定投优化策略与 Python 实现

import pandas as pd

# 设置 pandas 显示选项
pd.set_option(‘expand_frame_repr’, False)

# ===读取数据
df = pd.read_csv(‘C:/indwxyz/pythonProject/Reference_Documents/HUICE/btc_usdt_1D_2025_0123.csv’)
df = df[[‘candle_begin_time’, ‘close’]] # 只保留时间和收盘价

# ===确保时间列为日期格式
df[‘candle_begin_time’] = pd.to_datetime(df[‘candle_begin_time’])

# ===按时间升序排序并重置索引
df = df.sort_values(by=’candle_begin_time’, ascending=True).reset_index(drop=True)

# ===选取特定时间段
df = df[(df[‘candle_begin_time’] >= ‘2021-11-10’) & (df[‘candle_begin_time’] <= ‘2024-03-08’)]

# ===重置索引以确保索引连续
df = df.reset_index(drop=True)

# ===初始化资金和数量
df[‘每次投入资金’] = 0.0
df[‘累计投入资金’] = 0.0
df[‘每次买币数量’] = 0.0
df[‘累计买币数量’] = 0.0
df[‘平均持有成本’] = 0.0
df[‘市值’] = 0.0

# ===设置手续费
c_rate = 0.008

# ===逐行计算定投逻辑
for i in range(len(df)): # 使用连续索引迭代
current_price = df.loc[i, ‘close’]
if i == 0:
investment = 3.0 # 初始投资金额
quantity = investment / current_price * (1 – c_rate)

df.loc[i, ‘每次投入资金’] = investment
df.loc[i, ‘累计投入资金’] = investment
df.loc[i, ‘每次买币数量’] = quantity
df.loc[i, ‘累计买币数量’] = quantity
df.loc[i, ‘平均持有成本’] = investment / quantity
else:
prev_total_investment = df.loc[i – 1, ‘累计投入资金’]
prev_total_quantity = df.loc[i – 1, ‘累计买币数量’]
avg_cost = df.loc[i – 1, ‘平均持有成本’]

investment = 6.0 if current_price < avg_cost else 3.0
quantity = investment / current_price * (1 – c_rate)

df.loc[i, ‘每次投入资金’] = investment
df.loc[i, ‘累计投入资金’] = prev_total_investment + investment
df.loc[i, ‘每次买币数量’] = quantity
df.loc[i, ‘累计买币数量’] = prev_total_quantity + quantity
df.loc[i, ‘平均持有成本’] = (prev_total_investment + investment) / (prev_total_quantity + quantity)

df.loc[i, ‘市值’] = df.loc[i, ‘累计买币数量’] * current_price

# ===计算盈亏和收益率
df[‘盈亏’] = df[‘市值’] – df[‘累计投入资金’]
df[‘收益率’] = df[‘盈亏’] / df[‘累计投入资金’]

# ===输出数据
print(df[[‘candle_begin_time’, ‘close’, ‘每次投入资金’, ‘累计投入资金’, ‘每次买币数量’, ‘累计买币数量’, ‘平均持有成本’, ‘市值’, ‘盈亏’, ‘收益率’]])
print(df[‘收益率’].max())