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<DIV><FONT size=2>Guy,</FONT></DIV>
<DIV> </DIV>
<DIV><FONT size=2>Sorry this took so long. Had a big computer crash due to
(bad) new RAM modules and multi-monitor setup. Complete reinstall of
everything- but it works better than ever now (whew). I use CSI Unfair
Advantage for EOD price data. Here is an essay about the various data sets
that can be created with CSI UA.</FONT></DIV>
<DIV> </DIV>
<DIV><FONT size=2></FONT></DIV>
<DIV><FONT size=2>The following files are available to download
from <A
href="http://www.frontier.net/~acw";>http://www.frontier.net/~acw</A> </FONT></DIV>
<DIV><FONT size=2>Nasdaq 100 Index: </FONT><FONT size=2>- valid months
March, June, Sept, Dec </FONT></DIV>
<DIV><FONT size=2> -F1.dat = April 15, 1996 to April 20, 2000 with
rollover at LTD - nearest active contract actual prices
(unadjusted)</FONT></DIV>
<DIV><FONT size=2> -F2.dat thru F4.dat are individual contracts
Dec 1999, March 2000, and June 2000 (I used to verify the rollover
point).</FONT></DIV>
<DIV><FONT size=2> -F5.dat = April 15, 1996 to April 20, 2000 with
rollover on the 10th day of expiration month (or the next trading day
thereafter) This avoids thin days near LTD.</FONT></DIV>
<DIV><FONT size=2></FONT> </DIV>
<DIV><FONT size=2>The ND data.zip file contains the Master, dop, and dat files
F1 thru F5 so you can just download it.</FONT></DIV>
<DIV> </DIV>
<DIV><FONT size=2>Chuck (Not connected with CSI in anyway- just a pleased
customer of CSI)</FONT></DIV>
<DIV> </DIV>
<DIV><B><FONT face=Arial><FONT size=+1>Computed Contracts: Their Meaning,
Purpose and Application</FONT></FONT></B> <BR><I>An Essay by Bob Pelletier</I>
<DIR>It is an unending study of an ever-changing subject. It is a quest that
takes commodity traders and technicians deep into the history of the markets,
brings them rushing back to the present and hurls them pensively into the
future. Technical analysis is indeed an exciting, sometimes grueling business;
one which leads its practitioners to tackle large quantities of historical data
for individual commodities. Speculators demand a workable way to view the
markets that simulates the perils, profits and pitfalls of actual trading. Those
in the know are finding that the most meaningful results can be found in the
study of "computed" contracts, which are derived from, but do not exactly mirror
actual market activity. This is a discussion of the various types of computed
contracts available to CSI data resource subscribers.
<P>Let's start with the basic fact that futures contracts are relatively short
lived. They are created on some date by traders on some exchange floor and
eventually die when their delivery dates are reached. This birth-death process
for commodity and futures contracts is an inherent characteristic that cannot be
ignored. Some commodity contracts have longer lives than others. Grain
contracts, for example, trade for a year or two, while financial markets may be
traded six to ten years into the future. In all markets, nearby contracts (those
about to expire) enjoy much heavier volume and open interest than contracts with
later expiration dates. Technical traders are wary of entering illiquid markets,
where order-execution slippage can take a significant toll on both actual
profits and efficient order execution. Liquidity factors relating to open
interest and volume, life span and distance from expiration are all-important
considerations. <BR><BR><BR>
<CENTER><B>N<SUP>th</SUP> Nearest Future Contracts</B></CENTER>
<P>Traders of the 1950s and before were comfortable viewing a concatenation of
contracts of the same commodity over time. These were created by manually
splicing together the nearest portion of successive delivery months into a
series covering ten, 20 or even 50 years. They could then simulate the practice
of trading and viewing the more active (and most liquid) period of each
successive contract to obtain a feel for trends, volatility and opportunity for
profit. Many traders still prefer viewing the markets from a nearest-contract
perspective. An advantage to this approach is that the most heavily traded
portion of every contract viewed in the concatenated series is a representation
of the actual market prices. A major disadvantage is that significant price
jumps or drops (discontinuities) occur from one contract to the next which help
to discredit, distort and diminish results.
