Quant opinion: How to treat the losers?

(Last Updated On: November 23, 2011)

Quant opinion: How to treat the losers?

Anyone care to dicuss some metrics for getting out of bad trades? I’m working on a directional scalping system. It trades 50-200 times per day, so it’s not UHFT. The success rate is north of 95%, but the problem with the other 5% is that the losers can potentially grow pretty large, and offset the profits. So I need to find a quantifiable way to either skip the big losers(or more likely) manage them better.

The entry logic is pretty close to random, so there’s no secret sauce here…

Anyone have any thoughts?


What do you mean specifically by “losers … can grow pretty large”.
You have already said they are capped, say, to a 5% of trades (if i got that part right).
So, by “grow ” do you mean that, in your model, position size of losers is increasing, or that distance from entry is increasing, or maybe both ?

PS. Note that since you said that entries are close to random, all the “strategy” reduces essentially to trade and risk management. Which is essentially what you are asking about… 😉



right, the losers grow by way of distance from the entry. I’m not using any sizing models. All trades are sized equally at this point.

That is exactly what I’m looking for – some trade and risk management ideas…


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