Seeing that there is no publicly available python shark strategy on the platform, I wrote a simple shark-throwing blog of my own. It's not as good as the original, but it's better than the original, and it's not as good as the original.
Opening: Overtaking Dongjian on the opening day Hike: Hike above the previous price of 0.5ATR Stop-loss stop-loss: All stops are stopped if the last trade price - 2ATR drops or falls below the track
One year data was revised, yearly 80%, maximum retracement 16%.
The use of cash is lower, and the return on the contract version is higher.
'''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)