<P>CSI's new Unfair Advantage<SUP>®</SUP> (UA) product accommodates this type of
analysis through the Nearest Future Contract choice in its Portfolio Manager.
When selecting the Nearest-Future contract option, users may select the calendar
delivery months to include. Most users wish to analyze the first nearest future,
but the 2nd, 3rd, etc. nearest future may be selected instead, to add distance
and time from delivery risk. There is also a prompt allowing users to select the
day and relative month of roll-forward. This option also adds distance from
delivery risk and clarifies when to expect one contract to roll to the next.
<P>While viewing a chart of this or any other computed series, UA users can
display the price, volume and open interest information of the computed contract
along with the name of the underlying contract in a movable window. This is done
by clicking the Price Window (crosshair) button on the tool bar and positioning
the vertical bar on any day. <BR><BR><BR>
<CENTER><B>Gann Contracts</B></CENTER>
<P>Gann enthusiasts represent another trading group that is interested in
simulating markets over a wider spectrum of contract history. This group views
the markets similarly to the nearest future proponents, with the exception that
like contracts (those with the same delivery month classification) of a
commodity are concatenated. For example, a Gann time series might hold the final
year of the June 1987 contract, followed by the final year of the June 1988
contract, followed by successive June contracts up to and including the most
current June contract that lies within 12 months of its expiration date.
<P>Unfair Advantage accommodates this type of analysis through the Gann Contract
choice in its Portfolio Manager. First the single delivery month to be used for
this Gann series is chosen. Then comes the roll date, which can be selected as
any day relative to month start. This allows for rolling on, say, the first or
tenth day of the month, or any date the user selects. The ability to gain more
distance from delivery is available for these series by opting to roll in the
calendar month prior to expiration. UA users can simply enter a 0 to roll during
the delivery month, 1 to roll one month prior to the delivery month, or even
higher numbers to roll earlier.
<P>The Gann approach may be better than the nearest-future variety because there
are fewer discontinuities. On the other hand, the one-year segments of a "Gann
file" may be too long to yield meaningful information. What may have been
learned from the distant (early) portion of each one-year segment of the time
series may not readily apply to the more volatile later portion of each
successive one-year series. As a contract approaches maturity, its
characteristics such as volatility and trading volume gradually increase until a
maximum level is reached near the end of each delivery month's contribution to
the overall series. Unfortunately, the later period of each contract is likely,
in a statistical sense, to show no resemblance to the relatively tame earlier
period. This phenomenon suggests a lack of stationarity, a statistical property
explained in the Perpetual Contract<SUP>®</SUP> data discussion below.
<CENTER><B>Perpetual Contract Data</B></CENTER>
<P>In 1970, when the computer became more popular for analysis, CSI unveiled its
trademarked Perpetual Contract data. This computed contract, very popular among
CSI subscribers, represented a time-weighted average price of the two active
contracts that lie earlier and later than a fixed number of days and months
ahead of the then-current date. This method of calculation remains popular
because it provides an accurate view of the market's characteristic waveform
over time that is "perpetual" in nature. It is similar to the forward contracts
offered by the London Metals Exchange (LME). The major drawback of the Perpetual
Contract data approach is that the contracts cannot be traded directly, and can
only be used as a guide for overall market direction. They are used to assist in
examining long-term analysis alternatives. They should not be heavily relied
upon in examining agricultural markets where different supply-and-demand
conditions may affect the distinct old and new crops. An alternative to the
standard Perpetual Contract data is the open interest-weighted Perpetual
Contract which has a near-contract view that results from all contract prices
being weighted by their respective open interest.
<P>Advocates of Perpetual Contract data series point out that these series are
more likely to exhibit statistical stationarity than, say, a Gann contract. This
is particularly true when there is a long enough period from birth to death to
change the contract's volatility over time. The concept of "stationarity" is
simple to understand. For a serially correlated time series to be stationary
(and most time series are serially correlated), the mean and variance of the
series must remain statistically constant. Another significant advantage of
Perpetual Contract data is that it offers flexibility to focus on near or far
contracts as single independent series for analysis purposes. For example, an
analyst could pair off far-forward future hogs against nearby corn (the raw
material needed to produce the hogs) to study the dependent impact of these two
commodities on each other.
