start_date, analyzers, monthly_sum, normal months

master
Dmitry Maylarov 4 years ago
parent 12bbb63f3a
commit 4458e5386f

@ -9,9 +9,8 @@ import backtrader as bt
stockList = ["VOO"] stockList = ["VOO"]
total_days_in_market = 365 * 10 total_days_in_market = 365 * 10
month_sum = 500 # usd month_sum = 500 # usd
period_months = 1
reserve = 5 # usd for comms etc reserve = 5 # usd for comms etc
period_sum = month_sum * period_months startDate = datetime.datetime.fromisoformat("2018-01-01")
# import data # import data
@ -21,7 +20,7 @@ def get_data(stocks, start, end):
endDate = datetime.datetime.now() endDate = datetime.datetime.now()
startDate = endDate - datetime.timedelta(days=total_days_in_market) # startDate = endDate - datetime.timedelta(days=total_days_in_market)
stockData = get_data(stockList[0], startDate, endDate) stockData = get_data(stockList[0], startDate, endDate)
actualStart: datetime.datetime = stockData.index[0] actualStart: datetime.datetime = stockData.index[0]
@ -65,8 +64,6 @@ class PercentageCommisionScheme(bt.CommInfoBase):
class FormulaInvesting(bt.Strategy): class FormulaInvesting(bt.Strategy):
params = dict(monthly_cash=month_sum, monthly_range=[5, 20])
def __init__(self): def __init__(self):
self.order = None self.order = None
self.totalcost = 0 self.totalcost = 0
@ -77,10 +74,10 @@ class FormulaInvesting(bt.Strategy):
def log(self, txt, dt=None): def log(self, txt, dt=None):
dt = dt or self.datas[0].datetime.date(0) dt = dt or self.datas[0].datetime.date(0)
# print("%s, %s" % (dt.isoformat(), txt)) print("%s, %s" % (dt.isoformat(), txt))
def start(self): def start(self):
self.broker.set_fundmode(fundmode=True, fundstartval=100.0) # self.broker.set_fundmode(fundmode=True, fundstartval=100.0)
self.cash_start = self.broker.get_cash() self.cash_start = self.broker.get_cash()
self.val_start = 100.0 self.val_start = 100.0
@ -88,7 +85,7 @@ class FormulaInvesting(bt.Strategy):
# ADD A TIMER # ADD A TIMER
self.add_timer( self.add_timer(
when=bt.timer.SESSION_START, when=bt.timer.SESSION_START,
monthdays=[i for i in self.p.monthly_range], monthdays=[1],
monthcarry=True monthcarry=True
# timername='buytimer', # timername='buytimer',
) )
@ -137,6 +134,9 @@ class FormulaInvesting(bt.Strategy):
self.order = None self.order = None
def stop(self): def stop(self):
self.calc_params()
def calc_params(self):
# calculate actual returns # calculate actual returns
self.roi = (self.broker.get_value() / self.cash_start) - 1 self.roi = (self.broker.get_value() / self.cash_start) - 1
self.froi = self.broker.get_fundvalue() - self.val_start self.froi = self.broker.get_fundvalue() - self.val_start
@ -160,13 +160,13 @@ class FormulaInvesting(bt.Strategy):
def notify_timer(self, timer, when, *args): def notify_timer(self, timer, when, *args):
self.periods += 1 self.periods += 1
self.broker.add_cash(self.p.monthly_cash) self.broker.add_cash(month_sum)
self.formula() self.formula()
class VA(FormulaInvesting): class VA(FormulaInvesting):
def formula(self): def formula(self):
target_value = (self.periods) * self.p.monthly_cash - reserve target_value = min(self.periods * month_sum - reserve, self.broker.get_value())
self.order_target_value(target=target_value) self.order_target_value(target=target_value)
@ -176,6 +176,18 @@ class DCA(FormulaInvesting):
self.order_target_value(target=target_value) self.order_target_value(target=target_value)
class QVA(VA):
def formula(self):
if not self.periods % 3:
super().formula()
class QDCA(DCA):
def formula(self):
if not self.periods % 3:
super().formula()
def run(strategy, data): def run(strategy, data):
cerebro = bt.Cerebro(stdstats=False) cerebro = bt.Cerebro(stdstats=False)
@ -193,12 +205,20 @@ def run(strategy, data):
comminfo = PercentageCommisionScheme() comminfo = PercentageCommisionScheme()
cerebro.broker.addcommissioninfo(comminfo) cerebro.broker.addcommissioninfo(comminfo)
cerebro.broker.set_cash(period_sum) cerebro.broker.set_cash(month_sum)
cerebro.run() # cerebro.addobserver(bt.observers.FundValue)
# cerebro.addobserver(bt.observers.FundShares)
cerebro.addanalyzer(bt.analyzers.DrawDown, _name="drawdown")
cerebro.addanalyzer(bt.analyzers.VWR, _name="returns")
thestrats = cerebro.run()
thestrat = thestrats[0]
dd = thestrat.analyzers.drawdown
print(dd.get_analysis().max)
ret = thestrat.analyzers.returns
print(ret.get_analysis())
cerebro.plot(iplot=False, style="candlestick") cerebro.plot(iplot=False, style="candlestick")
if __name__ == "__main__": if __name__ == "__main__":
# run(LSI, 100000, data) for strategy in (DCA, QDCA, VA, QVA):
run(DCA, data) run(strategy, data)
run(VA, data)

Loading…
Cancel
Save