![]() ![]() As with lookback options, the first instinct is to price them using Monte Carlo techniques, but one can actually do so much more quickly using a multi-level PDE solver, at least for sufficiently simple SDEs. So far as efficient computation goes, we can regard this as a payoff very similar to a lookback option (much as in the PDF you linked). Therefore you should play with a variety of parameterizations to estimate your model error. (After the clarification, this answer is no longer relevant)Įxpected maximum drawdown is going to be highly sensitive to your choice of SDE, and to your calibration of it. Rd.DrawDown, rd.DrawDownPeak, rd.DrawDownTrough, rd.PeakIndex, rd.TroughIndex)) ![]() Int _startIndex, _endIndex, _troughIndex Here is the code of the simple drawdown class used for the comparisons: public class SimpleDrawDownĪnd here is the code for the full efficient implementation. We are achieving about a 20:1 improvement in calculation time. Test10 - running drawdown test with 500 period rolling window. Test9 - running drawdown test with 360 period rolling window. Test8 - running drawdown test with 180 period rolling window. Test7 - running drawdown test with 60 period rolling window. Here we compare to the results generated from my efficient rolling window algorithm where only the latest observation is added and then it does it's magic test6 - running drawdown test with 30 period rolling window. Total net profit, profit factor, percent profitable, average trade net profit, and maximum drawdown are the five key metrics included in most performance reports. Test5 - simple drawdown test with 500 period rolling window. Test4 - simple drawdown test with 360 period rolling window. Test3 - simple drawdown test with 180 period rolling window. Test2 - simple drawdown test with 60 period rolling window. Here we take a simple drawdown implementation and re-calculate for the full window each time test1 - simple drawdown test with 30 period rolling window. I want to share this as the effort required to replicate this work is quite high. I have gone ahead and written a solution to this in C#. This is quite a complex problem if you want to solve this in a computationally efficient way for a rolling window.
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