<P>Unfair Advantage accommodates this type of analysis through the Perpetual
Contract choice in its Portfolio Manager, where many options give the user
flexibility to fine-tune the study. Any or all contract months may be included
in a Perpetual Contract series, but generally all active trading months (the
default response) are represented over time. The Perpetual Contract data user
must choose how many months ahead to view the market. Three months is the usual
distance, but a two-month forward series may be appropriate for commodities that
expire every month or two such as the energy products and perhaps some precious
metals. Farther-out studies can also be useful as in the above example of near
corn and far-off hogs. Perpetual Contract users have the same roll-forward
options as nearest future and Gann traders. The Perpetual Contract choice in the
Portfolio Manager is also used to affect open interest weighting on the data,
whereby no rolling is involved and weighting is based solely on speculative and
trader interest.
<CENTER></CENTER>
<CENTER><B>Back- and Forward-Adjusted Contracts</B></CENTER>
<P>More recently, traders have shown an interest in back- and forward-adjusted
contracts. Back-adjusted contracts use the actual prices of the most recent
contract with a backward correction of price discontinuities for successive
earlier active delivery months. In a forward-adjusted contract, the prices of
the current contract are changed to eliminate the gap between the current and
recently expired contract. An important aspect to remember about
forward-adjusted contracts is that current prices do not represent actual values
for today's markets. Because of the removal of contract-to-contract price jumps
and drops in both back- and forward-adjusted contracts, they appear as smooth,
blended, homogeneous price histories representing a sorted and concatenated
compilation of successive contracts over time. <BR>
<P>Starting with version 1.66 of UA, there are two back adjusters available. One
is written with a forward market viewing perspective, and the other views the
market forward in time. Both have been thoroughly tested on standard and exotic
data as part of our continuing quality assurance commitment. The results may
differ in that the roll date may be skewed by a day.</P></DIR>
<DIR>For a more complete comparison of these choices, please go to our Internet
site at www.csidata.com. To use the
alternate adjuster, click the "Generate Forward" box in the Data Manager. To use
the standard back adjuster, leave the "Generate Forward" box unchecked.
<P>The back-adjustment method of joining contracts in a series over a period of
years or decades permits the analyst to focus on the period when one might
prefer to trade the markets in actual practice. Traders often wish to
communicate their own rolling preferences so that they will not be simulating
trading situations when there is either a risk of delivery or an exposure to
highly volatile markets. To accommodate these preferences, UA lets users choose
their desired delivery months and a roll-forward date. The roll-forward date may
be relative to the start or end of the month for rolling. The option of picking
a roll date relative to the month end is useful for traders who want to avoid
risking delivery of their commodities by rolling out of a contract on or before
the first notice day, which is often calibrated relative to the end of the
month.
<P>The back-adjustment method of joining contracts in a series over a period of
years or decades permits the analyst to focus on the period when one might
prefer to trade the markets in actual practice. Traders often wish to
communicate their own rolling preferences so that they will not be simulating
trading situations when there is either a risk of delivery or an exposure to
highly volatile markets. To accommodate these preferences, UA lets users choose
their desired delivery months and a roll-forward date. The roll-forward date may
be relative to the start or end of the month for rolling. The option of picking
a roll date relative to the month end is useful for traders who want to avoid
risking delivery of their commodities by rolling out of a contract on or before
the first notice day, which is often calibrated relative to the end of the
month.
