Saturday, April 16, 2011
When Sharpe is useless
During development of an intrady strategy I've come across a case where Sharpe ratio (and Sortino too) is a very bad way to benchmark performance. To illustrate this case, imagine a strategy that enters a position and 'brackets' the exit levels with a limit and a stop-loss order. This results in the pnl distribution as shown in the graph:
The position is either closed at the limit or the stop-loss level, but not in between. Because Sharpe is all about normal distribution, it just does does not work for this case. A better solution here is to use win %, especially in the case of symmetric brackets.
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I work at a prop trading firm, where the firm's risk management philosophy is for everyone to have a daily stoploss after which, the trader must puke it's position and start over the next day(I think it's actually a pretty common way of doing business). So, I have come to rely heavily on the sterling ratio as it optimizes 'exactly' what I want, ie, return/maxDrawdown
ReplyDeleteI don't see any problem for Sharpe ratio here. Stop-loss and Take-profit levels are important for one trade. But you will have several trades during the day and much more during the month. Your total monthly returns (i.e. sum result of all your trades) will be normally distributed (or close to normal). And you will compare performance of the strategy to proper benchmark by, for example, Sharpe ratio.
ReplyDeleteI agree that with many trades per day the daily returns could converge towards a normal distribution. However this particular strategy trades only 1x a day.
ReplyDeleteA Sterling ratio seems to be much better in this case (thanks for the tip, anonymous#1).
Hi Jev, nice blog and good point in using Sharpe Ratios.
ReplyDeleteSomething else I find useful to look at to get a more complete pictures are profit factors and expected gains. These implicitly give you information about drawdowns and in my opinion also make it easier to track your strategy performance (or lack of) once you go live.
Andrea