def __init__(self):
first, second = self.datas[0], self.datas[1]
beta = btind.SMA(first, period=self.p.period) / btind.SMA(
second, period=self.p.period)
spread = first - (beta * second)
self.lines.signal = (spread - btind.SMA(spread, period=self.p.period)
) / btind.StdDev(spread, period=self.p.period)
def __init__(self, args):
print("[Loading strategy]")
self.update = args.update_memory
## Updating params with input args ##
self.p.stoploss, self.p.takeprofit = args.stoploss, args.takeprofit
self.p.rsi_period = args.rsi_period
self.p.ema_period = args.ema_period
self.p.fast_period = args.fast_period
self.p.slow_period = args.slow_period
self.p.atr_period = args.atr_period
## Indicators Data ##
self.rsi = btind.RSI_EMA(period=self.p.rsi_period)
self.ema = btind.EMA(period=self.p.ema_period)
self.fast = btind.SMA(period=self.p.fast_period)
self.slow = btind.SMA(period=self.p.slow_period)
self.sar = btind.PSAR(period=self.p.sar_period,
af=self.p.sar_step,
afmax=self.p.sar_max)
self.order = None
self.tp, self.sl = None, None
self.data_name = 'AIBot'
self._close = []
self._rsi = []
self._fast = []
self._slow = []
self._sar = []
self.inc = 0
def __init__(self):
self.benchmark = self.getdatabyname(self.p.benchmark_name)
self.inds = dict()
for d in self.datas :
if d._name == self.p.benchmark_name :
continue
self.inds[d] = dict()
self.inds[d]['rsc'] = RSC.rsc(d,self.benchmark,subplot=False)
self.inds[d]['rscma'] = btind.SMA(self.inds[d]['rsc'],period=10)
self.inds[d]['rscCrossUpCondition'] = btind.crossover.CrossUp(self.inds[d]['rsc'], self.inds[d]['rscma'])
self.inds[d]['rscu'] = rscu.rscu(d,self.benchmark,subplot=False)
self.inds[d]['hrscu'] = self.inds[d]['rscu'].l.hrscu
self.inds[d]['lrscd'] = self.inds[d]['rscu'].l.lrscd
self.inds[d]['csma200'] = btind.SMA(d.close,period=200)
self.inds[d]['order'] = None
self.inds[d]['tradeNo'] = 0
self.inds[d]['counter'] = 0
self.inds[d]['eligible'] = False
self.bar_counter = 0
self.highest_lowest = []
hi, lo = self.data.high, self.data.low
def __init__(self):
self.sma_vel = btind.SMA(period=self.p.Med_vel)
self.sma_len = btind.SMA(period=self.p.Med_len)
self.buysig = btind.CrossOver(self.sma_vel, self.sma_len)
self.dataclose = self.datas[0].close
def __init__(self, args):
print("[Loading strategy]")
## Memory Params ##
self.update = args.update_memory
self.mem_close = memory.content(filename="close.dat", exists=True)
self.mem_rsi = memory.content(filename="rsi.dat", exists=True)
self.mem_fast = memory.content(filename="fast.dat", exists=True)
self.mem_slow = memory.content(filename="slow.dat", exists=True)
self.mem_sar = memory.content(filename="sar.dat", exists=True)
self.mem_results = memory.content(filename="results.dat", exists=True)
res = self.mem_results.getdata()
self.mem_close.train(num_layers=self.p.feature_window, results=res)
self.mem_rsi.train(num_layers=self.p.feature_window, results=res)
self.mem_fast.train(num_layers=self.p.feature_window, results=res)
self.mem_slow.train(num_layers=self.p.feature_window, results=res)
self.mem_sar.train(num_layers=self.p.feature_window, results=res)
self.p.stoploss, self.p.takeprofit = args.stoploss, args.takeprofit
## Indicators Data ##
self.rsi = btind.RSI_EMA(period=self.p.rsi_period)
self.ema = btind.EMA(period=self.p.ema_period)
self.fast = btind.SMA(period=self.p.fast_period)
self.slow = btind.SMA(period=self.p.slow_period)
self.sar = btind.PSAR(period=self.p.sar_period,
af=self.p.sar_step,
afmax=self.p.sar_max)
self.tp, self.sl = None, None
self.order = None
self.inc = 0
def __init__(self):
"""Initialize the strategy"""
self.fastma = dict()
self.slowma = dict()
self.regime = dict()
if self.params.var1 > self.params.var2:
vfast = self.params.var1
