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import pandas as pd
from utils import get_mf_scheme_data
from returns import get_investment_xirr, get_investment_sip_absolute_returns
from indicators import get_investment_sd, get_investment_sharpe_ratio, get_investment_indicator_report
def get_portfolio_nav_df(schemes_name_and_weight, start_date, end_date, schemes_df):
# start_date = pd.to_datetime(start_date)
# end_date = pd.to_datetime(end_date)
portfolio_nav_df = pd.DataFrame()
for scheme_name, scheme_weight in schemes_name_and_weight.items():
scheme_code = schemes_df[schemes_df['schemeName'] == scheme_name]['schemeCode'].values[0]
scheme_nav_df, _ = get_mf_scheme_data(scheme_code= scheme_code)
scheme_nav_df = scheme_nav_df[(scheme_nav_df['date'] >= start_date) & (scheme_nav_df['date'] <= end_date)]
scheme_nav_df['nav'] = scheme_nav_df['nav'] * scheme_weight / 100
if portfolio_nav_df.empty:
portfolio_nav_df = scheme_nav_df
else:
portfolio_nav_df['nav'] += scheme_nav_df['nav']
return portfolio_nav_df
def get_portfolio_xirr_returns(portfolio_df, start_date, end_date, SIP_date, lumpsum_amount, sip_amount):
return(get_investment_xirr(portfolio_df, start_date, end_date, SIP_date, lumpsum_amount, sip_amount))
def get_portfolio_absolute_returns(portfolio_df, sip_amount, lumpsum_amount, stepup, start_date, end_date, SIP_date):
return (get_investment_sip_absolute_returns(portfolio_df, sip_amount, lumpsum_amount, stepup, start_date, end_date, SIP_date))
def get_invdividual_scheme_returns(scheme_df, scheme_name,scheme_sip_amount, scheme_lumpsum_amount, stepup, start_date, end_date, SIP_date):
absolute_return, final_value, invested_value = get_investment_sip_absolute_returns(scheme_df, scheme_sip_amount, scheme_lumpsum_amount, stepup, start_date, end_date, SIP_date)
xirr = get_investment_xirr(scheme_df, start_date, end_date, SIP_date, scheme_lumpsum_amount, scheme_sip_amount)
scheme_string = f"""
Scheme: {scheme_name}
------------------------------------
Investment: {invested_value}
Scheme Final Value: {final_value}
Absolute Return: {absolute_return}%
XIRR: {xirr}%\n
"""
return (scheme_string)
def get_inception_date_warnings(inception_dates, start_date):
warnings = []
for scheme_name, scheme_inception_date in inception_dates:
if scheme_inception_date > start_date:
warnings.append(f"{scheme_name} has an inception date of {scheme_inception_date} which is after the start date of the portfolio.")
return warnings
def calculate_portfolio_returns(scheme_name_and_weight, sip_amount, lumpsum_amount, stepup, start_date, end_date, SIP_date, schemes_df):
inception_dates = []
scheme_individual_returns = []
portfolio_df = get_portfolio_nav_df(scheme_name_and_weight, start_date, end_date,schemes_df)
portfolio_absolute_return, portfolio_final_value, portfolio_invested_value = get_portfolio_absolute_returns(portfolio_df, sip_amount, lumpsum_amount, stepup, start_date, end_date, SIP_date)
portfolio_indicators_string = get_investment_indicator_report(portfolio_df, start_date, end_date)
for scheme_name, scheme_weight in scheme_name_and_weight.items():
scheme_code = schemes_df[schemes_df['schemeName'] == scheme_name]['schemeCode'].values[0]
scheme_df, scheme_inception_date = get_mf_scheme_data(scheme_code)
inception_dates.append((scheme_name, scheme_inception_date))
scheme_sip_amount = sip_amount * scheme_weight / 100
scheme_lumpsum_amount = lumpsum_amount * scheme_weight / 100
scheme_individual_returns.append(get_invdividual_scheme_returns(scheme_df, scheme_name, scheme_sip_amount, scheme_lumpsum_amount, stepup, start_date, end_date, SIP_date))
inception_date_warnings = get_inception_date_warnings(inception_dates, start_date)
portfolio_report_string = f"""
Portfolio
------------------------------------
SIP Amount: {sip_amount}
Lumpsum Amount: {lumpsum_amount}
Stepup: {stepup}
Start Date: {start_date}
End Date: {end_date}
SIP Date: {SIP_date}
Total Investment: {portfolio_invested_value}
------------------------------------
Portfolio Report
XIRR = {get_portfolio_xirr_returns(portfolio_df, start_date, end_date, SIP_date, lumpsum_amount, sip_amount)}%
Absolute Returns = {portfolio_absolute_return}%
Portfolio Final Value = {portfolio_final_value}
{portfolio_indicators_string}
------------------------------------
Individual Scheme Returns
------------------------------------
{''.join(scheme_individual_returns)}
------------------------------------
Warnings
{''.join(inception_date_warnings)}
"""
return portfolio_report_string
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