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Hi Jim and others who have written
This is an intersting "ATR stops for your portfolio.xls" ... with lots of
VBA code both
in the .xls and as .txt ... .
http://content.communities.msn.com/isapi/fetch.dll?action=get_message&ID_Com
munity=MoneyCentralSuperModels&ID_Message=1111&ID_Last=0&Dir=0&ID_Topic=0&La
stModified=942056506000
From: Jon_Markman
Sent: 10/28/99 7:36 pm
Attachments: SuperModels_PRQ.txt (1.7KB), ATR_v3b.txt (9KB)
From: Jon_Markman Reply 8 of 60 Add a Reply...
Sent: 11/8/99 2:21 am
Attachments: ATR Stops_Portfolio_v3.3.xls (968KB)
From: Jon_Markman Reply 22 of 60 Add a Reply...
Sent: 11/19/99 5:44 pm
Attachments: PRQ MonthsAndWeeks v1_4.xls (263.5KB)
here ist the new PRQ Monthly and Weekly analysis macro ....
====================
To others ... seasonality in Gitanshu's workbooks is not the same as
seasonally adjusted. These are two different concepts. Lets just re-program
these for our tradeables and worry about the other stuff later. Usually the
X-11 processes are used for seasonally adjusted time series data. The Excel
3-D ribbon chart usually has a vertical ordinal scale. A tradable with no
seasonality will have a divisor of 1.00. Seasonally-weak values have
divisors of less than 1.00, and seasonally-strong numbers have values
greater than 1.00.
Best regards
Walter
----- Original Message -----
From: "Jim Greening" <jimginva@xxxxxxxx>
To: <metastock@xxxxxxxxxxxxx>
Sent: Wednesday, December 29, 1999 8:45 PM
Subject: Re: Heat Map explained
| Gitanshu,
| Great work. I've been thinking along those lines myself and I'm glad
| someone has beat me to it and has already done all the leg work. I'm
going
| to think about how to incorporate your findings in the first part of my
| trading strategy which is to pick the right sectors. In the past, I've
just
| waited for a sector to begin to trend strong and then jump on. If the
| seasonality holds true, it will have the great advantage of being able to
| jump on early at lower prices before the trend starts. Keep up the good
| work.
| Once again, thanks for sharing.
|
| JimG
|
| ----- Original Message -----
| From: "Gitanshu Buch" <OnWingsOfEagles@xxxxxxxxxxxxx>
| To: <metastock@xxxxxxxxxxxxx>
| Cc: <realtraders@xxxxxxxxxxxxxxx>
| Sent: Monday, December 27, 1999 7:46 PM
| Subject: Heat Map explained
|
|
| > Before this gets overblown into some needless controversy - I am
| explaining
| > what this spreadsheet is all about right here.
| >
| > The reasons this spreadsheet was not uploaded to RT/Metastock before
were
| >
| > - simply because I thought nobody here would be interested, hence it
was
| > shared with a few close friends before the public release @ Microsoft
| > MoneyCentral.
| >
| > - I felt kinda embarrassed tooting my own horn.
| >
| > It seems to me that the latter was a needless concern. Grandma phrases
| like
| > God helps those who help themselves etc etc come to mind.
| >
| > Here is how this started:
| >
| > Jon Markman, an author (ex LA Times, now Microsoft, and responsible for
a
| > bestseller entitled Online Investing) wrote an article publishing some
of
| > his research on stock-specific seasonality.
| >
| > This research was astounding to me - in its simplicity, and
verifiability.
| >
| > Here is that article:
| > http://moneycentral.msn.com/articles/invest/models/4804.asp
| >
| > Independently, and unrelated to the above, I have observed and traded
| > seasonal patterns successfully in the energy derivatives complex. My
work
| > has been visual converted to Excel, clumsy, but gratifying since it has
| been
| > profitable.
| >
| > I got to know him, and we started exchanging ideas. One thing led to the
| > other, I did the index research, put it on a user-friendly spreadsheet,
| and
| > shared it with Jon. He got excited, and wrote it up in an article at
their
| > website.
| >
| > This started out as a discovery. It is aquiring a life of its own -
| perhaps
| > the way of the world in internet time - for that has since resulted in
| about
| > 200 emails in the past 3 weeks from strangers seeking investment advice,
a
| > book offer from someone in London, and assorted other flora and fauna.
| >
| > Now.
| >
| > Do I care it gets mass-distributed? Heck, no. This wouldn't be in public
| > domain otherwise.
| >
| > The spreadsheet focusses on indices that have liquid, tradeable options
| > because that sphere is where I trade the funds I manage and that is
where
| I
| > can find direct measurable portfolio impact.
| >
| > However, that work has now expanded to include Fidelity Select Sector
| Funds,
| > and I am happy to share that work here if anybody is interested. Fund
data
| > is currently inaccurately adjusted for dividends/distributions and
being
| > cross-checked - but the trends exist and the trends are tradeable and I
| > intend to trade them with real money come Jan 2000.
| >
| > The following is the text of what was sent to Jon before he wrote it up
in
| > his article - which is at this url.
| > http://moneycentral.msn.com/articles/invest/models/4950.asp
| >
| > Microsoft owns all the copyrights for all urls referenced in this space.
| >
| > Finally, and once again - I mean no disrespect towards Mark the person -
| my
| > previous email was towards the act - which looked and felt like
plagarism
| in
| > the crude way the email landed in my face - I believe I asked for basic
| > decency out of sheer indignation.