<P>Back- and forward-adjusted files can also roll when heaviest volume or open
interest shifts from one contract to the next. The switching of contracts based
on volume or open interest is always based on the previous day's data because
these values are released one day late by the commodity exchanges. For example,
a rollover based on a change in volume or open interest on Monday would not be
reflected in the data file until Tuesday. If heavy volume or open interest
switches back to an earlier contract, the current delivery month will not
change, as it is locked in to avoid confusing oscillations. Although the menu
choice of these adjusted files is called "Back-adjusted" the software can
forward-adjust the data just as easily by reversing the operation by checking
the appropriate box in the Portfolio Manager. <BR> <BR>The splicing method
(delta) is another user-defined option, which heavily impacts the adjusted
files. It refers to the data points used to calculate the back or forward
adjustment value. It closes the gap between adjacent contracts by focusing upon
the close-to-open, close-to-close or the open-to-open price differential of
successive pairs of contracts to be joined. The option of comparing the open
price of the new lead contract with the previous day's close price of the former
lead contract is an especially desirable feature because it gives the user the
opportunity to either ignore or include a real gap in contract-to-contract price
movement. <BR><BR><BR>
<CENTER><B>Negative Values in Back- and Forward-Adjusted Series</B></CENTER>
<P>An advantage of the back-adjusted approach to long-term market synthesis and
simulation is that the data observed is precisely the same as the exchange's
representation of the final contract in the concatenated series. A flaw in back
adjusting is the strong chance that an inflation-sensitive market could produce
negative price quantities into the past. The same logic allows forward-adjusted
contracts in a deflationary environment to produce negative current prices for
today. The suggestion that prices can be negative in actuality is clearly flawed
and could discredit the accuracy of such a methodology for longer-term analysis.
No one would really pay you to take 50 bars of gold away or pay you to take
thousands of pounds of cotton. This flaw demonstrates that a bias is introduced
through the removal of contract-to-contract price discontinuities.
<P>When early contract prices in a concatenated set are significantly less than
their real contract counterparts, they tend to produce a bias that in simulated
trading would heavily favor the act of buying over selling. In addition, even if
the early contract prices are not significantly different from their
current-contract counterparts, inflation could play a role in influencing buying
over selling when such a long series is introduced as representative of current
pricing norms. This phenomenon should tell you that your results may be invalid
and that applying in the present what you have learned by simulating the past
can distort your trading algorithm. Fortunately, there is a way this bias can be
removed without compromising the validity of your simulation.<BR><BR><BR>
<CENTER><B>Detrending to Remove Biases</B></CENTER>
<P>Users of back- or forward-adjusted series can, through a simple time series
analysis transformation, remove the upward or downward trend tendencies by
detrending the portion of the series that connects the final current contract
with the earlier balance of the series. This approach, which is found in all
computed contract series and cash prices of the UA data warehousing system,
removes any evidence of long-term trend for any length series so that trading
can be simulated without the danger of favoring long trades over short trades.
<BR> <BR>Two alternatives for detrending are offered. One allows
detrending up to the very end of the contract that lies before the current
contract; the other detrends up to one day short of the period end. This series
includes all of the current contract up to, but not including the very last day
on file. The latter approach may be most suitable for use with UA's Seasonal
Index study.
<P>The idea of detrending is meant to apply only to the longest possible time
period. This would be the period of time that incorporates all or virtually all
available history for the market to be studied. It wouldn't be practical to
detrend the short-to-intermediate oscillatory period. This more fruitful period
should be left in the data for the technician to study.
<P>Little or no penalty stems from the detrending process because all data is
viewed from today's perspective, with today's prices (when the entire series is
detrended). Before detrending, each price in a historical data file is assumed
to be measured by today's dollars. Given the effects of inflation over the
years, this is clearly a faulty assumption. Consider that a six-cent price move
in 1966 may have represented a limit-up or limit-down situation, whereas, the
same six-cent move today might be considered insignificant. When data is not
detrended, that very significant six-cent move of 1966 is rendered as
insignificant as a six-cent move today. Detrending, on the other hand, returns
integrity to data from the distant past by putting it back into proper
perspective. The importance of detrending is that it increases the chance that
analytical results derived from yesteryear will be relevant and comparable to
trading conditions in today's market.
<P>Don't be fooled by analysis results which suggest that the simulated
performance of a non-detrended series produces greater hindsight profits than
the same series in detrended form. Remember that this process removes a bias
that may give the false impression that buying is always better than selling.
