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Top mistakes to avoid with quant analytics and trading

(Last Updated On: March 27, 2012)

Top mistakes to avoid with quant analytics and trading Hi all. I’m cross posting a question that I put on a similar group to see whether folks here are also interested in throwing out some answers…
I’ve been thinking about this for a little bit, and wondered what some of you thought about this subject. I am interested in polling folks for what they think the most important “schoolboy errors” that people make when moving into this space?
I am thinking along lines of 1 – overfitting data2 – poor backtesting procedures (no in/out sample + no costs)3 – making inappropriate use of future information without realising it…
Things like that. I could add a few more, but I am more interested in seeing what comes up in the discussion…
I would be interested in your experiences in this area…
Cheers
–hmmm… looks like mistakes are as carefully guarded as the successes 😉
–Some strategies in equities and currencies tend to fade in and out in success i.e. they stop being successful and mysteriously start being successful again. So back testing has to be routinely carried out, depending on the trading time frames. The back testing should also consider breaking down the trading day, i.e. Asian, UK, US sessions, market closing and openings. These different times have different participants and hence different strategies come to play. The Asian session is notorious for low volume and cheeky brokers stop hunting, best avoided! These are a few of my head that I know that are really important. I apply these to trading they hold equally for algo trading, the only difference being the algo has no emotion

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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