Let $$ X_t = \mu t + \sigma B_t $$ be a linear Brownian motion with drift. Let $$ S_t = \max(X_u, u \le t) $$ denote the process of the running max, then the draw down is given by $$ DD_t = S_t - X_t, $$ and the maximum draw down over a period $[0,T]$ is $$max_{u \in [0,T]} DD_u.$$ What can we say about $$E[ max_{u \in [0,T]} DD_u ] ?$$ How can we calculate the expected maximum draw down? Are there analytical formulas, approximations, available (R) packages?
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as I mentioned here, this paper provides some theoretical insight (and a way to approximate the true value).
The authors end up with an approximative series for the density. It is implemented in the function maxdd of the R-package fBasics. There are convenient functions dmaxdd, pmaxdd and rmaxdd. Calculating the Expected Drawdown should be easy. (to be honest, I found the paper as a reference provided on the help page of the functions mentioned above)
The function you are asking for would be maxddStats:
require(fBasics)
maxddStats(mu,sigma,t)
answered Apr 30, 2015 at 9:06
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$\begingroup$ looking at maxddStats it looks as if they use simple MC ... $\endgroup$– Richi WaCommented Apr 30, 2015 at 13:01
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$\begingroup$ @Richard Maybe it appears to be a MC simulation because of the default value for $t$, which is $1000$, but to me the code .maxddStats looks like a numerical quadrature with precomputed values which are hard-coded into the function. I didn't look into it in more detail though. $\endgroup$ Commented Apr 30, 2015 at 13:37