Topics for October
Copyright (c) 1999 Commodity Systems Inc. (CSI). All rights are reserved.
Topics discussed in this month's journal.
magazine's September '99 issue featured a cover story about the accuracy of the
top end-of-day data providers for investors. We are pleased to report that CSI
was the undeniable champion in terms of data accuracy and in other ways that
might surprise you. Many of you may have seen the article in Futures magazine
written by Sheldon Knight of K-Data Inc. The following editorial notes are
intended to reinforce and clarify the importance of Mr. Knight's study.
On Data Accuracy
study, there were collectively 1,203 errors and omissions noted from among the
ten firms tested. The bottom line for CSI was the committal of 27 errors and
omissions in the 1,506-day test. Dividing the remaining errors among the nine
competing firms, we find that they had an average of 131 errors each in the
same time period, which demonstrates an error rate of the average CSI
competitor that is 385% higher than CSI's.
On Data Presentation
This was briefly noted in the Sheldon Knight study, but it deserves additional comment. Data presentation refers to the handling of after-the-close settlements that can result in exchanges quoting settlement prices that are outside the day's trading range (above the high or below the low). It is common (but not necessarily correct) for summary day-end data vending firms to expand the high-low range to accommodate the assigned settlement price, even though settlement prices do not necessarily represent prices where actual trading took place. CSI delivers actual trading statistics to customers and gives the option of presenting data 1) in actual form, based on exchange statistics, 2) with highs and lows expanded to include the settlement, or 3) with the settlement price modified so that it lies within the actual highs and lows. According to the article, only CSI has recorded the historical statistics on all markets so that they can be presented in any one of these ways. It is clear that CSI's competitors have forever lost the ability to present an unaltered historical record.
On Analytical Validity
study clearly demonstrates that technical analysis requires accurate data. In
the study, S&P 500 data from CSI, Omega Research, and Bridge were used on
the same simple breakout system with strikingly different results. The profit
scenario varied from 20% to much more than 100% over the full period of study.
This should offer substantial proof that the derived effects of a flawed
historical database can lead to a useless result and a wasted effort. This is
because parameter settings determined from flawed data cannot be expected to
work with the same efficiency when they are applied to actual (unflawed) market
activity. Unfair Advantage's software and database are designed so that every
user is equipped with exactly the same data set at all times, forcing any
common analytical tool that is derived from past information to produce
equivalent results on different machines.
On Vendor Compatibility
Several of the data vendors included in the study are either allied with or directly tied to very expensive analysis programs, but they are not necessarily the required data sources. Although CSI is explicitly excluded from the data download screens and menus of most of those programs, discriminating users of the industry's most powerful software tools still come to CSI for data. They know that it is pure folly to accept the suggestion that an average data firm can deliver the accuracy needed to create an exceptional trading system. Now that the importance of data accuracy has been revealed, perhaps even more traders will come directly to CSI, whether or not their software producer steers them in that direction. Software companies with whom CSI data products are compatible include: Equis Int'l (MetaStock®), Omega Research, Windows on Wall Street, ProfiTaker and many others.
Putting it All Together
It should be
mentioned that the errors measured in the Sheldon Knight study were discovered
in hindsight, based upon each company's one-time historical submission. An even
more telling result might have emerged had the study been conducted on an
ongoing basis by observing each contributor's performance one day at a time
over an extended period. With an ongoing study, the reader could have a better
understanding of each company's performance when it means the most: immediately
after each day's database update is posted. This way, each firm's timing of
delivery, diligence in avoiding omissions, and ability to stay on top of
information gathering in spite of unpredictable obstacles could be studied.