Quant opinion: How to treat the losers?

(Last Updated On: November 23, 2011)
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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…

 

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!
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About caustic

Hi i there My name is Bryan Downing. I am part of a company called QuantLabs.Net This is specifically a company with a high profile blog about technology, trading, financial, investment, quant, etc. It posts things on how to do job interviews with large companies like Morgan Stanley, Bloomberg, Citibank, and IBM. It also posts different unique tips and tricks on Java, C++, or C programming. It posts about different techniques in learning about Matlab and building models or strategies. There is a lot here if you are into venturing into the financial world like quant or technical analysis. It also discusses the future generation of trading and programming Specialties: C++, Java, C#, Matlab, quant, models, strategies, technical analysis, linux, windows P.S. I have been known to be the worst typist. Do not be offended by it as I like to bang stuff out and put priorty of what I do over typing. Maybe one day I can get a full time copy editor to help out. Do note I prefer videos as they are much easier to produce so check out my many video at youtube.com/quantlabs