moneycounter 1.4.3

Portfolio Analytics Utilities

Money Counter

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.

Installation

PyPI Page

$ pip install moneycounter 

Prerequisite Trades Data Frame

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

Example Calculations

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)

$` \phi = c * Q * (p - p_wap) `$