Ultimate Algorithmic Trading System

selection and reproduction may eventually converge and produce a nondiverse
population. Mutation can randomly change a genetic element and then like a chain
reaction create different selections and reproductions.
Before we mutate the initial population, let’s review our chromosome population
as it stood after our first selection and reproduction phase:
Chromosome (0) = [16,05,13,28]
Chromosome(1) = [13,08,15,20]
Chromosome(2) = [00,20,05,09]
Chromosome(3) = [16,05,13,28]
Chromosome(4) = [10,30,30,04]
Chromosome(5) = [00,20,05,09]
The rate of mutation should be low because you do want a convergence to
occur. In other words, you want a solution, and a high mutation rate could
potentially spin the population off into too many different directions. But at the
same time, you don’t want your population growing stale, either, and a sufficiently
high mutation rate prevents this. In this example, a mutation rate of 10 percent
was used. With six chromosomes, there are 24 genes or numbers total, so if the
mutation rate of 10 percent is applied, then 2.4 genes will be mutated. Since we
can’t have a partial gene, the number is rounded down to two. So out of the
24 numbers above, 2 of them will be randomly selected and replaced with two
random numbers between 0 and 30 (the same range that we initially used to seed
the population).
Each gene is assigned a number between 1 and 24 in order. So chromosome (0)
will have genes labeled 1 through 4. Chromosome (1) will have genes 5 through
8, and so on. Relying on the random number generator yet again (range between
1 and 24), it generates two numbers: 7 and 24. Don’t put the random number
generator away yet; we still need to randomize two more numbers between
0 and 30 to use in our mutation. After pushing the button on the RNG, two
numbers, 22 and 15, were generated. If we map 7 and 24 across the matrix of
chromosomes, then the following highlighted genes will be mutated with the
numbers 22 and 15:
Chromosome (0): 16 1 05 2 13 3 28 4
Chromosome (1): 13 5 08 6 22 7 20 8
Chromosome (2): 00 9 30 10 30 11 04 12
Chromosome (3): 16 13 05 14 13 15 28 16
Chromosome (4): 10 17 30 18 30 19 04 20
Chromosome (5): 00 21 20 22 05 23 15 24
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GENETIC OPTIMIZATION, WALK FORWARD
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