Such results are not achievable in future trading practice. You also cannot
easily trade across contract boundaries without paying a heavy slippage and
commission tax, even if you have carefully spliced together successive
independent series. <BR><BR><BR>
<CENTER><B>Deciding Which Computed Approach to Follow</B></CENTER>
<P>There are many considerations in choosing computed contracts for analysis
and, eventually, for impacting investment decisions. Each category has some
unique value. Both the nearest future contract and Perpetual Contract data can
view the markets from early and distant delivery perspectives by focusing upon
contracts that expire either early or late with respect to any given current
date. The Perpetual Contract is the only viable approach that can focus upon a
fixed period forward in time and therefore achieve a substantial level of
statistical stationarity.
<P>From an astrological perspective, perhaps only the Gann computation is valid.
It seems to have the advantage of offering a predictably long period of time to
view a market on an annualized basis and may have some longevity benefits not
possible with nearest-future contracts. Nearest future contracts have the
advantage of focusing upon the most liquid period of a contract's life, but the
disadvantage of offering very brief periods of individual contract data.
<P>The overlooked idea of detrending of computed data is especially useful with
Unfair Advantage. Without loss of substance, one can get data into a form where
profits and losses are not subject to extremes and avoid the problem of
compounding profits and losses of the distant past into present value terms.
Portions of an entire time series can receive equal weight treatment, and the
early portions of a detrended inflationary series are progressively amplified so
that they appear in as volatile a form as the most current data.
<P>The back-adjusted contract offers the most flexibility for the user. Current
data can be supplied as it was actually traded in exchange-released form and
past data can be expressed in adjusted and detrended form. The mechanical
effects of back adjusting and price inflation can be removed, making the
detrended series an excellent source of information for seasonal analysis. A
minor disadvantage to the back- or forward-adjusted contract is the heavy
computing requirements necessary to produce the resulting series. Total
computing time is measured in seconds rather than microseconds, making it
necessary for one to wait for results.
<P>Perpetual Contract data is also a very good choice because of the statistical
stationarity issue, but many users dislike using non-tradable price
representations. As an analytical guide or tool for overall market direction and
as an auxiliary independent supporting input, it is an excellent choice.
<P>Traders and analysts may be tempted to adopt some form of hindsight market
synthesis and simulation to prove a preconceived method of trading. Each of the
alternative computed contract methods have certain advantages. In addition to
what has been argued above, the Perpetual Contract data has a very distinct
advantage over the others where intermarket analysis is involved. Because
Perpetual Contract data uses actual prices on a time-weighted forward basis, the
data in related markets operating in parallel can be significant to any
analytical exercise. Price ratios of related markets and their correlated or
associative properties are directly comparable. Back-adjusted series, on the
other hand, cannot benefit from such associative characteristics. This is so
because the inherent flaws involving contract splicing and the overwhelming
tendency for back-adjusted series to report negative readings all but destroy
the relative characteristics of one market with respect to another. Gann and
nearest future contracts can be used much like Perpetual Contract data, however,
because of inherent price discontinuities, the results are not as consistent for
longer-term analysis.
<P>This message is presented to guide you in your study of the commodity markets
and to help you understand the ever-changing subject at hand. It is not only for
those who are contemplating building trading systems based on computed contract
series, but also for those whose trading systems have been derived from such
approaches. Each type of computed contract discussed here can add some
visibility to market analysis. It is important to consider both the strengths
and possible weaknesses inherent in these methods to maximize profits and
preserve capital in actual trading.
