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.