| >
| > ====
| > The spreadsheet as explained:
| >
| > Sector picking (through Sector Mutual Funds or their tracking sector
| > stocks) - beat S&P 500 Indexing by a factor of 10 to 1 since 1994 using
NO
| > LEVERAGE. The results are remarkably better if individual stocks are
| chosen.
| >
| > Methodology:
| >
| > PRQs were tested across 150 companies in different industry sectors,
just
| to
| > establish the validity of the concept.
| >
| > Research then extended to 31 industry sector indices, for as far back as
| > sector index data could be found.
| >
| > This spreadsheet is the result of the industry sector research. It
| provides
| > a "Heat Map" for sector rotation that seems to evolve in the market.
| >
| > The Heat Map is set about as follows:
| >
| > Each column has data for a single index across the 12 months.
| >
| > Each row has data for a single month, across the page index.
| >
| > Green cells are "Best Months to Buy these sectors"
| >
| > Red cells are "Worst Months to Buy these sectors; conversely, best
months
| to
| > Short them".
| >
| > Blue cells are Best of Breed for the month, across all sectors
researched
| so
| > far.
| >
| > A summary of the best 3 sector returns for each month is listed in the
| > initial 3 gray columns, and the Benchmark index is S&P 500.
| >
| > To use this to its desired initial screening potential or even as a
| > standalone strategy, the reader would:
| >
| > Buy the best performing index for Dec at the Close on the last trading
day
| > of Nov.
| >
| > Rotate into the next month in similar fashion on the last trading day in
| > Dec.
| >
| > Assuming no leverage or transaction costs, the trader outperforms SnP
500
| > Indexing by the average factor listed in Row 21. (An outperform reading
of
| 1
| > equals the benchmark, of 0 under-performs, and of 10 beats the benchmark
| 10
| > to 1).
| >
| > The trader would further research the index components' chart patterns
and
| > PRQs for individual stock selection. This component list (and where
given,
| > weight within the index) is hyperlinked with the Index name in Row 2.
Just
| > have an internet connection handy.
| >
| > The work-in-progress is as follows:
| >
| > I am PRQ'ing sector components, and then doing the Heat Map for each
stock
| > in that sector at Month Level.
| >
| > The Month level will then be imploded to explore the best weeks in the
| month
| > to hold that stock, or its options. Given that this data captures an
| entire
| > month while options expire on the third Friday of each month, there will
| be
| > some fine-tuning. But the core concept seems to be ready to be set in
| > stone - the findings are really exciting:
| >
| > Some Findings:
| >
| > A/ Forest and Paper Products is the best performing sector in April of
| every
| > year. FPP appreciates better than SPX by a factor of 10. Better than
| > Internets, Semis, Banks, you name it. This is consistent with Jon's
| original
| > PRQ article and his experience with Dow 30 component Cyclicals.
| >
| > B/ Semiconductors have a tendency to outperform the rest of the world
and
| > their own annual buy-and-hold results in the January, April, and July of
| > each year - notably, these are the first months in every quarter.
| >
| > C/ Networking stocks are best bought in April and held through July.
This
| > beats the SPX by a factor of 9 to 1 during the same period.
| >
| > D/ While September is billed to be the worst month for the market
(true),
| > the sectors studied actually end up losing the most of their value in
| > August. This leads me to believe that the September under-performance
| > catches up with the not-too-favored stocks that make up the general
index,
| > while the real damage in the market's YTD faves happens in August.
| >
| > E/ Contrary to current popular belief, Oil prices, Oil sector stocks and
| > Airline stocks can, and do rally together - the spreadsheet will show
that
| > these sectors simultaneously outperform the rest of the world (including
| > Internet stocks) in March of each year.
| >
| > F/ Airlines again outperform the universe in Oct and Nov each year, but
| Oil
| > sector stocks curiously decline in this period.
| >
| > G/ While on Oil: This is the classic Anti-January effect sector. The
| sector
| > plunges >5% on average every year, (the worst performer of the universe)
| > making it a prime candidate for shorting during the month.
| >
| > H/ The best January Effect halo exists over Brokers, Semiconductors, and
| > Internets. While other sectors do find investor enthusiasm, it appears
| that
| > following the crowd while ignoring these 3 sectors obligate you to
| > mediocrity, for you give up >4 to 1 returns in a generally strong
market.
| >
| > I/ There is something to be said about being defensive. Drug related
| > sectors, for example, typically outperform the benchmark during the
| market's
| > weak period in Aug-Sep. But within the drug sector, the more momentum
| driven
| > Biotech sector is better owned than the Mercks of the world.
| >
| > Next steps for me:
| >
| > Sector-Component Level seasonality
| > Week-of-month seasonality at Sector and Component Level.
| > Trading Instrument choice and Trading Plan finalization.
| > Since I now have a general heat map, I will start with sectors that
enjoy
| > their best seasonality in Dec and Jan. If you are interested, I will
send
| > these spreadsheets over.
| >
| > Weaknesses/Shortcomings noticed so far:
| >
| > a. Data inconsistency: Index measurements start from different dates in
| > history, a little skew may exist.
| > b Multiple index participation: Lots of stocks appear in multiple index
| > standings.
| > c. Unknown reasons for some stock exclusions: For eg, the SnP Bank Index
| > (BIX) does not have Citibank as a component. Go figure.
| > d. Bad data on MSN/CSI database. Can't use it unless manually washed.
| > e. From a trader's perspective, given today's ATR, a lot of these
numbers
| > seem miniscule - a whole month's performance can be reached within a
week
| or
| > less.
| >
| > Comments welcome.
| >
| > Gitanshu
| >
| >
|
|
|