EdgeWare FastBreak Pro Version 6.5 - Manual (Page 84)

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Appendix A -- Technical Discussion
What are Genetic Algorithms?
Genetic Algorithms are a mathematical method used to solve hard optimization problems.
The method simulates the biological processes of “evolution”, “natural selection” and
“survival of the fittest.” Biological terminology is used to describe the process:
 Individual trading systems can be thought of as a “chromosome”
 Individual options and parameters in a trading system are called genes
 A group of chromosomes are called a “population”
 Chromosomes are “mated” and “offspring” are produced
 These offspring may have “mutations” added
 The offspring are evaluated for “fitness,” which for the purposes of our investing is
performance
 Only the most fit (best performing) offspring are allowed to survive and mate to
produce the next generation of chromosomes
FastBreak Pro builds the first generation of chromosomes (trading systems) using a
random process. Options and parameter values for trading systems are chosen from the
options and range of values provided by the user. The systems are tested in FastBreak to
find the back-tested performance, i.e., Annual Return, MDD, and UPI. If the Annual
Return is negative for a system, it is not allowed to “survive.” This is why you may see
the Current Population counter at the bottom of the Best Results screen exceed the size
value you specified for the first generation.
The FastBreak Pro user can specify one of three variables to optimize: Annual%, UPI,
and MDD. The user can also specify additional “objectives.” For example, the typical
user will want to optimize Annual% but may also require a maximum acceptable MDD, a
maximum number of switches per year, and a minimum UPI. These additional objectives
are used to obtain an “adjusted” performance value. The adjustment is a penalty applied
to the optimized variable.
Here is an example: A user may specify to optimize Annual%, with a MDD of no more
than 15% and a maximum of 10 switches per year.
A hypothetical system may return a
value of 20% annual return, with a MDD of 18% and 14 switches per year. The adjusted
performance is calculated by multiplying the system return by penalty functions as
follows: