 0.7 SD, or +/0 1.5 SD, or whatever you like. Nobody really knows what the variation in pricing will be in future, and value metrics are always a bit limited in precision, so you do need a range that is of a decent


As to your specific question, "expected value plus 1SD" seeming low because the current price is already above that and has been for a while...I think it's just a matter of getting your head around the idea that you know better than the market does. Berkshire has the unusual property of trading within a fairly narrow range of valuation levels, or at least that has been the case since the credit crunch, so the underlying leap of faith is that the range in the next while won't be wildly different. If you're wrong about that you don't actually lose money, you just don't do as well.

Bearing in mind that I haven't done this as a mechanical system but simply as an "off the cuff" trade from time to time, what I do is this: if I think the likely price 3 months from now is below the current price, I generally write a call at the money, since that's where you get the most time value. But if that call is replacing one that I've lost money on (I'm rolling the position up and out), I will tend to pick a strike that is sufficiently in the money that the trade does not eat cash. This isn't being in denial about losing money on a trade, I don't care about that, but done as a regular rule it means that the original block of "in the money" premium as mentioned above is always still there to be recouped, eventually, when the stock gets back to its normal valuation zone.

FWIW, the stock has been more than one standard deviation above its smoothed value estimate for about 11.7 months now, the longest stretch since the analysis period starting Jan 2007, so writing calls has not been the best idea in this stretch. (ask me how I know!) Perhaps there has been a regime change and valuations are going to over around a new higher norm and the 20 year history is not a good guide. But I have a hunch that it's simply that Berkshire has been dragged up along with an exuberant market, and it won't last any longer than the exuberance does. Berkshire's stock-specific return has its little ups and downs, but the total return since Q1 three years ago is exactly the same as for SPY.

Sorry, kind of a rambling response.

Jim

Hi Jim,

Thank you for the response. I'm assuming that this is of some interest to the rest of the board (I can take it to email if that is not the case).

While I know that you have not implemented this mechanically, I am interested in trying to mechanically do this, even with the hope of eventually automating the entire thing so I get sent an email telling me what to do next (I hear Rayvt perking up with recommendations as to hardware and platforms).

The current rules are, assuming a 50/50 split between cash and BRK-B stock:

(1) Use current BRK book, smoothed by WMA, and scaled to match price (CPI adjusted on both) for ~20 years for the current trendline (call this "fair price"). Based on current calculation, that will be 415.36 until either CPI data adjusts or new book data comes out.

(2) Use multiplicative SD from trend over 20 years to set range for price around "fair price" above. That is currently 11.41%, so usual range should be between 462.77 and 367.95 (and BRK-B is currently high above that, at 476.17).

(3) Sell covered call backed by 50% BRK-B position at high range, Sell cash secured puts backed by 50% cash position at low range. Do these for 1-3 months into the future.

(4) If calls are exercised, rebuy stock to 50%, if puts are exercised, sell stock back to 50%.

(5) Rinse, recycle, repeat.

Above, you advanced the idea that the +/- 1 SD was just plucked out and there might be a range there that works better. Not sure we can "mound of toast" it without some idea of the time value of the options. My question comes from the original post for the calls and puts:

* Write a call option (covered call) backed by your stock, at the net exit price (strike + premium) that is one standard deviation above the current value of the trend line.
* Write a put option backed by your cash, at the net entry price (strike minus premium) that is one standard deviation below the current value of the trend line.

What I am finding is that currently on the call side, I cannot get to a net exit price that low. If I only use the time value of the option, I could do so, but using the full premium (including the intrinsic part of the call), the strike + premium is above the current close for all options no matter how far down in strike I go. Am I misunderstanding what the premium is? Note that for the puts, they all have an intrinsic value of 0.

You also state: Bearing in mind that I haven't done this as a mechanical system but simply as an "off the cuff" trade from time to time, what I do is this: if I think the likely price 3 months from now is below the current price, I generally write a call at the money, since that's where you get the most time value.

But that is missing the mechanical targets, and requires the jusdgement of likely price in 3 months. Perhaps we should use the "fair value" +/- SD to set the strikes, and the premium is what you get.

As always, your comments are appreciated.

--G

I am interested in trying to mechanically do this, even with the hope of eventually automating the entire thing so I get sent an email telling me what to do next

Of course! ;-)

Very diy.

Buy a used HP T620 or T520 or T630 thin client on ebay. Make sure you get one that includes the AC power brick/adapter, and 4GB-8GB ram, and an SSD.
like: https://www.ebay.com/itm/156460983475 or https://www.ebay.com/itm/326109395019

Or a new mini-PC with N100/N150 CPU. $100-$150. (Those are so cute I am tempted to buy one just because.)

I bought a couple T620's a while back for $35 each, incl shipping.
It takes a special power pack, but you can use a non-HP one by adding one resistor. It takes a non-standard SSD, which are available from Aliexpress pretty cheap. Add a USB pocket hard drive for more storage -- 16GB is pretty small.

I used to buy hp refurbished desktop(s) before I discovered the thin clients. You don't need much CPU power.

Install Debian Linux. Then write bash scripts to download data, do the screen calculations, and email you the results.

This is getting way off topic, so I moved it to a new thread: https://www.shrewdm.com/MB?pid=640258021

--G

OK, once more into the breach...

So the 2Q report came out, and I am a bit confused as to how to match the above numbers for book. Note that there is a thread on the BRK board that is similar, but I thought it best to post on this one.

According to my old saved notes:

Go to https://berkshirehathaway.com/reports.html, download and open the latest report.
Search for 'Berkshire Hathaway shareholders' equity' (page 3: $667,989 million)


If that is not the latest "book" then what is? I have seen several different estimates from the BRK-B board, Mungo's posts, and Yahoo Finance. Trying to figure out the "correct" way to compute it.

Thanks, G.

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