Portfolio analytics utilities
This is the beginning of a work in progress. I expect it will be in pretty good shape early in 2023 and then evolve from there.
This is a supporting package for a larger project I am working on and should be useful to others as is.
$ pip install moneycounter A trades dataframe has these columns:
columns = Index(['dt', 'q', 'p', 'cs', 't', 'a'], dtype='object')
It must be ordered by dt.
Where:
| Column | Description |
|---|---|
dt |
execution time as datetime.datetime |
q |
quantity traded, signed with negative as a sale |
p |
execution price |
cs |
contract size, typically 1.0 |
t |
ticker |
a |
account |
from datetime import date
from moneycounter import pnl, realized_gains, wap_calc
# Calculate realized, unrealized and total pnl from trades dataframe.
realized, unrealized, total = pnl(df, price=price)
# Calculate weighted average price of open positions from trades data frame.
wap = wap_calc(df)
# Calculate realized gains from trades data frame.
realized = realized_gains(df)
$` \phi = c * Q * (p - p_wap) `$