Small Portfolio
|
XLF & IAU
|
17.10%
|
|
Sector
|
XLF
|
23.67%
|
|
Secular
|
IAU
|
10.53%
|
|
|
|
|
|
Large Portfolio
|
Date
|
Return
|
Days
|
RIMM
|
7/16/2012
|
65.66%
|
147
|
SEAC
|
9/25/2012
|
26.07%
|
76
|
CAJ
|
9/25/2012
|
6.37%
|
76
|
DDAIF
|
9/25/2012
|
-2.99%
|
76
|
CFI
|
10/31/2012
|
14.50%
|
40
|
MO
|
11/8/2012
|
6.59%
|
32
|
EL
|
11/12/2012
|
5.53%
|
28
|
BOKF
|
11/19/2012
|
-0.34%
|
21
|
RE
|
11/26/2012
|
3.89%
|
14
|
GLW
|
12/3/2012
|
2.53%
|
7
|
|
|
|
|
S&P
|
Annualized
|
3.51%
|
|
Small Portfolio
|
Annualized
|
10.86%
|
|
Sector Model
|
Annualized
|
14.89%
|
|
Large Portfolio
|
Annualized
|
26.34%
|
|
*Returns on Friday, 12/7/2012.
**No rotation today (see below).
The other day I wrote something to a friend about compound
returns that I quickly realized was wrong.
The point I was trying to make was essentially correct, but
the number I gave for a compounded annualized return was wrong, and it reminded
me that my model still used a placeholder linear equation that only loosely
calculated an annualized rate of return, and not a more accurate exponential
equation.
The good news is that the correction bumped the annualized
return rate on my Large Portfolio up by a fraction of a percentage. The bad news was that my basic model may have
been using the wrong rotation period.
Sure enough, the correct rotation rate on current data was
88 days, instead of 67 days.
Oh well.
My only fear with all of this is that I may discover one day
that the model only works with bad math…
…we’ll find out…
Geeze, the things that keep me awake on a Friday night!
Come Saturday night I was plugging the new equations in all
their proper places and realized that it would adjust my adaptive fundamental
filter as well.
Come Sunday night I realized that I had no time to write a
blog entry, but no need to do so, since the next rotation shouldn’t happen
before Wednesday.
Come Monday, it’ll be alright… no wait, that’s a song…
Come Monday, I took a look at my revised rotation periods
and fundamental filters and realized they make a lot more sense than they did
last week.
So why all the fuss?
The fuss is about the difference between gross returns and net returns. Gross returns
are what you think you have before trading costs and taxes leave you holding a
shredded net.
Here’s how it works:
The blue line is the S&P 500 index from 1950 to the
present. It’s what you would have in
your account if you invested in the full index and held it for 62 years.
The red line is what you would get after you cashed out.
The green line is what you would get if you rotated your
stocks once a year and paid long term capital gains each year.
Short term capital gains is even worse:
Instead of 1413.94, you’d have 1204.35 if you cashed out
today and paid taxes (Bush rates), or 1078.59 if you cashed out in January
(Obama rates). But if you had been
actively trading the entire time you wouldn’t even have that. You’d have 800.43 if you traded once every
367 days (paying long term capital gains each year), or 355.28 if you rotated
once every 364 days (paying short term capital gains each year).
355.28??????????????
Yep. Uncle Sam would
have the rest, you patriot.
Whatever you pay in taxes in 1951 you can’t re-invest in
1952, and so on. The taxes keep killing
your base and you can’t grow your retirement income at nearly the rate you need
to survive.
Back to the only Buffet rule that we should care about: the more you trade, the less you have.
So why trade at all?
Short answer is that most people shouldn’t.
No, really. They
shouldn’t trade at all. They should
deposit it into SPY and walk away and NEVER look at the account. This compounding problem is also the reason
that the vast majority of mutual funds underperform the market averages – they trade
too much. Statistically, men trade more
often than women do, and women make better returns than men do. It’s an insidious cycle in which you work
harder and harder for less and less, when you would have done far better by doing
nothing at all.
For 95% of investors, SPY is your friend.
Still, being a male of the species I’m doomed to trade more
often, so I might as well make the best of it.
Hence the periodicity chart for my model to determine the optimal
holding period after trading costs and taxes are accounted for:
The original fundamental filter for the model was based on
the work of Joel Greenblatt, which is designed for a one year holding period
(that spike you see at the one year mark).
It’s not designed for shorter holding periods, and I adjusted my model
to use a more complex fundamental filter designed after the work of Benjamin
Graham (that second top shows a clear outperformance over Greenblatt).
Finally, I created a self-adaptive fundamental filter that
evolves with, and for, the Mousetrap.
That’s the third spike on the left hand side.
The blue line is the net return for any given holding period
on my model, after you remove taxes and trading costs.
The red line is the after tax net you would have from SPY
(assuming you always held longer than a year and only cashed out with long term
rates).
The green line is the difference – and the highest point on
the green line is the optimal holding period for my model.
Of course, as the fundamentals self-adjust to the holding
period, the holding period will also self-adjust to the fundamentals, until
they finally reach a long term equilibrium.
Incidentally, that red line should eventually become flat. It only dips at the beginning because I
started the model on 5/31/2011, just before a nasty drop in the S&P. That drop will be diluted as more trades and
more data are entered.
And, as the rules change in Washington D.C. the chart will
change as well. I can’t force them to
make good decisions, but I can certainly try to navigate around the chaos they
create.
Tim
