Adaptive parameters of the indicator adapting to the filter of volatility and momentum

Discussion in 'Automated Trading' started by novikov433, Feb 15, 2019.

  1. I want to understand, is it possible to implement such an algorithm in python, R? Just need to put the parabolic sar, and use the momentum readings to change the parabolic parameter.

    Just need to make a change in the condition of entry into the transaction, depending on the indication of the momentum indicator, and then the condition: in which the open buy transaction at the value of Acceleration 0.02 closes when Acceleration receives a signal of 0.2.[​IMG]
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    With the sale of all the same. Can python acc omplish this task? What course on python would you recommend?

    Why just do not have this function by default and we are forced to focus on the testimony of history?

    After all, the Grail is hidden in this function, which by default is not in more than one terminal.

    Here are some sites for learning I found:
    1: https://www.quantinsti.com/
    2: https://optinum.co.za/competency/algorithmic-trading/
    3: https://www.getsmarter.com/courses/uk/oxford-algorithmic-trading-programme
    4: https://robotwealth.com/algo-bootcamp/
    5: https://www.quantstart.com/articles
    6: https://www.coursera.org/courses?query=algorithmic trading
    7: https://www.udemy.com/courses/search/?q=algorithmic trading&src=sac&kw=algo
    8: https://www.quantconnect.com/
     
    Last edited: Feb 15, 2019