self.params.var1 = self.params.var2
self.params.var2 = vfast
for d in self.getdatanames():
# The moving averages
self.fastma[d] = btind.SMA(
self.getdatabyname(d), # The symbol for the moving average
period=self.params.var1, # Fast moving average
plotname="FastMA: " + d)
self.slowma[d] = btind.SMA(
self.getdatabyname(d), # The symbol for the moving average
period=self.params.var2, # Slow moving average
plotname="SlowMA: " + d)
# Get the regime
self.regime[d] = self.fastma[d] - self.slowma[
d] # Positive when bullish
def __init__(self):
self.inds = dict()
for d in self.datas:
if d._name == self.p.benchmark_name:
continue
self.inds[d] = dict()
self.inds[d]['csma200'] = btind.SMA(d.close, period=200)
self.inds[d]['dmi'] = dmi_inds.BCH(d, subplot=False)
self.inds[d]['bbh'] = self.inds[d]['dmi'].bbh
self.inds[d]['adx'] = btind.AverageDirectionalMovementIndex(
d, period=14, subplot=False)
self.inds[d]['adxma'] = btind.SMA(self.inds[d]['adx'], period=2)
self.inds[d]['rbbhl'] = RBBBHL.RBBHL(d, subplot=False)
self.inds[d]['hbb'] = self.inds[d]['rbbhl'].hbb
self.inds[d]['order'] = None
self.inds[d]['sellStop'] = None
self.inds[d]['onceTrue'] = False
self.inds[d]['sell_condition'] = btind.crossover.CrossDown(
self.inds[d]['adx'], self.inds[d]['adxma'])
self.inds[d]['bar_counter'] = 0
def __init__(self):
self.dataclose = self.datas[0].close
self.datavolume = self.datas[0].volume
# self.datape200 = self.datas[0].pe200
# self.datape1000 = self.datas[0].pe1000
self.ts_code = self.params.ts_code
self.startDate = self.params.startDate
self.endDate = self.params.endDate
self.dividentData = None
# 待处理的股利股息
self.stk_div = None
# 待处理的现金股息
self.cash_div = None
self.order = None
self.buyprice = None
self.buycomm = None
# 读取除权除息数据
self.getDivident()
# 添加移动平均指标
self.sma = bt.indicators.SimpleMovingAverage(self.datas[0],
period=self.params.maperiod)
# 添加自定义指标
# self.ssa = Ssa(ssa_window=self.params.ssa_window, subplot=False)
# self.pehist = Pehist(subplot=False)
btind.SMA(self.data.pe, period=1, subplot=True, plotname='pe')
btind.SMA(self.data.pe200, period=1, subplot=True, plotname='pe200')
btind.SMA(self.data.pe1000, period=1, subplot=True, plotname='pe1000')
def __init__(self):
self.sma_small_tf = btind.SMA(self.data, period=self.p.period)
bt.indicators.MACD(self.data0)
if not self.p.onlydaily:
self.sma_large_tf = btind.SMA(self.data1, period=self.p.period)
bt.indicators.MACD(self.data1)
def __init__(self):
# Keep a reference to the "close" line in the data[0] dataseries
self.dataclose = self.datas[0].close
# To keep track of pending orders and buy price/commission
self.order = None
self.buyprice = None
self.buycomm = None
btind.SMA(self.data.vp, period=1, subplot=True)
btind.SMA(self.data.q_g, period=1, subplot=True)
def __init__(self):
# 指标函数也支持简写 SimpleMovingAverage → SMA
# 最简方式：直接省略指向的数据集
self.sma1 = btind.SimpleMovingAverage(period=5)
# 只指定第一个数据表格
self.sma2 = btind.SMA(self.data, period=5)
# 指定第一个数据表格的 close 线
self.sma3 = btind.SMA(self.data.close, period=5)
# 完整写法
self.sma4 = btind.SMA(self.datas[0].lines[0], period=5)
def __init__(self):
#keep a log of where we are in the datafeed
self.dataclose = self.datas[0].close
#create fast and slow moving averages
self.ma_fast = btind.SMA(period=5)
self.ma_slow = btind.SMA(period=30)
# set values for when the fast ma crosses the slow ma w backtrader's indicator
# -1 is bearish, 1 is bullish
self.crossover = btind.CrossOver(self.ma_fast, self.ma_slow)
def __init__(self):
# Keep a reference to the "close" line in the data[0] dataseries
self.dataclose = self.datas[0].close
sma_fast = btind.SMA(period=self.p.fast)
sma_slow = btind.SMA(period=self.p.slow)
self.buysig = btind.CrossOver(
