富邦人壽美富紅運外幣分紅終身壽險(PFA,分紅保單) IRR分析 (死亡IRR最高45%) #富貴都是韭菜幫的 #香港保單集合

點此或下圖可以連結FB討論串
以下為富邦人壽
美富紅運外幣分紅終身壽險(PFA) 的建議書
(六年期繳)

python code:

# -*- coding: utf-8 -*-
"""
Created on Tue May 23 18:57:45 2023

@author: SavingKing

03: 
    j,k合為同一個迴圈(死亡IRR),且使用enumerate
    df使用"年"當index,以免cash_value,death_insurance
    資料的年度不一致,還可以正確合併
04:
    修正未滿期時的總報酬率計算錯誤
"""
import numpy_financial as npf
import numpy as np
import pandas as pd
import os

cash_value:list=[3705,  10019, 16618, 25014, 36514,
                 59644, 61605, 63621, 65695, 67809,
                 69908, 71975, 74042, 76104, 78143,
                 80167, 82170, 84174, 86175, 88167]  
#富邦人壽美富紅運外幣分紅終身壽險PFA 6年 #1~20年末解約金(上),死亡保額(下)
death_insurance:list=[10034, 23943, 39579, 55823, 72665,
                      264607,269510,274509,279604,284774,
                      289769,294579,297006,298837,300098,
                      300823,301045,300803,300136,299087]

rate=210/100 #30歲以下 #保誠 
#180/100 if 31~40歲
#160/100 if 41~50歲
cash_valueXrate:list = list( np.array(cash_value) * rate )

capital_protection = 7 #7年末保本
increasing_rate = [np.nan]*capital_protection 
#從保本才開始算解約金增加率

for i in range(capital_protection, len(cash_value)):
    increase = cash_value[i]/cash_value[i-1]-1
    increasing_rate.append(increase)

discount = (0)/100 #花旗,星展,華南 
# 樂天10萬回饋2500(2.5%)
# 遠銀百萬保費3.5%
pay:float = -10033* (1-discount) #-60570  #-59358.6
n_years = 6


lisIRR_death = []
for i, value in enumerate(death_insurance, 0):
    if i < n_years: #i=0,1,2
        cash_flow = [pay]*(i+1)+[death_insurance[i]]
    else:
        lis0 = [0]*(i-n_years+1)
        cash_flow = [pay]*n_years+lis0+[value]
    print(f"第{i+1:02d}年末死亡cashflow:",cash_flow)
    irr = npf.irr(cash_flow)
    lisIRR_death.append(irr)


for m,irr in enumerate(lisIRR_death,1):
    print(f"第{m:02d}年末({m+40}歲)死亡IRR:\t{irr:.4%}")

lisIRR_death = [f"{irr:.4%}" for irr in lisIRR_death]

dic={"死亡IRR":lisIRR_death , "年": list(range(1,len(death_insurance)+1))}
dfIRR_death = pd.DataFrame(dic).set_index("年")
#以"年"當index,以免cash_value跟death_insurance資料不一致
#這樣合併資料還可以正確


lisIRR = []
totReturn = []

for i, value in enumerate(cash_value, 0):
    if i < n_years: #i=0,1,2
        cash_flow = [pay]*(i+1)+[cash_value[i]]
        tot = sum(cash_flow)/abs(sum( [pay]*(i+1) ) )
    else:
        lis0 = [0]*(i-n_years+1)
        cash_flow = [pay]*n_years+lis0+[value]
        tot = sum(cash_flow)/abs(sum([pay]*n_years))
    print(f"第{i+1:02d}年末cashflow:",cash_flow)
    irr = npf.irr(cash_flow)
    lisIRR.append(irr)
    
    totReturn.append(tot)

