Dynamic calculation based on "weights" dictionary

josephg

Hi, I started discovering BackTrader, and I would appreciate any suggestion how to "structure" my strategy.

The algorithm needs to read a dict which contains different weights of total position size. Let's say I want to split a complete position in 4 orders, then, any time the datas[0].high fill the target_price position.size += 1 out of total of 4. However, theses target prices are intended to be moved by offset. So, this target_price should be dynamic calculated based on an offset given by a dict.

Following code is an example of my strategy I want to code, please keep focus on the part I want to create de entries dictionary based on an imported CSV, this file includes offset to then dynamically map params.offset.vaue.

I want to include this mapping part in the def next() part when if <condition> statement is True when False the offset remains as initially declared.

lass PoolsJedi(bt.Strategy):
    params = (
        ('offset', 0.0055),
    )

    def __init__(self):
        # Start fields
        self.dataopen = self.datas[0].open
        self.dataclose = self.datas[0].close
        self.datahigh = self.datas[0].high
        self.datalow = self.datas[0].low

        # Create weights dictionary
        qtr = pd.read_pickle('config/weights.csv')
        entries = {
            w: {
                'e{}'.format(i): qtr[e][w]
                for i,e in enumerate(qtr.columns) 
            } for w in qtr.index
        }

        # Initialize variables
        entries_length = len( entries[list(entries.keys())[0]] )
        cpos = np.array( [0] * entries_length )

    """  CODE CONTINUES """

I hope this part may give you the whole idea. I'd appreciate any support in advance.

josephg

I just figured it out. Thanks anyway for the support!