I know this question will be quickly destroyed and my account summarily banned, but I just have to ask:
For a trader using machine-learning algorithms (SVMs, ANNs, GAs, Decision Trees) for quantitative finance, without seasoned financial intuition, what would be considered a good confidence / success rate?
I know this will depend on the following, as well as other items I'm not aware of:
-Market / Sector (stocks, commodities, FOREX, etc.)
-Frequency of trades
-News Volatility of sector
-Range of dates used for datasets
Please feel free to list other considerations... But in the end, to make the question crystal clear I'd really like a target number. 75%? At 60% I would be roughly taking 1 step forward for every 10 steps taken. Any less and I might as well flip a coin. If it varies, please list the considerations under which they do so. If possible, it would be preferable to use these models to support trades over a period of days rather than seconds/minutes.
If you have other suggestions for how to go about things based on low/high, principal, markets to consider, share prices, etc. please feel free. If my question does not make sense, please tell me why. Thank you.
-At this point I was simply trying to predict up and down movements over a 5 day period. Simple. 45%.
-Free Yahoo data be my market data source... daily quotes. Wasn't sure if intra-day information would be helpful.
-I've attempted ANNs, SVMs, and some GAs so far.
-I wasn't looking for real-time trading, but instead looking to identify regular tides over a several day period.
-Maybe if I can get my error high enough, I can simply trade opposite my predictions! (no, seriously though)