Curve fitting

Discussion in 'Automated Trading' started by boza, Dec 13, 2017.

  1. boza

    boza

    Everyone says that you shouldn't curve fit a system perfectly because it will fail. So why not perfectly curve fit a system and then just do the opposite of that system?
     
    sle likes this.
  2. sle

    sle

    Because failure does not mean a guaranteed money-losing. Instead it’s going to be neither here nor there and going to slowly bleed transaction costs.
     
    tommcginnis, Xela, d08 and 1 other person like this.
  3. tomorton

    tomorton

    Development of a strategy's rules is good, writing unrealistic rules that could only have been justified by hind-sight is delusional.

    For example, you take stock long trades triggered by some buy signal. Development would be a filter to disregard buy signals received while the stock's index is bearish. Curve-fitting would be a filter to use smaller position sizes on losing trades - these could only be identified after the event.
     
    digitalnomad likes this.
  4. southall

    southall

    It might not fail completely. Just give you huge drawdowns.

    When testing a curve fit system it might give worst case 25% drawdowns with average 100% yearly returns. Sounds excellent.

    But in real world trading, because the system was curve fit, it might actually give 75% drawdowns and only 25% return.

    If you attempt to trade a system with 75% drawdowns you will eventually fail in your execution due to psychological issues. Even if you automate such a strategy you will eventually turn it off and fail.

    If you attempt to fade the same system you will also eventually fail as the system is net profitable. If the system went into drawdown straight away and you faded the drawdown and made 75%, that will all be lost + more when the system recovers.
     
    Last edited: Dec 14, 2017
    shatteredx likes this.
  5. Simples

    Simples

    Indeed. The trading problem is a problem of consistency. The more you study, the more you realize the lack of it in the markets. Longer-term frequencies may help, but still the future is fundamentally unknowable for most. If the system is consistently losing, you can just reverse it to win. However finding a consistent loser is just as hard as finding consistency in winning.

    I've started thinking any system I make will be wrong for some period, and need to mitigate that. This is due to sheer improbability of predicting 100% correctly, or even anticipating or following correctly, without some larger overall fail periods.
     
    Last edited: Dec 14, 2017
    tommcginnis likes this.
  6. d08

    d08

    That's not the definition of curve-fitting. You're talking about peeking (as in, peek into the future).
    Curve-fitting is over-optimizing parameters for maximal risk-reward, no peeking involved.
     
  7. userque

    userque

    Curve-fitting with relevant inputs is good.
    Curve-fitting with irrelevant inputs is bad.
    Over-fitting with either is bad.

    The desired skill lies in (1) identifying the relevant inputs and (2) not over-fitting them.
     
    cafeole, digitalnomad and Xela like this.
  8. qxr1011

    qxr1011

    Everyone is wrong : system fail not because of perfect fit, but because the fit itself is no substitution for finding fundamental rules of the market!

    And you are wrong too because opposit of wrong is wrong in trading at least
     
    CALLumbus likes this.
  9. boza

    boza

    What about applying technical analysis to the equity curve of the system?
     
  10. lukepoga

    lukepoga

    This is the actual reason:

    Curve fitting means you looked at the past and built a model on the noise during that period.

    It’s the same as throwing tea leaves to decide where the prices will go. Whether you follow the leaves, or do the opposite, you are still just making a decision from noise.

    you could ask an octopus what to do. It’s the same thing.

    Hope that illustrates why curve fitting or the opposite, has no predictive power at all!
     
    #10     Dec 14, 2017
    spindr0 and goodgoing like this.