Thx for the info Michael, The performance seems great, I'll try to find some time to study NNN deeply and see if they're applicable to HFT and intraday
Cheers On Fri, Feb 25, 2011 at 4:18 PM, Astor <[email protected]> wrote: > Yes. I have built a NNN strategy which trades ETFs. Each ETF in the > tradable universe is chosen to be a proxy of a sector of the economy. > > The strategy is market-neutral and can best be described as sector > rotation strategy. > > Over seven years the annualized return is 25% and Sharpe ratio is 2.4. It > had a single drawdawn of 30%, lasting one week when the markets > imploded during the subprime meltdown. All other drawdawns were less than 6 > %. The strategy is in the market 30% of the time. > > It is not an HFT strategy though. It trades only once a day, > takes positions (or not) at the open and closes them at the close. No > overnight positions and no intraday trading. > > I think the same approach can be used for HFT strategy as well. > > ------------------------------ > *From:* Victor Martin <[email protected]> > *To:* [email protected] > > *Cc:* Astor <[email protected]> > *Sent:* Fri, February 25, 2011 3:54:04 AM > *Subject:* Re: [JBookTrader] Poll for new features > > Astor, have you backtested successfully any NNN strategy? Can you share its > results?? > > cheers > > On Fri, Feb 25, 2011 at 4:20 AM, Astor <[email protected]> wrote: > >> Da, I have built quite a few ANN models. Several of them had been (and >> I think still are) used to manage portfolios with AUM in tens of billions. >> Let me save you some time - if you are going to optimize thousands of >> parameters, you will most definitely overfit the data. Your model will >> perform spectacularly in the backtest and will fail in actal trading. >> >> I can give you a litany of other problems that you will encounter. You >> will have no clue whether your forecasts come from densely or sparsely >> populated sample space, i.e. confidence intervals of your forecasts will >> vary greatly. When your model fails, you will not know if it is part of >> normal operation or if there has been a structural shift. >> >> If you are determined to explore non-linear interactions for prediction, >> you will get much more consistent and much more intuitive results using >> N-nearest neighbor algorithm. NNN has no parameters to optimize, requires no >> training and can be updated in real time - which is very important for >> HFT. As long as your original hypothesis for your model makes sense, you >> will be able to understand the basis for the predictions. >> >> Good luck. >> >> ------------------------------ >> *From:* Da Xu <[email protected]> >> *To:* [email protected] >> *Sent:* Thu, February 24, 2011 6:41:18 PM >> >> *Subject:* Re: [JBookTrader] Poll for new features >> >> >> As I posted before, I woud like to develop artificial neural networks >> strategy on JBT. We have to add thousands of parameters and change the >> optimization class. I have been focusing on this project for a couple of >> months. Are there anyone that is interested in ANN strategy? >> >> Da >> >> >> >> On Wed, Feb 23, 2011 at 3:19 PM, nonlinear <[email protected]>wrote: >> >>> Do JBT users have a "wish list" for the new JBT features/functionality? >>> If so, please post them here. >>> >>> -- >>> You received this message because you are subscribed to the Google Groups >>> "JBookTrader" group. >>> To post to this group, send email to [email protected]. >>> To unsubscribe from this group, send email to >>> [email protected]. >>> For more options, visit this group at >>> http://groups.google.com/group/jbooktrader?hl=en. >>> >> >> -- >> You received this message because you are subscribed to the Google Groups >> "JBookTrader" group. >> To post to this group, send email to [email protected]. >> To unsubscribe from this group, send email to >> [email protected]. >> For more options, visit this group at >> http://groups.google.com/group/jbooktrader?hl=en. >> >> -- >> You received this message because you are subscribed to the Google Groups >> "JBookTrader" group. >> To post to this group, send email to [email protected]. >> To unsubscribe from this group, send email to >> [email protected]. >> For more options, visit this group at >> http://groups.google.com/group/jbooktrader?hl=en. >> > > -- > You received this message because you are subscribed to the Google Groups > "JBookTrader" group. > To post to this group, send email to [email protected]. > To unsubscribe from this group, send email to > [email protected]. > For more options, visit this group at > http://groups.google.com/group/jbooktrader?hl=en. > > -- > You received this message because you are subscribed to the Google Groups > "JBookTrader" group. > To post to this group, send email to [email protected]. > To unsubscribe from this group, send email to > [email protected]. > For more options, visit this group at > http://groups.google.com/group/jbooktrader?hl=en. > -- You received this message because you are subscribed to the Google Groups "JBookTrader" group. 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