def __init__(self,
bars=None,
strategy=None,
port=None,
broker=None,
start_date=None,
end_date=None):
if bars is None:
bars = CoinDataHandler(self, ['okcoinUSD'])
if strategy is None:
strategy = BuyAndHoldStrategy(bars, self)
if port is None:
port = NaivePortfolio(bars, self, '2017-1-1')
if broker is None:
broker = SimulatedExecutionHandler(self)
self.bars = bars
self.strategy = strategy
self.port = port
self.broker = broker
self.__event_queue = Queue()
self.__thread = Thread(target=self.__run)
self.__active = False
self.__handlers = {
'MARKET': [self.__filte_market_event],
'SIGNAL': [port.update_signal],
'ORDER': [broker.execute_order],
'FILL': [port.update_fill]
}
if start_date is not None:
try:
sd = datetime.datetime.strptime(start_date + " 00:00:00",
"%Y-%m-%d %H:%M:%S")
except ValueError:
print(
"Parameter start_date can't be parsed by datetime.strptime,"
"start_date will equal to None.")
sd = None
if end_date is not None:
try:
ed = datetime.datetime.strptime(end_date + " 00:00:00",
"%Y-%m-%d %H:%M:%S")
except ValueError:
print(
"Parameter end_date can't be parsed by datetime.strptime,"
"end_date will equal to None.")
ed = None
self.__start_date = sd
self.__end_date = ed
def test_bnh_strategy(self):
events_queue = queue.Queue(100)
bars = HistoricCSVDataHandler(
events_queue,
'./tests/datasets/',
['BTC_ETC'],
['open', 'high', 'low', 'close']
)
strategy = BuyAndHoldStrategy(bars, events_queue)
bars.update_bars()
event = events_queue.get(False)
strategy.calculate_signals(event)
signal = events_queue.get(False)
self.assertEqual(signal.symbol, 'BTC_ETC')
self.assertEqual(signal.strategy_id, 'BUY_AND_HOLD')
self.assertEqual(signal.signal_type, 'LONG')
#PYTHON
from queue import Queue
import time
#PROJECT
from events import (MarketEvent, SignalEvent, OrderEvent, FillEvent)
from data import HistoricCSVDataHandler
from strategy import BuyAndHoldStrategy
from portfolio import BacktestPortfolio
from broker import BacktestBroker
#MODULE
event_queue = Queue()
data = HistoricCSVDataHandler(event_queue, ["AAPL", "BRK-B", "CVX", "KO"])
strategy = BuyAndHoldStrategy(data, event_queue)
portfolio = BacktestPortfolio(event_queue, data, "2015-01-01", 10000)
broker = BacktestBroker(event_queue)
while True:
if data.continue_backtest is True:
data.update_latest_data()
else:
break
while True:
try:
event = event_queue.get(block=False)
except:
break
if event is not None:
symbol_list=av_list,
key=conf.keys['alpha vantage']['key'],
url=conf.keys['alpha vantage']['url']).take_csv(outputsize='full')
events = queue.Queue()
start_date = conf.values['date']['start_date']
bars = HistoricCSVDataHandler(events, dir_path, symbol_list, start_date)
port = NaivePortfolio_add_founds(
bars,
events,
start_date,
initial_capital=conf.values['money']['initial_capital'],
buy_quantity=10.0,
add_funds=conf.values['money']['add_funds'])
strategy = BuyAndHoldStrategy(bars, events, port)
broker = SimulatedExecutionHandler(events)
while True:
# Обновляем бары (код для бэктестинга, а не живой торговли)
if bars.continue_backtest == True:
bars.update_bars()
else:
break
# Обрабатываем события
while True:
try:
event = events.get(False)
except queue.Empty:
break
from cybos import *
import pandas as pd
import matplotlib.pyplot as plt
from strategy import BollingerStrategy, BuyAndHoldStrategy
from barfeed import dataframefeed
from datetime import date
targetStock = getBarsFromCybos("A000660", date(2015, 1, 1), date(2016, 12, 29))
targetStock.index = targetStock['Date']
initialCash = 200000
feed = dataframefeed.Feed()
feed.addBarsFromDf('targetStock', targetStock)
buyandhold = BuyAndHoldStrategy(feed, 'targetStock', initialCash)
buyandhold.run()
print "Buy and Hold: Final portfolio value: $%.2f" % buyandhold.getBroker(
).getEquity()
feed.reset()
myStrategy = BollingerStrategy(feed, 'targetStock', initialCash, 20, 1.8)
myStrategy.run()
print "Bollinger Band: Final portfolio value: $%.2f" % myStrategy.getBroker(
).getEquity()
plotData = pd.DataFrame(data={'Close':targetStock['Close'], 'Upper': list(reversed(myStrategy.upper)), \
'Lower': list(reversed(myStrategy.lower)), \
'Middle': list(reversed(myStrategy.middle))}, index= targetStock['Date'])
#MYMODULES
from queue import Queue
from events import (MarketEvent, SignalEvent, OrderEvent, FillEvent)
from data import HistoricCSVDataHandler
from strategy import BuyAndHoldStrategy
from portfolio import NaivePortfolio
from execution import SimulatedExecutionHandler
#INSTANTIATIONS
event_queue = Queue()
CSV_dir = 'INCLUDE DIRECTORY OF CSV FILES HERE'
data = HistoricCSVDataHandler(event_queue, CSV_dir, ['AAPL', 'CVX']) #Input a list of stock names here
strategy = BuyAndHoldStrategy(data, event_queue)
start_date = datetime.date(14, 12, 1)
portfolio = NaivePortfolio(event_queue, data, start_date)
broker = SimulatedExecutionHandler(event_queue)
#outer loop: mimicking the drip-feed of live data
while True:
if data.continue_backtest is True:
data.update_data() #drip-feed new line of data
else:
break
#inner loop: handles events in the queue. Breaks when the queue is empty to get new data
while True:
try:
event = event_queue.get_nowait() #gets new event but does not wait for queue to fill again if it is empty
#from data import DataHandler #actually a subclass of DataHandler
import os
os.chdir("/home/taylor/backtester/")
import Queue
import time
from data import HistoricCSVDataHandler
from strategy import BuyAndHoldStrategy
from portfolio import NaivePortfolio
from execution import SimulatedExecutionHandler
start_date = '2015-03-13' #figure out better solution for this
events = Queue.Queue(maxsize=100)
bars = HistoricCSVDataHandler(events, "/home/taylor/backtester/csv/", ['yhoo'])
strategy = BuyAndHoldStrategy(bars, events)
port = NaivePortfolio(bars, events, start_date, initial_capital=100000.)
broker = SimulatedExecutionHandler(events)
while True:
# Update the bars (specific backtest code, as opposed to live trading)
if bars.continue_backtest == True:
bars.update_bars()
else:
break
# Handle the events
while True:
try:
event = events.get(False)
except Queue.Empty: