In This Issue
Copyright (c) 1998 Commodity Systems Inc. (CSI). All rights are reserved.
Proportional Back Adjusting and its Comparative Advantages.
When we first announced our Unfair Advantage® software, including plans to allow the creation of custom-defined historical series, we were inundated with requests to incorporate a back-adjuster for concatenating historical commodity contracts of a given commodity into the past. In the many months since we introduced the first back-adjust option, some cumbersome issues have appeared. Today we will discuss the various obstacles that must be negotiated in dealing with back-adjusted data and will explore a new UA procedure that will solve many perceived problems.
Chief among the difficulties with back-adjusted time series is the fact that commodity prices, particularly those of commodities that have traded for many years, sometimes reach significantly into negative territory when back-adjusted. The negative values are most prevalent when using the industry standard back-adjustment process for studying the futures markets. This approach, which involves splicing many commodity contracts together in backward chronological sequence, produces a homogeneous series, which reveals a non-emotional, mechanical attitude about trading and the development of trading systems. The back-adjustment approach allows the most current contract in a price series to always represent the reality of the near past. Successively further distant contracts are spliced by matching the behavior of the last couple of days of one contract with the behavior of the next. This splicing procedure matches up opens, closes or a combination of both to achieve as smooth a transition as possible on roll-forward day. Rules can be formulated to time the rolling with respect to a date relative to the start or end of the month, or with respect to the relative positioning of volume, open interest, or a combination of the two.
The hope, in most applications, is to roll forward when trading in the old contract wanes in comparison to the emerging and strengthening new contract. However, the tendency of the resulting back-adjusted data to "go negative" has forced us to make adjustments in policies regarding back-adjustment series. Some customers have demanded we elevate the series out of negative territory by adding in a constant, or that we forward-adjust the series making future prices reach for the sky. Others have preferred the idea of detrending the history by placing all history into relative terms of current-day dollars. All of these ideas and many more, including the production of Perpetual Contract® Data, nearest future contracts and Gann contracts have been built into Unfair Advantage for the convenience of our customers.
The idea behind each computed time series is to make disparate commodity contracts appear much like the longer-term history of a stock. The usual intent, of course, is to introduce a long-term testing platform for simulating and synthesizing trading system performance over time by applying a proposed trading procedure to the historical past.
Unfair Advantage's newest enhancement will, at your option, proportionately adjust the history of a commodity by percentage or ratio terms, in addition to splicing contracts by adding or subtracting their relative differences into the past. As it turns out, the proportional adjust idea may be a very sensible way to view the past. Proportionally adjusted series prepared through ratio multiplications cannot go negative, so there is never a need to elevate a series out of negative territory. Contracts are joined by increasing or decreasing successively further distant contracts by a percentage to raise or lower the entire history by the same proportion.
Because the proportional adjustment yields a much milder descending slope of long-term prices into the past, there is much less long-side trading bias that can be captured from the data. An unbiased result that offers realism should be much preferred over a highly profitable and unbelievable result that holds more contributions from inflation than from any perceived trading style or expertise.
The idea of proportionally adjusted contracts requires applying the percentage change in price of the earlier contract with respect to the price of the current (or later) contract. For example, say your series is rolling backward through the quarterly contracts of December, September, June and March of a given calendar year for your commodity. If the price of the December contract were 100 and the price of September were 95 on roll- backward day, the traditional back-adjuster would elevate all prices for the September contract by five. This would be maintained as a delta of five to be added to all past data, beginning with the September contract, on the day before rolling from the December contract.
In a proportionately adjusted series, the fixed delta of five would represent a factor of 5/100 or 105% of the September price for all data in the September contract. This process would repeat at the same percentage for every contract boundary until the series ended.
Because the proportional adjustment yields a somewhat milder descending slope of long-term prices into the past, there is much less long-side trading bias that can be captured from the data. An unbiased result that offers realism should be much preferred over a highly profitable and unbelievable result that holds more contributions from inflation than from any perceived trading style or expertise.
Please consider the two coffee charts to compare the two methods (CHARTS NOT AVAILABLE ON-LINE). The back-adjusted coffee chart moves negative into the past and holds a slightly ascending (inflationary) slope. By contrast, the proportionally adjusted coffee chart shows almost no indication of inflationary effects, yet it represents the entire history in an unbiased form. As with every computed contract in the UA inventory, there is also the capability to remove the apparent effects of inflation by detrending the resulting series before applying a trading algorithm.
Trading systems players are accustomed to analyzing one market at a time with the undeclared idea that each market stands on its own and is relatively independent from all others. This may not be each trader's intent or belief, but for the sake of convenience, we may go along with things that don't make practical sense.
Markets may be better used in concert with others. What happens in one grain may affect what is going on in another grain or (because energy is such an important element in the efficiency of farming) an energy market. Those who would trade off one market with another should know about simple ratios and what they can suggest. Proportional series, because of the reduced sensitivity to distortion, and Perpetual Contract Data, because of its time-based averaging design, are examples of workable series that may offer the ability to compare one market with another over very long periods. There are many things to consider when choosing the computed contract that is most appropriate for your needs. The UA manual, itself, goes far in showing you how to make an intelligent selection in the essay, "Computed Contracts, Their Meaning Purpose and Application."
Unfair Advantage has been well received and has a growing following, partly because of its massive database and partly because of its data-crunching abilities. We continue to make headway in refining this tool to meet and anticipate the needs of our customers. We will continue to use this journal to keep you apprised of software enhancements and capabilities. All it takes is a little study to uncover the opportunities offered through the UA database. Markets data from all over the world is there and it just takes the spark of an idea to put it to good use.