海龟交易系统所代表的传统CTA策略是不是过时了？

大家感受一下海龟交易系统的代码——只有在这种场景下，也就是精细化的仓位管理，比如向上突破一次，加仓多少个ATR这样的逻辑。

ize = 0
    self.buy_count = 0
    # 海龟交易法则中的唐奇安通道和平均波幅ATR        
    self.H_line = bt.indicators.Highest(self.data.high(-1), period=self.p.long_period)
    self.L_line = bt.indicators.Lowest(self.data.low(-1), period=self.p.short_period)
    self.TR = bt.indicators.Max((self.data.high(0) - self.data.low(0)), \
                                abs(self.data.close(-1) - self.data.high(0)), \
                                abs(self.data.close(-1) - self.data.low(0)))
    self.ATR = bt.indicators.SimpleMovingAverage(self.TR, period=14)
    # 价格与上下轨线的交叉      
    self.buy_signal = bt.ind.CrossOver(self.data.close(0), self.H_line)
    self.sell_signal = bt.ind.CrossOver(self.data.close(0), self.L_line)

def next(self):
    if self.order:
        return
        # 入场：价格突破上轨线且空仓时        
    if self.buy_signal > 0 and self.buy_count == 0:

        self.buy_size = self.broker.getvalue() * 0.01 / self.ATR
        self.buy_size = int(self.buy_size / 100) * 100
        self.sizer.p.stake = self.buy_size
        self.buy_count = 1
        print('空仓时买入', self.buy_size)
        self.order = self.buy()
        # 加仓：价格上涨了买入价的0.5的ATR且加仓次数少于3次（含）        
    elif self.data.close > self.buyprice + 0.5 * self.ATR[0] and self.buy_count > 0 and self.buy_count <= 4:
        print('加仓买入')
        self.buy_size = self.broker.getvalue() * 0.01 / self.ATR
        self.buy_size = int(self.buy_size / 100) * 100
        self.sizer.p.stake = self.buy_size
        self.order = self.buy()
        self.buy_count += 1
        # 离场：价格跌破下轨线且持仓时        
    elif self.sell_signal < 0 and self.buy_count > 0:
        print('平仓信号卖出')
        self.order = self.sell()
        self.buy_count = 0
        # 止损：价格跌破买入价的2个ATR且持仓时        
    elif self.data.close < (self.buyprice - 2 * self.ATR[0]) and self.buy_count > 0:
        print('止损信号卖出')
        self.order = self.sell()
        self.buy_count = 0

        # 交易记录日志（默认不打印结果）

def log(self, txt, dt=None, doprint=False):
    if self.params.printlog or doprint:
        dt = dt or self.datas[0].datetime.date(0)
        print(f'{dt.isoformat()},{txt}')

# 记录交易执行情况（默认不输出结果）
def notify_order(self, order):
    # 如果order为submitted/accepted,返回空
    if order.status in [order.Submitted, order.Accepted]:
        return
    # 如果order为buy/sell executed,报告价格结果
    if order.status in [order.Completed]:
        if order.isbuy():
            self.log(f'买入:\n价格:{order.executed.price},\
            成本:{order.executed.value},\
            手续费:{order.executed.comm}')

            self.buyprice = order.executed.price
            self.buycomm = order.executed.comm
        else:
            self.log(f'卖出:\n价格：{order.executed.price},\
            成本: {order.executed.value},\
            手续费{order.executed.comm}')

        self.bar_executed = len(self)

        # 如果指令取消/交易失败, 报告结果
    elif order.status in [order.Canceled, order.Margin, order.Rejected]:
        self.log('交易失败')
    self.order = None

# 记录交易收益情况（可省略，默认不输出结果）
def notify_trade(self, trade):
    if not trade.isclosed:
        return
    self.log(f'策略收益：\n毛收益 {trade.pnl:.2f}, 净收益 {trade.pnlcomm:.2f}')

def stop(self):
    self.log(f'(组合线：{self.p.long_period},{self.p.short_period})；\
    期末总资金: {self.broker.getvalue():.2f}', doprint=True)