看到平台上没有公开的python海龟策略,自己写个简单的抛个砖。 接近原版的海龟系统,没怎么优化,当做回测试验吧,也可以自己再优化下接实盘跑。
开仓:超过唐奇安上轨开仓 加仓:超过之前的价格的0.5ATR就加仓 止损止盈:跌破下轨或者跌破上次开仓价-2ATR就全部止盈
回测了1年数据,年化80%,最大回撤16%
现货资金利用率较低,改成合约版后收益会更高。
'''backtest start: 2019-01-01 00:00:00 end: 2020-03-02 00:00:00 period: 1d exchanges: [{"eid":"OKEX","currency":"BTC_USDT","stocks":0}] args: [["fresh_rete",24],["DC_range",20],["atrlength",14]] ''' import numpy as np import pandas as pd import datetime data = {'ordertime':[],'id':[],'price':[]} hisorder = pd.DataFrame(data) def turtle(): #声明全局变量 global hisorder acct = exchange.GetAccount() records=exchange.GetRecords(fresh_rete*60*60) ticker = exchange.GetTicker() portfolio_value = acct.Balance+acct.FrozenBalance+(acct.Stocks+acct.FrozenStocks)*records[-1]['Close'] atr = TA.ATR(records, atrlength)[-1] #计算得到unit大小 value = portfolio_value*trade_percent unit = min(round(value/atr,4),round(acct.Balance/(ticker['Last']+100),4)) #unit = round(value/atr,2) df = pd.DataFrame(records) current_price = records[-1]['Close'] last_price = 0 if len(hisorder)!=0: last_price = hisorder.iloc[-1]['price'] max_price = df[-DC_range:-2]['High'].max() min_price = df[-int(DC_range/2):-2]['Low'].min() opensign = len(hisorder)==0 and current_price > max_price addsign = len(hisorder)!=0 and current_price > last_price + 0.5*atr stopsign = len(hisorder)!=0 and current_price < min_price closesign = len(hisorder)!=0 and current_price < (last_price - 2*atr) # if _D(records[-1]['Time']/1000) == '2020-01-25 00:00:00': # Log("records[-1]",records[-1]) if opensign | addsign: if acct.Balance >= (ticker['Last']+10)*unit and unit >0: id = exchange.Buy(ticker['Last']+10,unit) orderinfo = exchange.GetOrder(id) data = {'ordertime':_D(records[-1]['Time']/1000),'id':id,'price':records[-1]['Close']} hisorder = hisorder.append(data,ignore_index=True) Log('买入后,最新账户信息:', exchange.GetAccount()) Log("opensign",opensign,"addsign",addsign) # else: # Log('余额已不足,请充值......', exchange.GetAccount()) if stopsign | closesign: exchange.Sell(-1, acct.Stocks+acct.FrozenStocks) data = {'ordertime':[],'id':[],'price':[]} hisorder = pd.DataFrame(data) Log('卖出后,最新账户信息:', exchange.GetAccount()) Log("stopsign",stopsign,"closesign",closesign) def main(): while True: turtle() Sleep(fresh_rete*60*60*1000)template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6