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