sma_fast, sma_slow) #10일과 30일 이동평균의 교차점 찾아줌, -1혹은 1 output
print('-----------------------------------------------')
print(" This is test strategy ")
print('-----------------------------------------------')
def __init__(self, args):
self.dataclose = self.datas[0].close
self.order = None
self.smafast, self.smaslow = btind.SMA(period=args.fastma), btind.SMA(
period=args.slowma)
self.stoploss = args.stoploss
self.takeprofit = args.takeprofit
self.sl, self.tp = None, None
self.buyfinaltime = args.buyfinaltime
self.timetosell = args.timetosell
self.logging = args.log
def __init__(self):
self.l.adx = btind.AverageDirectionalMovementIndex(self.data0)
self.l.adxma = btind.SMA(self.l.adx(0), period=2)
self.crossup_condition = btind.crossover.CrossUp(
self.l.adx(0), self.l.adxma(0))
self.hi = []
self.lo = []
def __init__(self):
self.dataclose = self.datas[0].close
self.order = None
#self.macd = bt.indicators.MACD(self.datas[0])
#self.sma05 = btind.SMA(self.datas[0],period = self.params.mapperiod,subplot=False)
self.sma20 = btind.SMA(self.datas[0],
period=self.params.mapperiod02,
subplot=False)
self.bbrands = btind.BBands(self.datas[0], subplot=False)
self.max20 = bt.talib.MAX(self.datas[0],
period=self.params.mapperiod02,
plot=False)
self.min20 = bt.talib.MIN(self.datas[0],
period=self.params.mapperiod02,
plot=False)
self.atr = btind.ATR(self.datas[0], plot=False)
self.signaltop = btind.CrossOver(self.dataclose,
self.bbrands.top,
plot=False)
self.signalcrossover = btind.CrossOver(self.dataclose,
self.sma20,
plot=False)
self.signallow = btind.CrossOver(self.datas[0], self.bbrands.bot)
self.signaltop = btind.CrossOver(self.datas[0], self.bbrands.top)
self.buyprice = None
self.buycomm = None
def __init__(self):
self.inds = dict()
for d in self.datas:
if d._name == self.p.benchmark_name:
continue
self.inds[d] = dict()
self.inds[d]['mach'] = MA_Channel.MAChannel(d, subplot=False)
self.inds[d]['MACHH'] = self.inds[d]['mach'].MACHH
self.inds[d]['csma50'] = btind.SMA(d.close, period=50)
self.inds[d]['order'] = None
self.inds[d]['buy_condition'] = btind.crossover.CrossUp(
d.high, self.inds[d]['MACHH'])
self.inds[d]['tradeNo'] = 0
self.inds[d]['counter'] = 0
self.inds[d]['eligible'] = False
self.bar_counter = 0
hi, lo = self.data.high, self.data.low
def __init__(self):
self.bar_num = 0
#MyTrix(self.data, period=self.p.trixperiod)
#self.data_priceDiv = PriceDiv(self.data)
self.data_obv = OnBalanceVolume(self.data) ##
##btind.obv(self.data,period=3, plot=True)
self.data_obv20 = btind.SMA(self.data_obv, period=20)
def __init__(self):
#keep a log of where we are in the datafeed
self.dataclose = self.datas[0].close
#create fast and slow moving averages
self.ma_fast = btind.SMA(period=self.p.smafast)
self.ma_slow = btind.SMA(period=self.p.smaslow)
self.macd = btind.MACD(self.data,
period_me1=self.p.macd1,
period_me2=self.p.macd2,
period_signal=self.p.macdsig)
# set values for when the fast ma crosses the slow ma w backtrader's indicator
# -1 is bearish, 1 is bullish
self.crossover = btind.CrossOver(self.ma_fast, self.ma_slow)
def __init__(self):
btind.SMA()
btind.Stochastic()
btind.RSI()
btind.MACD()
btind.CCI()
TestInd().plotinfo.plot = False
def __init__(self):
self.dataclose = self.datas[0].close
self.order = None
#self.macd = bt.indicators.MACD(self.datas[0])
#self.sma05 = btind.SMA(self.datas[0],period = self.params.mapperiod,subplot=False)
self.sma20 = btind.SMA(self.datas[0],
period=self.params.mapperiod02,
subplot=False)
self.bbrands = btind.BBands(self.datas[0], subplot=False)
self.max55 = bt.talib.MAX(self.datas[0].high,
period=self.params.mapperiod,
plot=False)
self.min55 = bt.talib.MIN(self.datas[0].low,
period=self.params.mapperiod,
plot=False)
self.atr = btind.ATR(self.datas[0])
