pyalgotrade_mootdx 0.1.1

pyalgotrade mootdx module

PyAlgoTrade mootdx module
=========================
此项目是 PyAlgoTrade [mootdx](https://github.com/bopo/mootdx) (基于 pytdx 的二次封装版本) 的一个数据源

一个简单的用法:

```
from pyalgotrade import plotter, strategy
from pyalgotrade.bar import Frequency
from pyalgotrade.barfeed.csvfeed import GenericBarFeed
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.technical import ma

from pyalgotrade_mootdx import tools


class Strategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument):
super(Strategy, self).__init__(feed)

self.__position = None
self.__sma = ma.SMA(feed[instrument].getCloseDataSeries(), 150)
self.__instrument = instrument
self.getBroker()

def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
self.info("买入 %.2f" % (execInfo.getPrice()))

def onEnterCanceled(self, position):
self.__position = None

def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
self.info("卖出 %.2f" % (execInfo.getPrice()))
self.__position = None

def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
self.__position.exitMarket()

def getSMA(self):
return self.__sma

def onBars(self, bars):
# 每一个数据都会抵达这里，就像becktest中的next
# Wait for enough bars to be available to calculate a SMA.
if self.__sma[-1] is None:
return

# bar.getTyoicalPrice = (bar.getHigh() + bar.getLow() + bar.getClose())/ 3.0
bar = bars[self.__instrument]

# If a position was not opened, check if we should enter a long position.
if self.__position is None:
if bar.getPrice() > self.__sma[-1]:
# 开多头.
self.__position = self.enterLong(self.__instrument, 100, True)

# 平掉多头头寸.
elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():
self.__position.exitMarket()


def main():
instruments = ["600036"]
feeds = tools.build_feed(instruments, 2017, 2018, "histdata")

# 3.实例化策略
strat = Strategy(feeds, instruments[0])

# 4.设置指标和绘图
ratio = sharpe.SharpeRatio()
strat.attachAnalyzer(ratio)
plter = plotter.StrategyPlotter(strat)

# 5.运行策略
strat.run()
strat.info("最终收益: %.2f" % strat.getResult())

# 6.输出夏普率、绘图
strat.info("夏普比率: " + str(ratio.getSharpeRatio(0)))
# plter.plot()


if __name__ == '__main__':
main()
```

```
2018-04-03 00:00:00 strategy [INFO] 卖出 28.86
2018-04-11 00:00:00 strategy [INFO] 买入 30.34
2018-04-17 00:00:00 strategy [INFO] 卖出 28.25
2018-05-02 00:00:00 strategy [INFO] 买入 29.98
2018-05-04 00:00:00 strategy [INFO] 卖出 29.28
2018-05-09 00:00:00 strategy [INFO] 买入 29.70
2018-05-24 00:00:00 strategy [INFO] 卖出 29.60
2018-09-25 00:00:00 strategy [INFO] 买入 29.83
2018-10-12 00:00:00 strategy [INFO] 卖出 28.70
2018-10-15 00:00:00 strategy [INFO] 买入 29.16
2018-10-19 00:00:00 strategy [INFO] 卖出 27.75
2018-10-22 00:00:00 strategy [INFO] 买入 29.53
2018-10-30 00:00:00 strategy [INFO] 卖出 28.12
2018-11-01 00:00:00 strategy [INFO] 买入 29.45
2018-11-15 00:00:00 strategy [INFO] 卖出 28.24
2018-11-19 00:00:00 strategy [INFO] 买入 28.70
2018-11-23 00:00:00 strategy [INFO] 卖出 28.29
2018-12-03 00:00:00 strategy [INFO] 买入 29.49
2018-12-11 00:00:00 strategy [INFO] 卖出 28.35
2018-12-12 00:00:00 strategy [INFO] 买入 29.00
2018-12-18 00:00:00 strategy [INFO] 卖出 28.05
2018-12-21 13:48:01,740 strategy [INFO] 最终收益: 999254.00
2018-12-21 13:48:01,740 strategy [INFO] 夏普比率: -0.6957113853538597
```