移植自JavaScript版本的「商品期货跨期对冲 - 百行代码实现」，本策略为简单的教学策略，意图展示Python语言的商品期货策略设计。主要用于学习策略编写、参考设计思路。
class Hedge:
'对冲控制类'
def __init__(self, q, e, initAccount, symbolA, symbolB, hedgeSpread, coverSpread):
self.q = q
self.initAccount = initAccount
self.status = 0
self.symbolA = symbolA
self.symbolB = symbolB
self.e = e
self.isBusy = False
self.hedgeSpread = hedgeSpread
self.coverSpread = coverSpread
self.opAmount = OpAmount
def poll(self):
if (self.isBusy or not exchange.IO("status")) or not ext.IsTrading(self.symbolA):
Sleep(1000)
return
insDetailA = exchange.SetContractType(self.symbolA)
if not insDetailA:
return
tickerA = exchange.GetTicker()
if not tickerA:
return
insDetailB = exchange.SetContractType(self.symbolB)
if not insDetailB:
return
tickerB = exchange.GetTicker()
if not tickerB:
return
LogStatus(_D(), "A卖B买", _N(tickerA["Buy"] - tickerB["Sell"]), "A买B卖", _N(tickerA["Sell"] - tickerB["Buy"]))
action = 0
if self.status == 0:
if (tickerA["Buy"] - tickerB["Sell"]) > self.hedgeSpread:
Log("开仓 A卖B买", tickerA["Buy"], tickerB["Sell"], "#FF0000")
action = 1
elif (tickerB["Buy"] - tickerA["Sell"]) > self.hedgeSpread:
Log("开仓 B卖A买", tickerB["Buy"], tickerA["Sell"], "#FF0000")
action = 2
elif self.status == 1 and (tickerA["Sell"] - tickerB["Buy"]) <= self.coverSpread:
Log("平仓 A买B卖", tickerA["Sell"], tickerB["Buy"], "#FF0000")
action = 2
elif self.status == 2 and (tickerB["Sell"] - tickerA["Buy"]) <= self.coverSpread:
Log("平仓 B买A卖", tickerB["Sell"] - tickerA["Buy"], "#FF0000")
action = 1
if action == 0:
return
self.isBusy = True
tasks = []
if action == 1:
tasks.append([self.symbolA, "sell" if self.status == 0 else "closebuy"])
tasks.append([self.symbolB, "buy" if self.status == 0 else "closesell"])
elif action == 2:
tasks.append([self.symbolA, "buy" if self.status == 0 else "closesell"])
tasks.append([self.symbolB, "sell" if self.status == 0 else "closebuy"])
def callBack(task, ret):
def callBack(task, ret):
self.isBusy = False
if task["action"] == "sell":
self.status = 2
elif task["action"] == "buy":
self.status = 1
else:
self.status = 0
account = _C(exchange.GetAccount)
LogProfit(account["Balance"] - self.initAccount["Balance"], account)
self.q.pushTask(self.e, tasks[1][0], tasks[1][1], self.opAmount, callBack)
self.q.pushTask(self.e, tasks[0][0], tasks[0][1], self.opAmount, callBack)
def main():
SetErrorFilter("ready|login|timeout")
Log("正在与交易服务器连接...")
while not exchange.IO("status"):
Sleep(1000)
Log("与交易服务器连接成功")
initAccount = _C(exchange.GetAccount)
Log(initAccount)
n = 0
def callBack(task, ret):
Log(task["desc"], "成功" if ret else "失败")
q = ext.NewTaskQueue(callBack)
if CoverAll:
Log("开始平掉所有残余仓位...")
ext.NewPositionManager().CoverAll()
Log("操作完成")
t = Hedge(q, exchange, initAccount, SA, SB, HedgeSpread, CoverSpread)
while True:
q.poll()
t.poll()
只是移植一下代码，感觉有点太简单了，我们继续来做一些改造，给策略加上图表。
在LogStatus函数调用的位置之前加上以下代码，把实时的价格差做成K线统计出来，self.preBarTime是Hedge类增加的一个成员，用来记录最新BAR的时间戳，画图我们使用「画线类库」，直接调用画图接口，很简单就可以画出图表。
# 计算差价K线
r = exchange.GetRecords()
if not r:
return
diff = tickerB["Last"] - tickerA["Last"]
if r[-1]["Time"] != self.preBarTime:
# 更新
self.records.append({"Time": r[-1]["Time"], "High": diff, "Low": diff, "Open": diff, "Close": diff, "Volume": 0})
self.preBarTime = r[-1]["Time"]
if diff > self.records[-1]["High"]:
self.records[-1]["High"] = diff
if diff < self.records[-1]["Low"]:
self.records[-1]["Low"] = diff
self.records[-1]["Close"] = diff
ext.PlotRecords(self.records, "diff:B-A")
ext.PlotHLine(self.hedgeSpread if diff > 0 else -self.hedgeSpread, "hedgeSpread")
ext.PlotHLine(self.coverSpread if diff > 0 else -self.coverSpread, "coverSpread")
回测时的效果：
接下来，我们再加入交互功能，让策略在运行时可以修改HedgeSpread和CoverSpread参数，控制对冲开仓差价、平仓差价。还需要一个一键平仓的按钮。我们在策略编辑页面增加这几个控件。
然后在策略的主循环中，q.poll(),t.poll()调用之后，加上交互控制代码。
while True:
q.poll()
t.poll()
# 以下交互控制代码
cmd = GetCommand()
if cmd:
arr = cmd.split(":")
if arr[0] == "AllCover":
p.CoverAll()
elif arr[0] == "SetHedgeSpread":
t.SetHedgeSpread(float(arr[1]))
elif arr[0] == "SetCoverSpread":
t.SetCoverSpread(float(arr[1]))
策略用于教学，实盘根据自身需求优化调整。
如有问题，欢迎留言。
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