初始资金为 100 万

好的，以下是一个更新的代码示例，考虑初始资金和最大亏损的影响：

import tushare as ts
import numpy as np

# 获取沪深300指数数据
hs300 = ts.get_hist_data('hs300')

# 计算5日和20日移动平均线
hs300['ma5'] = hs300['close'].rolling(window=5).mean()
hs300['ma20'] = hs300['close'].rolling(window=20).mean()

# 计算交易信号
hs300['signal'] = np.where(hs300['ma5'] > hs300['ma20'], 1, 0)

# 计算持仓情况
hs300['position'] = hs300['signal'].shift(1)

# 计算收益率
hs300['return'] = np.log(hs300['close'] / hs300['close'].shift(1))

# 计算策略收益率
hs300['strategy_return'] = hs300['position'] * hs300['return']

# 计算交易手续费
hs300['fee'] = abs(hs300['position'] - hs300['position'].shift(1)) * hs300['close'] * 0.0005

# 计算每日保证金
hs300['margin'] = hs300['close'] * 300 * 0.1

# 计算可用资金
hs300['available_fund'] = 1000000 - hs300['margin'].shift(1) - hs300['fee'].shift(1)

# 计算账户净值
hs300['nav'] = hs300['available_fund'] + hs300['strategy_return']

# 计算最大回撤
hs300['max_drawdown'] = (hs300['nav'].cummax() - hs300['nav']) / hs300['nav'].cummax()

# 判断是否爆仓
hs300['margin_call'] = np.where(hs300['max_drawdown'] >= 0.5, 1, 0)

# 计算当前持仓量
hs300['position_size'] = hs300['position'] * 300

# 计算当前持仓市值
hs300['position_value'] = hs300['close'] * hs300['position_size']

# 计算当前持仓盈亏
hs300['position_pnl'] = hs300['position_size'] * hs300['return']

# 计算账户总资产
hs300['total_asset'] = hs300['nav'].shift(1) + hs300['position_value'].shift(1) + hs300['position_pnl'].shift(1)

# 计算账户可用资金
hs300['available_fund'] = hs300['total_asset'] - hs300['margin'].shift(1) - hs300['fee'].shift(1)

# 计算账户净值
hs300['nav'] = hs300['available_fund'] + hs300['strategy_return']

# 计算最大亏损
hs300['max_loss'] = (hs300['nav'].cummax() - hs300['nav']) / hs300['nav'].cummax()

# 判断是否爆仓
hs300['margin_call'] = np.where(hs300['max_loss'] >= 0.5, 1, 0)

# 输出结果
print(hs300.tail())

这个策略在原有的基础上增加了持仓量、持仓市值、持仓盈亏、账户总资产、账户可用资金、最大亏损等指标的计算。我们假设每手期货交易量为300，因此当前持仓量为持仓标志位乘以300。我们还计算了当前持仓市值和持仓盈亏，用于计算账户总资产。在计算账户可用资金和账户净值时，需要减去前一天的保证金和手续费。我们还计算了最大亏损，当最大亏损达到50%时，我们认为账户已经爆仓，交易应该停止。