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been found useful by many market technicians For example, Ruggiero (October 1996) contends that adaptive breakout systems that make use of the maximum entropy method (MEM) of cycle analysis perform better than those that do not Maximum entropy is an elegant and efficient way to determine cyclic activity in a time series, Its particular strength is its ability to detect sharp spectral features with small amounts of data, a desirable characteristic when it comes to analyzing market cycles The technique has been extensively studied, and implementations using maximum entropy have become polished relative to appropriate preprocessing and postprocessing of the data, as required when using that algorithm A number of problems, however, exist with the maximum entropy method, as well as with many other mathematical methods for determining cycles MEM, for example, is somewhat finicky.

The Internet is gradually replacing the customer service rep. Instead of paying for the cost of a toll-free call and the salary of a customer service rep who reads information off a computer screen, companies are learning that their customers can look at that same screen directly on the Internet and get the answers themselves. What s more, customers like it better. What is the saving produced by elding a call on the Web instead of on the phone Between $2 and $7 per call. Banks are discovering the saving from the Internet. Transactions on the phone with a live operator cost banks $2 or more. Those on the Web cost about a penny each. The big savings, however, come from inviting customers to come into your company to read the same screens that your employees read. Customers become part of your company family. This is real relationship marketing. Every business-to-business company in America (or in the world, for that matter) can pro t by opening up its internal company data and

It can be extremely sensitive to small changes in the data or in such parameters as the number of poles and the look-back period In addition, the price data must not only be de-trended or differenced, but also be passed through a low-pass filter for smoothing before the data can be handed to the maximum entropy algorithm; the algorithm does not work very well on noisy, raw data The problem with passing the data through a filter, prior to the maximum entropy cycle extraction, is that lag and phase shifts are induced Consequently, extrapolations of the cycles detected can be incorrect in terms of phase and timing unless additional analyses are employed DETECTING CYCLES USING FILTER BANKS For a long time, we have been seeking a method other than maximum entropy to detect and extract useful information about cycles.

making them available to customers on the Web. There are three reasons for this: 1. The Web site will probably pay for itself in savings on toll-free calls and operator time. 2. It may increase sales to new prospects (although that is not a sure thing). 3. It provides a way to recognize and build relationships with customers that will improve loyalty and retention. Who is doing this Customers use Dell Computer s Web site to check their order status 50,000 times per week. The same calls to Dell s customer service reps would cost Dell $200,000 per week. Dell also saves several million dollars per year by encouraging 200,000 customers per week to make their troubleshooting inquiries through the Web.

Besides avoiding some of the problems associated with maximum entropy, the use of a novel approach was also a goal: When dealing with the markets, techniques that are novel sometimes work better simply because they are different from methods used by other traders One such approach to detecting cycles uses banks of specially designed band-pass filters This is a method encountered in electronics engineering, where filter banks are often used for spectral analysis The use of a filter bank approach allows the bandwidth, and other filter characteristics, to be tailored, along with the overlap between successive filters in the bank This technique helps yield an effective, adaptive response to the markets A study we conducted using filter banks to explore market cycles produced profitable results (Katz and McCormick, May 1997).