Ultimate Algorithmic Trading System

■ Initial Population Setup Using VBA Excel
'All Lines starting with single quote is a comment
'Random variables into each chromosome’s genes
'Numbers range between 0 and 30
'Chromos will be represented by a table/matrix
'The first index in the chromo table will be row #
'The second index in the chromo table will be column #
'Excel's RNG is invoked by using the Rnd function call
'Int ((upperbound - lowerbound + 1) * Rnd + lowerbound)
232
GENETIC OPTIMIZATION, WALK FORWARD
Randomize '<– must use this to get different numbers
For i = 0 To 5 ' Six Chromos
Next i
For j = 0 To 3 ' Four Genes
Next j
chromo(i, j) = Int((30 - 0 + 1) * Rnd + 0)
How good or fit is this population? Fitness is determined by how close each
chromosome comes to providing a solution to our equation. Remember, this is a very
simple problem, but these ideas are easily scalable to problems involving extreme
complexity. Calculating fitness is quite easy; simply plug in the chromosomes’
genes (values) for a, b, c and d. In chromosome (0) its fitness is determined by:
a(10) +2b(2 ∗ 11) +3c(3 ∗ 20) +d(19) =111. The solution we are seeking
is 40 so this fitness doesn’t seem to be that good. However, each chromosome’s
fitness is relative to all the other chromosomes.
Fitness 1: Chromosome(0) = 111
Chromosome(1) = 94
Chromosome(2) = 64
Chromosome(3) = 90
Chromosome(4) = 164
Chromosome(5) = 93
■ Testing Fitness of Chromosomes Using VBA Excel
'Equation is : a + 2b + 3c + d = 40
'a coefficient = Cell(3,3)
'b coefficient = Cell(3,4)
'c coefficient = Cells(3,5)
'd coefficient = Cells(3,6)
'the summation of the equation is in Cells(3,7)
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