lisIRRx2 = [] #0歲女其實是*2.1倍
for i, value in enumerate(cash_valueXrate, 0):
    if i < n_years: #i=0,1,2
        # cash_flow = [pay]*(i+1)+[cash_valueXrate[i]]
        cash_flow = [pay]*(i+1)+[value]
    else:
        lis0 = [0]*(i-n_years+1)
        cash_flow = [pay]*n_years+lis0+[value]
    print(f"第{i+1:02d}年末cashflow X rate:",cash_flow)
    irr = npf.irr(cash_flow)
    lisIRRx2.append(irr)
    

lisIRR = [f"{irr:.4%}" for irr in lisIRR]
totReturn = [f"{ele:.4%}" for ele in totReturn]
increasing_rate = [f"{ele:.4%}" for ele in increasing_rate]
# lisIRR_death = [f"{ele:.4%}" for ele in lisIRR_death]
lisIRRx2 =  [f"{irr:.4%}" for irr in lisIRRx2]


dic = {
    "年"           : list(range(1, len(cash_value)+1)),
    "IRR"          : lisIRR,
    "總報酬率"      : totReturn,
    "增加率"        : increasing_rate,
    #"解約金x2.1_IRR": lisIRRx2
    # "死亡IRR"     : lisIRR_death
    }

df = pd.DataFrame(dic).set_index("年")

df_concat = pd.concat([df,dfIRR_death],axis=1)
print("\n",df_concat)

cwd = os.getcwd()
exFolder = os.path.join(cwd,"export")
if not os.path.exists(exFolder):
    os.makedirs(exFolder)
xlsx_path = "\\".join( [exFolder,"irr.xlsx"] )
df_concat.to_excel(xlsx_path)

輸出的xlsx

不討論富邦的分紅達成率如何了
先假設達成率100%
(有可能高估了富邦的能力)
六年內解約皆為負報酬
七年保本
20年IRR 2.2%
低於台灣銀行一年期
 美金定存利率3.85%
以儲蓄險的角度來看
可說完全不及格
20年都無法勝定存
8.7分不能再高了
(滿分為1000分)

如果看完這種8.7分的IRR
您仍因為死亡IRR最高45%
而願意購買
儲蓄保險王絕對不會攔阻你
請在此谷歌表單留下聯繫資料:
https://forms.gle/6hPmWBUVyvS9GDxH9
請保經朋友幫你服務，
並感謝你的大方

本文不論解約還是死亡IRR
都算得清清楚楚，
依據金管會的標準
這涉及不當行銷
商品應該要下架
麻煩金管會趕快將這張
富邦的分紅保單下架

歡迎檢舉到金管會
#金管會吃屎!
也歡迎富邦業務員來打臉，
富邦那張儲蓄型保單
IRR可以超越5%?
才不像版主所述
張張都很弱
貼出建議書，
本站將代為免費廣告

保誠多重宇宙: 香港保單保誠雋富多元貨幣計劃IRR分析
同樣叫做保誠人壽
香港保誠有IRR超過5%的實力
台灣保誠愛美鑫IRR才4%
因金管會把國人當成次等公民
便以分紅公式太複雜的奇怪理由
強迫下架,
成為僅開賣16天的短命保單
之後若有新商品,
必然IRR更低
才符合金管會的心意
台灣與香港猶如多重宇宙

保誠愛美鑫下架同時
霉體妓者還大讚富邦分紅公式簡單清楚:
相較富邦人壽，在外幣分紅終身壽險保單條款附件的「分紅公式」就明白列出；年度保單紅利是利差加上死差的紅利，調整為可分配金額後再乘上分配給要保人的比例，終期保單紅利則是以資產額份為基礎，各項計算參數講得相對清楚。
這不是不當行銷的話
什麼才是不當行銷?
分紅公式是消費者關心的嗎?
我只關心分紅達成率能不能100%
IRR多少?
我管分紅怎麼算的幹嘛?
富邦分紅保單20年IRR仍輸定存
才是需要關注的重點吧?

