Unify

This release connects models with systems for MarketFlow, i.e., you can now use the probabilities generated by a classifier as trading signals. For example:

system:
    name       : alpha
    holdperiod : 0
    longentry  : phigh_0.6
    longexit   :
    shortentry :
    shortexit  :
    scale      : False

The variables phigh and plow are variables defined by AlphaPy. For example, if the probability associated with a time series prediction is greater than or equal to 0.6, then the system would go long. Likewise, a short entry might have a value of plow_0.4, meaning the probability is less than or equal to 0.4.

This release also fixes a bug with '.' in variable names, such as the examples shown above.

The market section of the market.yml has been changed to add the fields create_model and data_fractal (resample_data has been removed). If fractal is different than the data_fractal, then the data are resampled to the fractal value. Set create_model to False if you wish to test different systems after creating your initial model, or if your systems are free-standing and don't use the output of a model.

market:
    create_model    : True
    data_fractal    : 1min
    data_history    : 100
    forecast_period : 1
    fractal         : 20min
    lag_period      : 1
    leaders         : []
    predict_history : 50
    schema          : data
    subject         : crypto
    target_group    : btc

Finally, there is now one general system for both daily and intraday systems. Intraday signals are automatically closed at the end of the day. All systems follow the format shown above, and you can mix model-based signals with technical signals.