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backtest_orbd.py
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backtest_orbd.py
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from db import config
import backtrader, pandas, sqlite3
from datetime import date, datetime, time, timedelta
class OpeningRangeBreakdown(backtrader.Strategy):
params = dict(
num_opening_bars=15
)
def __init__(self):
self.opening_range_low = 0
self.opening_range_high = 0
self.opening_range = 0
self.bought_today = False
self.order = None
def log(self, txt, dt=None):
if dt is None:
dt = self.datas[0].datetime.datetime()
print('%s, %s' % (dt, txt))
def notify_order(self, order):
if order.status in [order.Submitted, order.Accepted]:
# Buy/Sell order submitted/accepted to/by broker - Nothing to do
return
# Check if an order has been completed
if order.status in [order.Completed]:
order_details = f"{order.executed.price}, Cost: {order.executed.value}, Comm {order.executed.comm}"
if order.issell():
self.log(f"SELL EXECUTED, Price: {order_details}")
else: # buy
self.log(f"BUY EXECUTED, Price: {order_details}")
elif order.status in [order.Canceled, order.Margin, order.Rejected]:
self.log('Order Canceled/Margin/Rejected')
self.order = None
def next(self):
current_bar_datetime = self.data.num2date(self.data.datetime[0])
previous_bar_datetime = self.data.num2date(self.data.datetime[-1])
if current_bar_datetime.date() != previous_bar_datetime.date():
self.opening_range_low = self.data.low[0]
self.opening_range_high = self.data.high[0]
self.bought_today = False
opening_range_start_time = time(9, 30, 0)
dt = datetime.combine(date.today(), opening_range_start_time) + timedelta(minutes=self.p.num_opening_bars)
opening_range_end_time = dt.time()
if current_bar_datetime.time() >= opening_range_start_time \
and current_bar_datetime.time() < opening_range_end_time:
self.opening_range_high = max(self.data.high[0], self.opening_range_high)
self.opening_range_low = min(self.data.low[0], self.opening_range_low)
self.opening_range = self.opening_range_high - self.opening_range_low
else:
if self.order:
return
if self.position and (self.data.close[0] > (self.opening_range_low + self.opening_range)):
self.close()
if self.data.close[0] > self.opening_range_low and not self.position and not self.bought_today:
self.order = self.sell()
self.bought_today = True
if self.position and (self.data.close[0] < (self.opening_range_low - self.opening_range)):
self.order = self.close()
if self.position and current_bar_datetime.time() >= time(15, 45, 0):
self.log("RUNNING OUT OF TIME - LIQUIDATING POSITION")
self.close()
def stop(self):
self.log('(Num Opening Bars %2d) Ending Value %.2f' %
(self.params.num_opening_bars, self.broker.getvalue()))
if self.broker.getvalue() > 34000:
self.log("*** BIG WINNER ***")
if self.broker.getvalue() < 26000:
self.log("*** MAJOR LOSER ***")
if __name__ == '__main__':
conn = sqlite3.connect(config.DB_FILE)
conn.row_factory = sqlite3.Row
cursor = conn.cursor()
cursor.execute("""
SELECT DISTINCT(stock_id) as stock_id FROM stock_price_minute
""")
stocks = cursor.fetchall()
# stocks = [stocks[0]]
for stock in stocks:
print(f"== Testing {stock['stock_id']} ==")
cerebro = backtrader.Cerebro()
cerebro.broker.setcash(30000.0)
# cerebro.addsizer(backtrader.sizers.PercentSizer, percents=95)
dataframe = pandas.read_sql("""
SELECT datetime, open, high, low, close, volume
FROM stock_price_minute
WHERE stock_id = :stock_id
AND strftime('%H:%M:%S', datetime) >= '09:30:00'
AND strftime('%H:%M:%S', datetime) < '16:00:00'
ORDER BY datetime ASC
""", conn, params={"stock_id": stock['stock_id']}, index_col='datetime', parse_dates=['datetime'])
data = backtrader.feeds.PandasData(dataname=dataframe)
cerebro.adddata(data)
cerebro.addstrategy(OpeningRangeBreakdown)
#strats = cerebro.optstrategy(OpeningRangeBreakout, num_opening_bars=[15, 30, 60])
cerebro.run()
#cerebro.plot()