看完這種8.7分的IRR
本來也是一笑置之
連文章都懶得寫
不過據說計算保單的IRR
涉及不當行銷
商品需要下架
現在要以踢爆黑心貨的角度
計算所有台灣黑心保單的IRR
直至官方建議書列出IRR
或者黑心商品都下架光為止

這種8.7分的黑心商品
請大家千萬不要上當
建議參考海外保單
金管會有本事就叫
香港保誠或忠意保險下架啊!
#金管會吃屎!
#香港保誠雋富多元貨幣計劃: https://lihi2.com/LVlHg/blog
#忠意保險跨越創富保2(五年期繳): https://lihi2.com/iQTrf/blog
#忠意保險跨越創富保2(二年期繳): https://lihi2.com/qvFk6/blog

若想了解IRR 5%的香港保單或其他台灣保單

複委託優惠或YTM超過6%的債券

請在此表單留下聯絡資料:

https://forms.gle/6hPmWBUVyvS9GDxH9

若您願意贊助我:

機構代號(391,一卡通),帳號:1501823311

FB粉絲團: 儲蓄保險王,

Line@: @wvr5039s,

Line社群: https://lihi1.com/MaSdv/blog

twitter: https://twitter.com/SavingKing925

TG: https://t.me/savingking

後記:
更為模組化的python code:

# -*- coding: utf-8 -*-
"""
Created on Tue May 23 18:57:45 2023

@author: SavingKing

03: 
    j,k合為同一個迴圈(死亡IRR),且使用enumerate
    df使用"年"當index,以免cash_value,death_insurance
    資料的年度不一致,還可以正確合併
04:
    修正未滿期時的總報酬率計算錯誤
05:
    模組化,刪除已經註解的保誠資料,__file__擷取當前py檔路徑
    輸出的xlsx檔名,可以跟py檔 主檔名相同
"""
import numpy_financial as npf
import numpy as np
import pandas as pd
import os

cash_value:list=[3705,  10019, 16618, 25014, 36514,
                 59644, 61605, 63621, 65695, 67809,
                 69908, 71975, 74042, 76104, 78143,
                 80167, 82170, 84174, 86175, 88167]  
#富邦人壽美富紅運外幣分紅終身壽險PFA 6年 #1~20年末解約金(上),死亡保額(下)
death_insurance:list=[10034, 23943, 39579, 55823, 72665,
                      264607,269510,274509,279604,284774,
                      289769,294579,297006,298837,300098,
                      300823,301045,300803,300136,299087]

capital_protection = 7 #7年末保本
discount = (0)/100 
# 2% 花旗,星展,華南 
# 樂天10萬回饋2500(2.5%)
# 遠銀百萬保費3.5%
pay:float = -10033* (1-discount) #-60570  #-59358.6
n_years = 6

def get_increasing_rate(capital_protection=capital_protection,
                        cash_value=cash_value,fmt_str=True):
    
    increasing_rate = [np.nan]*capital_protection 
    #從保本才開始算解約金增加率
    
    for i in range(capital_protection, len(cash_value)):
        increase = cash_value[i]/cash_value[i-1]-1
        increasing_rate.append(increase)
    if fmt_str == True:
        increasing_rate = [f"{ele:.4%}" for ele in increasing_rate]
    return increasing_rate #list

increasing_rate = \
get_increasing_rate(capital_protection=capital_protection,
                    cash_value=cash_value)


def get_lisIRR_totReturn(pay=pay, discount=discount,
                         n_years=n_years,
                         cash_value=cash_value, start=1,
                         fmt_str=True):

    lisIRR = []
    totReturn = []
    
    for i, value in enumerate(cash_value, start-1):
        if i < n_years: #i=0,1,2
            lis_pay=[pay]*(i+1)
            cash_flow = lis_pay+[value]
            tot = sum(cash_flow)/abs(sum( lis_pay ) )
        else:
            lis_pay=[pay]*n_years
            lis0 = [0]*(i-n_years+1)
            cash_flow = lis_pay+lis0+[value]
            tot = sum(cash_flow)/abs(sum( lis_pay ))
        print(f"第{i+1:02d}年末cashflow:",cash_flow)
        irr = npf.irr(cash_flow)
        lisIRR.append(irr)
        totReturn.append(tot)
    
