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