self.stake = 4000
self.ownprice = 0
## self.signaltop = btind.CrossOver(self.dataclose,self.bbrands.top,plot=False)
self.buyprice = None
self.buycomm = None
def __init__(self):
self.inds = dict()
for d in self.datas:
if d._name == self.p.benchmark_name:
continue
self.inds[d] = dict()
self.inds[d]['pdimdiCH'] = PDIMDIHL.PDIMDIHL(d, subplot=False)
self.inds[d]['pdi'] = self.inds[d]['pdimdiCH'].l.pdi
self.inds[d]['mdi'] = self.inds[d]['pdimdiCH'].l.mdi
self.inds[d]['adx'] = btind.AverageDirectionalMovementIndex(
d, subplot=False)
self.inds[d]['adxma'] = btind.SMA(self.inds[d]['adx'].l.adx,
period=2,
subplot=False)
self.inds[d]['LLPCH'] = hhpc.PC(d, subplot=False)
self.inds[d]['llpc'] = self.inds[d]['LLPCH'].l.llpc
self.inds[d]['PC'] = pchannel.priceChannel(d, subplot=False)
self.inds[d]['pch'] = self.inds[d]['PC'].l.pch
self.inds[d]['order'] = None
self.inds[d]['eligible'] = False
self.inds[d]['counter'] = 0
self.inds[d]['tradeno'] = 0
self.inds[d]['is_last'] = False
self.bar_counter = 0
def __init__(self):
self.inds = dict()
for d in self.datas :
if d._name == self.p.benchmark_name :
continue
self.inds[d] = dict()
self.inds[d]['hhpcCH'] = hhpc.PC(d,subplot=False)
self.inds[d]['llpc'] = self.inds[d]['hhpcCH'].l.llpc
self.inds[d]['priceCH'] = pchannel.priceChannel(d,subplot=False)
self.inds[d]['pcl'] = self.inds[d]['priceCH'].l.pcl
self.inds[d]['csma200'] = btind.SMA(d.close,period=200)
self.inds[d]['order'] = None
self.inds[d]['tradeNo'] = 0
self.inds[d]['counter'] = 0
self.inds[d]['eligible'] = False
self.bar_counter = 0
self.highest_lowest = []
hi, lo = self.data.high, self.data.low
def __init__(self):
# Add indicators to add load
btind.SMA(period=self.p.smaperiod)
btind.MACD(period_me1=self.p.macdperiod1,
period_me2=self.p.macdperiod2,
period_signal=self.p.macdperiod3)
def __init__(self):
self.benchmark = self.getdatabyname(self.p.benchmark_name)
# Initialize & assign Indicators here
self.rsc = RSC.rsc(self.data0, self.benchmark, subplot=True)
self.rscma = btind.SMA(self.rsc, period=10, subplot=False)
self.rsc_up = rscu.rscu(self.data0, self.benchmark, subplot=False)
def __init__(self):
self.l.pdi = btind.PlusDirectionalIndicator(self.data0, period=14)
self.l.mdi = btind.MinusDirectionalIndicator(self.data0, period=14)
self.l.adx = btind.AverageDirectionalMovementIndex(self.data0,
period=14)
self.l.adxma = btind.SMA(self.l.adx, period=2)
self.adx_condition = btind.crossover.CrossUp(self.adx(0),
self.adxma(0))
def __init__(self):
# SimpleMovingAverage on main data
sma = btind.SMA(period=self.p.smaperiod)
# CrossOver (1: up, -1: down) close / sma
self.crossover = btind.CrossOver(self.data.close, sma, plot=True)
# Set to None: new ordersa allowed
self.order = None
def __init__(self):
# SimpleMovingAverage on main data
# Equivalent to -> sma = btind.SMA(self.data, period=self.p.smaperiod)
sma = btind.SMA(period=self.p.smaperiod)
# CrossOver (1: up, -1: down) close / sma
self.buysell = btind.CrossOver(self.data.close, sma, plot=True)
# Sentinel to None: new ordersa allowed
self.order = None
def __init__(self):
btind.SMA()
btind.Stochastic()
btind.RSI()
btind.MACD()
btind.CCI()
TestInd().plotinfo.plot = False
sma1, sma2 = bt.ind.SMA(period=10), bt.ind.SMA(period=30)
crossover = bt.ind.CrossOver(sma1, sma2)
self.signal_add(bt.SIGNAL_LONG, crossover)
def __init__(self):
# To control operation entries
self.orderid = None
# Create SMA on 2nd data
sma = btind.MovAv.SMA(self.data, period=self.p.period)
# Create a CrossOver Signal from close an moving average
self.signal = btind.CrossOver(self.data.close, sma)
self.signal.csv = self.p.csvcross
btind.SMA(
self.data.pe, period=1,
subplot=False) # A way to draw the new data field on the chart
