Nooby McNoob becomes a quant

Discussion in 'Journals' started by nooby_mcnoob, Mar 24, 2017.

  1. sle


    That means that a strategy has small possible absolute dollar output. For example, imagine that there is an ETF that frequently trades at a significant discount/premium to NAV. If this ETF has very little daily volume and you can only make a small amount in dollar terms, you'd say that it's a capacity constrained strategy.
    #41     Mar 25, 2017
    algofy, nooby_mcnoob and O(1) like this.
  2. sle


    Mainly because you get used to a specific jargon and assume that other people know it. For example, a lot of Americans would say "X is built like a linebacker" which colloquially would be "X is tall and weighs a lot". If you work in finance you might as well learn the jargon.
    #42     Mar 25, 2017
  3. New member here, but been through the grinder already.

    Here is my advice for intraday auto-trading:

    1) Start with capacity constrained markets (as sle metioned)

    2) Focus on event-driven trading/testing (not easy to test)

    3) Use a quality tick data provider and software that can implement it
    Last edited: Mar 26, 2017
    #43     Mar 26, 2017
    mrgod2u and nooby_mcnoob like this.
  4. quant1


    Sounds like a very reasonable way to start out. You definitely have the right skill set. The way to work around the unexplained losses situation is by decoupling alpha models from execution models. If you have an alpha model that back tests well but fails live, then you can test the model over the live period to confirm signal strength. If it is still strong, then your execution/fees are the problem. If not, the signal must be refined.
    #44     Mar 26, 2017
    digitalnomad likes this.
  5. Glad to hear you say that.

    I was of the impression that most backtest frameworks allow you to model commissions and slippage as well. Are you saying that even when you model these, the differences from reality are large enough to trash your model in live trading?
    #45     Mar 26, 2017
  6. quant1


    I see the confusion. I'm saying that you should have separation between the models for alpha and execution. And then, you backtest using both at the same time. Basically, you want to be able break apart the effects of the models to the greatest extent possible.
    #46     Mar 26, 2017
    Simples and nooby_mcnoob like this.
  7. algofy


    Some quant talk and methods make things more complicated than it needs to be. I intentially stay away from all quant education material and I just develop and test in a common sense approach that greatly reduces curve fitting and then I just throw a ton of mud at the wall and every once in a while something sticks. Like allot of things in life, keeping it basic and simple works better, at least for me.
    #47     Mar 26, 2017
  8. To each their own, for sure, but the guys at Renaissance Technologies would like to have a word with you. Speaking of which... Anyone here know anything about the actual models they are using?
    #48     Mar 26, 2017
  9. quant1


    No claim to specify methods, but it seems signal processing is of great interest there.
    #49     Mar 26, 2017
  10. sle


    No (to the next question).
    #50     Mar 26, 2017