EdgeWare FastBreak Pro Version 5 - Manual (Page 58)

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10.0 Suggestions for Building Better Systems
The optimization parameter defaults in FastBreak Pro will give you good results. In this
chapter we show you the sensitivity to some of the optimization options and give you
ideas for doing your own studies. We also provide results from our studies that may help
you build better systems.
General Suggestions
• Select only one ranking method per optimization run. Our personal order of
preference for ranking methods is: MAM, UPI, and Rank.
• Choose “reasonable” trading system performance goals. For example, do not try for a
MDD of 5% trading stocks. This will result in an unrealistic trading system with far
too many stop parameters.
• Fewer stops and buy filters are usually better. Try using the Stop Penalty option if
you find more than three or four stop and filter types being selected. This may reduce
the IS return slightly but improve the OS return.
• Choose trading family members wisely. FastTrack has hundreds of funds and stocks.
Many of these funds/stocks perform well over long periods of time while others
under-perform. Try to choose from the first group.
• Do not expect the Optimize Family option to do all your screening work. Using this
option increases the number of possible system combinations significantly. This
option should be used to fine tune your trading family.
• The Rydex family of funds is an example of very “trader friendly” funds, and we
have had success developing trading systems for this family, but more effort than
usual is involved. The major problem with developing Rydex systems is the lack of
historical data needed to perform long-term optimization and testing. The Rydex
index funds, i.e., Nova, Ursa, and OTC, can be simulated back to 9/1/1988 using the
capability in FastGraph. We have used the equivalent sector funds from Fidelity as
substitutes for system development. These methods result in excellent IS and OS
results, however, when the actual Rydex data is substituted back into the trading
system for the simulated/Fidelity data, the results can be substantially less. This
appears due to the fact that, although the Fidelity and Rydex sectors funds have high
correlation, the price performance between the funds can be substantially different
over long time periods. Our most successful systems have been developed by
limiting the number of trades and trying and capture the major moves in the sector
and index funds (as opposed to trying to capture smaller moves that are allowed with
Rydex’s generous trading rules).