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 prop table gives a table of proportion of run transition pairs 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

-----------------------------------------------------------------------------------------

#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 joint ensemble table streak(n) vs streak(n+1)

tt<-table(lt.1,lt.2)

#convert to proportions

options(digits=2)

100*prop.table(tt)

maxrun

7 hours ago

Nice R demonstration.

ReplyDeleteDo you actually use studies like this in deciding if you are going to trade a system?

Thanks Craig,

ReplyDeleteThis particular simulation was put together in response to a forum thread I happened to be reading about how to approach the question. Practically speaking, it really depends upon your trading style. Although I sampled from a random distribution to illustrate the approach, I generally prefer to sample from empirical data related to a strategy. If anything, this type of simulation demonstrates that a very large number of trials is required to minimize any kind of output results variance associated with such input as expected parameters. However, it has other uses, such as comparing your system's runs to a random one.

IT