Need help optimising / simplifying formula and additional filtering

I have a dataset with variour portfolios, each made up of various lists with their ratios. The dataset has daily return values, and I am calculating cumulative return as follows:

cumulative_return = previous cumulative_return * (1 + daily_return)

To achieve that I am using PRODUCTX, multiplying the PRODUCTX output with the ratio, and summing all the components with SUMX.

The following is my current formula:

cr3 = 
var tbl = ALLSELECTED('CMC Daily Return')
var onDate = MAX('CMC Daily Return'[last_updated])
var fk_count = DISTINCTCOUNT('CMC Daily Return'[fk])
RETURN
SUMX(
    'CMC Daily Return',

    var fk_item = 'CMC Daily Return'[fk]
    var list_item = 'CMC Daily Return'[list_id]
    var fromDate = CALCULATE(
        MIN('CMC Daily Return'[last_updated]),
        tbl,
        'CMC Daily Return'[fk] = fk_item,
        'CMC Daily Return'[list_id] = list_item
    )
    RETURN
    CALCULATE(
        PRODUCTX(
            'CMC Daily Return',
            IF('CMC Daily Return'[last_updated] = fromDate, 1, 1 + 'CMC Daily Return'[daily_return])
        ),
        tbl,
        'CMC Daily Return'[fk] = fk_item,
        'CMC Daily Return'[list_id] = list_item,
        'CMC Daily Return'[last_updated] >= fromDate,
        'CMC Daily Return'[last_updated] <= onDate
    ) * 'CMC Daily Return'[ratio]
) / fk_count

The above formula works, but I feel it could be simplified or optimised better. I'd also like to add another metric yesterdays_cumulative_return, where I'd just do a calculate of cumulative_return with a filtered dataset until yesterday.

Currently that is not working with the above formula. Appreciate any help.