The following script allows you to simulate sample runs of Win, Loss, Breakeven streaks based on a random distribution, using the run length encoding function, rle in R. Associated probabilities are entered as a vector argument in the sample function.

You can view the actual sequence of trials (and consequent streaks) by looking at the trades result.  maxrun returns a vector of maximum number of Win, Loss, Breakeven streaks for each sample run. And lastly, the transition table gives a table of proportion of run transitions from losing streak of length n to streak of all alternate lengths.

Example output (max run length of losses was 8 here):

100*prop.table(tt)
    lt.2
lt.1      1      2      3      4      5      6      7      8
   1 41.758 14.298  5.334  1.662  0.875  0.131  0.000  0.044
   2 14.692  4.897  1.924  0.787  0.394  0.087  0.131  0.000
   3  4.985  2.405  0.525  0.350  0.000  0.000  0.044  0.000
   4  1.662  0.875  0.306  0.087  0.000  0.000  0.000  0.000
   5  0.831  0.219  0.175  0.000  0.000  0.044  0.000  0.000
   6  0.087  0.131  0.044  0.000  0.000  0.000  0.000  0.000
   7  0.087  0.087  0.000  0.000  0.000  0.000  0.000  0.000
   8  0.044  0.000  0.000  0.000  0.000  0.000  0.000  0.000

maxrun
 B  L  W
 3  8 17

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#generate simulations of win/loss streaks use rle function

trades<-sample(c("W","L","B"),10000,prob=c('.6','.35','.05'),replace=TRUE)
traderuns<-rle(trades)
tr.val<-traderuns$values
tr.len<-traderuns$lengths
maxrun<-tapply(tr.len,tr.val,max)

#streaks of losing trades
lt<-tr.len[which(tr.val=='L')]
lt.1<-lt[1:(length(lt)-1)]
lt.2<-lt[2:(length(lt))]

#simple table of losing trade run streak(n) frequencies
table(lt)

#generate transition table streak(n) vs streak(n+1)
tt<-table(lt.1,lt.2)
#convert to proportions
options(digits=2)
100*prop.table(tt)
maxrun