# 你好，算法交易！

> 原文：[`www.backtrader.com/home/helloalgotrading/`](https://www.backtrader.com/home/helloalgotrading/)

一个经典的*简单移动平均线交叉*策略，可以轻松地以不同方式实现。下面呈现的三个片段的结果和图表是相同的。

![image](img/80e7046cb8ec40277514e948183e2afa.png)

```py
`from datetime import datetime
import backtrader as bt

# Create a subclass of Strategy to define the indicators and logic

class SmaCross(bt.Strategy):
    # list of parameters which are configurable for the strategy
    params = dict(
        pfast=10,  # period for the fast moving average
        pslow=30   # period for the slow moving average
    )

    def __init__(self):
        sma1 = bt.ind.SMA(period=self.p.pfast)  # fast moving average
        sma2 = bt.ind.SMA(period=self.p.pslow)  # slow moving average
        self.crossover = bt.ind.CrossOver(sma1, sma2)  # crossover signal

    def next(self):
        if not self.position:  # not in the market
            if self.crossover > 0:  # if fast crosses slow to the upside
                self.buy()  # enter long

        elif self.crossover < 0:  # in the market & cross to the downside
            self.close()  # close long position

cerebro = bt.Cerebro()  # create a "Cerebro" engine instance

# Create a data feed
data = bt.feeds.YahooFinanceData(dataname='MSFT',
                                 fromdate=datetime(2011, 1, 1),
                                 todate=datetime(2012, 12, 31))

cerebro.adddata(data)  # Add the data feed

cerebro.addstrategy(SmaCross)  # Add the trading strategy
cerebro.run()  # run it all
cerebro.plot()  # and plot it with a single command` 
```

```py
`from datetime import datetime
import backtrader as bt

# Create a subclass of Strategy to define the indicators and logic

class SmaCross(bt.Strategy):
    # list of parameters which are configurable for the strategy
    params = dict(
        pfast=10,  # period for the fast moving average
        pslow=30   # period for the slow moving average
    )

    def __init__(self):
        sma1 = bt.ind.SMA(period=self.p.pfast)  # fast moving average
        sma2 = bt.ind.SMA(period=self.p.pslow)  # slow moving average
        self.crossover = bt.ind.CrossOver(sma1, sma2)  # crossover signal

    def next(self):
        if not self.position:  # not in the market
            if self.crossover > 0:  # if fast crosses slow to the upside
                self.order_target_size(target=1)  # enter long

        elif self.crossover < 0:  # in the market & cross to the downside
            self.order_target_size(target=0)  # close long position

cerebro = bt.Cerebro()  # create a "Cerebro" engine instance

# Create a data feed
data = bt.feeds.YahooFinanceData(dataname='MSFT',
                                 fromdate=datetime(2011, 1, 1),
                                 todate=datetime(2012, 12, 31))

cerebro.adddata(data)  # Add the data feed

cerebro.addstrategy(SmaCross)  # Add the trading strategy
cerebro.run()  # run it all
cerebro.plot()  # and plot it with a single command` 
```

```py
`from datetime import datetime
import backtrader as bt

# Create a subclass of SignaStrategy to define the indicators and signals

class SmaCross(bt.SignalStrategy):
    # list of parameters which are configurable for the strategy
    params = dict(
        pfast=10,  # period for the fast moving average
        pslow=30   # period for the slow moving average
    )

    def __init__(self):
        sma1 = bt.ind.SMA(period=self.p.pfast)  # fast moving average
        sma2 = bt.ind.SMA(period=self.p.pslow)  # slow moving average
        crossover = bt.ind.CrossOver(sma1, sma2)  # crossover signal
        self.signal_add(bt.SIGNAL_LONG, crossover)  # use it as LONG signal

cerebro = bt.Cerebro()  # create a "Cerebro" engine instance

# Create a data feed
data = bt.feeds.YahooFinanceData(dataname='MSFT',
                                 fromdate=datetime(2011, 1, 1),
                                 todate=datetime(2012, 12, 31))

cerebro.adddata(data)  # Add the data feed

cerebro.addstrategy(SmaCross)  # Add the trading strategy
cerebro.run()  # run it all
cerebro.plot()  # and plot it with a single command` 
```
