DCA_Everyday.py

import pandas as pd
from twstock import Stock
import argparse


def parse():
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--etf_code", type=str, default="00733",
    )
    parser.add_argument(
        "--year", type=int, default="2018",
    )
    parser.add_argument(
        "--month", type=int, default="9",
    )

    return parser

# 獲取ETF的歷史價格數據
def get_etf_history_data(etf_code, year, month):
    stock = Stock(etf_code)
    history_data = stock.fetch_from(year, month)

    name_attribute = ['Date', 'Capacity', 'Turnover', 'Open', 'High', 'Low', 'Close', 'Change','Transcation']

    df = pd.DataFrame(columns=name_attribute, data=history_data)

    return df


# 主程式
if __name__ == "__main__":
    # 定義ETF的代碼
    args = parse().parse_args()

    df = get_etf_history_data(args.etf_code, args.year, args.month)

    # 假設每個交易日投入200元
    investment_per_day = 300

    df['Shares_Purchased'] = investment_per_day / df['Close']

    total_investment = investment_per_day* len(df)

    # 計算資產終值
    final_value = df['Shares_Purchased'].sum()*df['Close'].iloc[-1]
    
    # 計算報酬率
    overall_return = (final_value - total_investment) / total_investment

    # 打印結果
    print("整體報酬率: {:.2%}".format(overall_return))
    print("總投入資金: {:.2f}元".format(total_investment))
    print("資產終值: {:.2f}元".format(final_value))
    print("淨收益: {:.2f}元".format(final_value-total_investment))