Automated strategies risk/return profiles examples

Discussion in 'Automated Trading' started by jelite, Jan 12, 2011.

  1. jelite

    jelite

    I have always been interested in seeing what other people can come up with when it comes to fully automated trading strategies. By that I do not mean them actually revealing their strategy logic (why would they?) but rather providing a glimpse of what risk/return/drawdown etc. their strategy can achieve.

    So here is what I would like to see ideally in this thread. Whoever has a strategy that is fully automated (purely mechanical), please share some of your backtested (or better yet traded) results. The only requirement I pose here: only include OUT OF SAMPLE tests of your systems.

    By the same token, here is what I wouldn't like to see: a bunch of people saying it's impossible to come up with a purely mechanical trading strategy.

    To be fair I am attaching a snapshot of one of my strategies, I hope to see many others.
     
  2. Bowgett

    Bowgett

    Here is one of mine systems

    Out of sample results:

    Type: Long/short US equities
    Annual return: 48.42%
    Trades number: 15,739
    Max draw down: 23.80%
    Max draw down period: 7 month
    Max positions in portfolio: 44
    Margin: 70%
    Sample: 18 years
     
  3. Bowgett

    Bowgett

    and here are actual results for 2010
     
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  4. jelite

    jelite

    That equity curve looks nice. Would be great to see it without compounding and a known % of capital risk per trade. For example, in my attached sheet, the equity curve shows growth of capital in % without compounding and assuming a fixed 2% risk per trade. That makes it easy to spot whether performance of the strategy has been deteriorating over time. In any case, thanks for your contribution, I hope we will get to see more here...
     
  5. Bowgett

    Bowgett

    I forgot to mention that I use equally weighted portfolio for this system so for 44 positons that would be 2.27% of capital for each position.
     
  6. Ok, I'll play...

    The following is from a strategy I started working on about 4 months ago. It may not have the best numbers, but what it does have is very small draw downs (less than 7% in the last 2 years) that don't last very long. More importantly it is a steady climber without many flat spots.

    + PF of 1.64
    + Max Drawdown of 13.81% (not more than 7% in the last 2 years)
    + 1305 trades since 8/1/2008
    + 58.4% profitable

    * Results are completely out-of-sample
    * Non compounding results
    * No position sizing changes employed (in live trading, I'm increasing sizes based on returns)
    * Commissions are included in results
     
  7. I have a purely "mechanical approach" and have been sharing a lot in various threads here on ET. With both live and simulated results, under various random walk hypothesis. Here is the last one:

    http://www.elitetrader.com/vb/showthread.php?s=&threadid=208265&perpage=6&pagenumber=6

    Actually i don't believe other approaches to be profitable. But that's another story ... ;-)

    Tom
     
  8. travis

    travis

  9. alarFX

    alarFX

    Before you trade with automated system, you have to consider the risk that your account can support.

    People used to take a high risk, to generate high win rates. Because people like to win... that is an usual mistake.

    You have to be patient and persevering and design an strategy that gets small steady gains... Probably you will not get 100 pips per day, but you will get it. If you are a newie, start always trading with microlots.

    I was working on my portfolio yesterday in rentasignal, I have three diferent moderate signals in it and I never risk more than the 20% of the size of my account per week, so I adjust my stop loss according it so I never have high losses and get littles profits progressive
    :)
     
  10. StateWX

    StateWX

    but, have u been able to find three good signlas in rentasignal? Tell me how because I have tried to invest twice with them and I continue being poor...
     
    #10     Feb 4, 2011