    if fmt_str == True:
        lisIRR = [f"{ele:.4%}" for ele in lisIRR]
        totReturn = [f"{ele:.4%}" for ele in totReturn]
        
    return lisIRR,totReturn #list
    #return的縮排不要在for迴圈之內,不然lisIRR只會有一個元素

lisIRR,totReturn = get_lisIRR_totReturn(pay=pay,discount=discount,
                         n_years=n_years,
                         cash_value=cash_value,start=1)
# print("lisIRR:",lisIRR)

lisIRR_death,totReturn_death = \
get_lisIRR_totReturn(pay=pay,discount=discount,
                     n_years=n_years,
                     cash_value=death_insurance,start=1)

# =============================================================================
##lisIRR_death 要重複使用function get_lisIRR_totReturn
# lisIRR_death = []
# for i, value in enumerate(death_insurance, 0):
#     if i < n_years: #i=0,1,2
#         cash_flow = [pay]*(i+1)+[death_insurance[i]]
#     else:
#         lis0 = [0]*(i-n_years+1)
#         cash_flow = [pay]*n_years+lis0+[value]
#     print(f"第{i+1:02d}年末死亡cashflow:",cash_flow)
#     irr = npf.irr(cash_flow)
#     lisIRR_death.append(irr)
# 
# 
# for m,irr in enumerate(lisIRR_death,1):
#     print(f"第{m:02d}年末({m+40}歲)死亡IRR:\t{irr:.4%}")
# =============================================================================

# lisIRR_death = [f"{irr:.4%}" for irr in lisIRR_death]

dic={"死亡IRR":lisIRR_death ,"死亡總報酬率":totReturn_death, 
     "年": list(range(1,len(death_insurance)+1))}
dfIRR_death = pd.DataFrame(dic).set_index("年")
#以"年"當index,以免cash_value跟death_insurance資料不一致
#這樣合併資料還可以正確
  

# lisIRR = [f"{irr:.4%}" for irr in lisIRR]
# totReturn = [f"{ele:.4%}" for ele in totReturn]
# increasing_rate = [f"{ele:.4%}" for ele in increasing_rate]
# lisIRR_death = [f"{ele:.4%}" for ele in lisIRR_death]
# lisIRRx2 =  [f"{irr:.4%}" for irr in lisIRRx2]


dic = {
    "年"           : list(range(1, len(cash_value)+1)),
    "IRR"          : lisIRR,
    "總報酬率"      : totReturn,
    "增加率"        : increasing_rate,
    }

df = pd.DataFrame(dic).set_index("年")

df_concat = pd.concat([df,dfIRR_death],axis=1)
print("\n",df_concat)

cwd = os.getcwd()
exFolder = os.path.join(cwd,"export")
if not os.path.exists(exFolder):
    os.makedirs(exFolder)

# 獲取當前腳本的文件路徑
current_script_path = __file__
#'p:\\python\\financial\\富邦\\pfa-美富紅運30歲6年\\irr_05_富邦人壽美富紅運外幣分紅終身壽險6年.py'

# 提取主檔名
#main_filename = os.path.basename(current_script_path).split('.')[0]
main_filename = os.path.splitext(os.path.basename(current_script_path))[0]
"""
os.path.basename(current_script_path)
Out[21]: 'irr_05_富邦人壽美富紅運外幣分紅終身壽險6年.py'

os.path.splitext(os.path.basename(current_script_path))
Out[20]: ('irr_05_富邦人壽美富紅運外幣分紅終身壽險6年', '.py')
"""

# 打印主檔名
print("\npy主檔名:", main_filename)

xlsx_path = "\\".join( [exFolder,f"{main_filename}.xlsx"] )
df_concat.to_excel(xlsx_path)
print(f"\nxlsx檔已經輸出到:\n{xlsx_path}")