<P>
<HR width="100%">
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<DIV><FONT size=2>----- Original Message ----- </FONT>
<DIV><FONT size=2>From: Guy Tann <<A
href="mailto:grt@xxxxxxxxxxxx";>grt@xxxxxxxxxxxx</A>></FONT></DIV>
<DIV><FONT size=2>To: <<A
href="mailto:metastock@xxxxxxxxxxxxx";>metastock@xxxxxxxxxxxxx</A>></FONT></DIV>
<DIV><FONT size=2>Sent: Wednesday, April 12, 2000 6:33 PM</FONT></DIV>
<DIV><FONT size=2>Subject: RE: NASDAQ futures continuous
contract</FONT></DIV></DIV>
<DIV><BR></DIV><FONT size=2>> Chuck,<BR>> <BR>> I already have a couple
of sample contracts, but I do have a question and a<BR>> request.<BR>>
<BR>> First, what is back adjusted or adjusted? I hate to show my
ignorance, but<BR>> I have absolutely no idea what this means. For our
continuous contracts we<BR>> have always used the current month to the end
and then switch to the next<BR>> month. With our modified contracts
(used for other commodities) we switch<BR>> months when the next active
month's volume exceeds the current (or delivery<BR>> month). For other
commodities, we ignore all of the minor months and only<BR>> use the major,
active months.<BR>> <BR>> If you could put a continuous contract together
for me rolling over to the<BR>> next month when the current month dies, I
would appreciate it. That will<BR>> give us 3 different "continuous"
contracts to look at.<BR>> <BR>> Thanks,<BR>> <BR>> Guy<BR>>
<BR>> <BR>> -----Original Message-----<BR>> From: <A
href="mailto:owner-metastock@xxxxxxxxxxxxx";>owner-metastock@xxxxxxxxxxxxx</A>
[<A
href="mailto:owner-metastock@xxxxxxxxxxxxx";>mailto:owner-metastock@xxxxxxxxxxxxx</A>]On<BR>>
Behalf Of Chuck Wemlinger<BR>> Sent: Wednesday, April 12, 2000 6:49
AM<BR>> To: <A
href="mailto:metastock@xxxxxxxxxxxxx";>metastock@xxxxxxxxxxxxx</A><BR>>
Subject: Re: NASDAQ futures continuous contract<BR>> <BR>> Guy,<BR>>
<BR>> I can build a continous contract based on Nth nearest and rolling
parameters<BR>> such as Vol, OI, Vol+OI, or specific time of month. It
can be unadjusted or<BR>> adjusted. What would you like?<BR>>
<BR>> Chuck Wemlinger<BR>> <BR>> ----- Original Message -----<BR>>
From: "Guy Tann" <<A
href="mailto:grt@xxxxxxxxxxxx";>grt@xxxxxxxxxxxx</A>><BR>> To: "Metastock
User Group" <<A
href="mailto:metastock-list@xxxxxxxxxxxxx";>metastock-list@xxxxxxxxxxxxx</A>><BR>>
Sent: Sunday, April 09, 2000 16:05<BR>> Subject: NASDAQ futures continuous
contract<BR>> <BR>> <BR>> > List,<BR>> ><BR>> > Does
anyone have a MS or text format NASDAQ continuous futures contract<BR>>
that<BR>> > I could get a copy of? We're going to try to analyze it
to see if our<BR>> > system might work with it as well. You can send
it via an attachment via<BR>> > email as long as you include a note as to
what it is.<BR>> ><BR>> > TIA<BR>> ><BR>> > Guy<BR>>
><BR>> ><BR>> ><BR>> ><BR>> <BR>>
</FONT></BODY></HTML>
</x-html>From ???@??? Tue Apr 25 06:09:02 2000
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From: "Guy Tann" <grt@xxxxxxxxxxxx>
To: "Metastock User Group" <metastock-list@xxxxxxxxxxxxx>
Subject: Another Day, Another Trade - Going Short!
Date: Mon, 24 Apr 2000 23:15:49 -0700
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Status:
List,
Rather than post our internal family newsletter and our summary spreadsheet,
I'm just posting our latest signal.
We're going short in the morning. We are selling all of our stocks and
shorting the SPY, DIA and QQQ. Use this information at your own risk.
This is just what we're doing.
Our S&P trading system, since October 11, 1999 (the date when we started our
little family newsletter to publicly post our trades and actual results, not
when we started trading it) is running 81.82% correct with 9 winners and 2
losers, in the last 6 months. Total number of points of profitability,
trading 1 e-mini S&P contract, is 400.20. At $50 a point, that's $20,010
net profit before approximately $300 fees and commissions. Margin for
trading 1 e-mini S&P contract is $4,688. We maintain much more than that in
order to satisfy our money management requirements. These P&L numbers are
before our fills tomorrow morning. If this trade remains profitable
(according to GLOBEX) we'll be 83.33% profitable.
Guy
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