EdgeWare FastBreak Pro Version 6.5 - Manual (Page 66)

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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. Note: As you will see, many of these studies were performed
many years ago. That doesn’t invalidate the concepts and ideas for you to consider.
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
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).