def main(tick, year, cash, smaPeriod, order):
print 'Welcome, ' + os.environ['USER'] + '!'
print 'Backtesting ' + tick + ' in ' + str(year)
# Download daily bars
filename = tick + '-' + str(year) + '.csv'
yahoofinance.download_daily_bars(tick, year, filename)
# Load CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV(tick, filename)
# Evaluate Strategy
strategySMA = StrategySMA(feed, tick, smaPeriod, order, cash)
# Attach a returns analyzers to the strategy.
retAnalyzer = returns.Returns()
strategySMA.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strategySMA.attachAnalyzer(sharpeRatioAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(strategySMA)
# Include the SMA in the instrument's subplot to get it displayed along with the closing prices.
plt.getInstrumentSubplot(tick).addDataSeries("SMA", strategySMA.getSMA())
# Set portfolio cash
strategySMA.getBroker().setCash(cash)
initial = strategySMA.getBroker().getEquity()
# Run the strategy
strategySMA.run()
# Print the results
print '*' * 60
print 'Initial portfolio value: $%.2f' % initial
final = strategySMA.getBroker().getEquity()
print 'Final portfolio value: $%.2f' % final
net = final - initial
if net > 0:
print 'Net gain: $%.2f' % net
else:
print 'Net loss: $%.2f' % net
percentage = (final - initial) / initial * 100
if percentage > 0:
print 'Percentage gain: +%.2f%%' % percentage
else:
print 'Percentage loss: %.2f%%' % percentage
#print 'Final portfolio value: $%.2f' % strategySMA.getResult()
print 'Annual return: %.2f%%' % (retAnalyzer.getCumulativeReturns()[-1] * 100)
print 'Average daily return: %.2f%%' % (stats.mean(retAnalyzer.getReturns()) * 100)
print 'Std. dev. daily return: %.4f' % (stats.stddev(retAnalyzer.getReturns()))
print 'Sharpe ratio: %.2f' % (sharpeRatioAnalyzer.getSharpeRatio(0))
# Plot the strategy
plt.plot()
def testDownloadAndParse(self): instrument = "orcl" path = "orcl-2010.csv" yahoofinance.download_daily_bars(instrument, 2010, path) bf = yahoofeed.Feed() bf.addBarsFromCSV(instrument, path) bf.loadAll() self.assertEqual(bf[instrument][-1].getOpen(), 31.22) self.assertEqual(bf[instrument][-1].getClose(), 31.30)
def run_strategy():
# Load the yahoo feed from the CSV file
yahoofinance.download_daily_bars('600865.SS', 2015, '600865.SS-2015.csv')
feed = yahoofeed.Feed()
feed.addBarsFromCSV("600865.SS", "600865.SS-2015.csv")
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed, "600865.SS", 10, 5, 1)
myStrategy.run()
print "Final portfolio value: $%.2f" % myStrategy.getBroker().getEquity()
def testDownloadAndParseDaily(self):
instrument = "orcl"
with common.TmpDir() as tmp_path:
path = os.path.join(tmp_path, "orcl-2010.csv")
yahoofinance.download_daily_bars(instrument, 2010, path)
bf = yahoofeed.Feed()
bf.addBarsFromCSV(instrument, path)
bf.loadAll()
self.assertEqual(round(bf[instrument][-1].getOpen(), 2), 31.22)
self.assertEqual(round(bf[instrument][-1].getClose(), 2), 31.30)
def build_feed(instruments, fromYear, toYear):
feed = yahoofeed.Feed()
for year in range(fromYear, toYear+1):
for symbol in instruments:
fileName = "%s-%d-yahoofinance.csv" % (symbol, year)
if not os.path.exists(fileName):
print "Downloading %s %d" % (symbol, year)
yahoofinance.download_daily_bars(symbol, year, fileName)
feed.addBarsFromCSV(symbol, fileName)
return feed
def testDownloadAndParseDaily(self):
instrument = "orcl"
common.init_temp_path()
path = os.path.join(common.get_temp_path(), "orcl-2010.csv")
yahoofinance.download_daily_bars(instrument, 2010, path)
bf = yahoofeed.Feed()
bf.addBarsFromCSV(instrument, path)
bf.loadAll()
self.assertEqual(bf[instrument][-1].getOpen(), 31.22)
self.assertEqual(bf[instrument][-1].getClose(), 31.30)
def build_feed(instruments, fromYear, toYear):
feed = yahoofeed.Feed()
for year in range(fromYear, toYear + 1):
for symbol in instruments:
fileName = "%s-%d-yahoofinance.csv" % (symbol, year)
if not os.path.exists(fileName):
print "Downloading %s %d" % (symbol, year)
yahoofinance.download_daily_bars(symbol, year, fileName)
feed.addBarsFromCSV(symbol, fileName)
return feed
def testDownloadAndParseDaily(self):
instrument = "orcl"
common.init_temp_path()
path = os.path.join(common.get_temp_path(), "orcl-2010.csv")
yahoofinance.download_daily_bars(instrument, 2010, path)
bf = yahoofeed.Feed()
bf.addBarsFromCSV(instrument, path)
bf.loadAll()
self.assertEqual(bf[instrument][-1].getOpen(), 31.22)
self.assertEqual(bf[instrument][-1].getClose(), 31.30)
def run_strategy():
# Load the yahoo feed from the CSV file
from pyalgotrade.tools import yahoofinance
import csv
instruments = {
#'orcl'
#,'aapl'
'^HSI': {"name":"MHSI", "dollar_per_point":10},
#'fxcm',
}
YEARS = [2010,2015]
CAPITAL = 20000000
feed = yahoofeed.Feed()
for i in instruments:
for y in range(YEARS[0], YEARS[1]+1):
# print i, y
csv_name = '%s-%s.csv' % (i,y)
csv_name_new = "new_" + csv_name
yahoofinance.download_daily_bars(i, y, csv_name)
with open(csv_name, "rb") as fr:
reader = csv.DictReader(fr)
with open(csv_name_new, "wb")as fw:
w = csv.DictWriter(fw, reader.fieldnames)
w.writeheader()
for row in reader:
factor = float(row["Adj Close"]) / float(row["Close"])
row["Open"] = float(row["Open"]) * factor
row["High"] = float(row["High"]) * factor
row["Low"] = float(row["Low"]) * factor
row["Close"] = float(row["Close"]) * factor
row["Volume"] = float(row["Volume"]) * factor
w.writerow(row)
feed.addBarsFromCSV(i, csv_name_new)
# Evaluate the strategy with the feed.
myStrategy = TurtleTrading(feed, instruments, CAPITAL)
myStrategy.run()
final = myStrategy.getBroker().getEquity()
profit = final - CAPITAL
print "Final portfolio value: $%.2f" % final
print "Profit = %.2f, %.2f " % (profit, 100 * profit / CAPITAL)
f = open("record.csv", "wb")
rows = myStrategy.record.values()
sorted(rows, key = lambda x: x["date"])
for r in rows:
print r["date"]
w = csv.DictWriter(f, rows[0].keys())
w.writeheader()
w.writerows(rows)
def run_strategy(smaPeriod):
# download a CSV file from yahoo finance
yahoofinance.download_daily_bars(ticker, year, csv_file)
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV(ticker, csv_file)
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed, ticker, smaPeriod)
myStrategy.run()
equity = myStrategy.getBroker().getEquity()
print '\nStarting portfolio value: $%.2f' % start_capital
print 'Final portfolio value: $%.2f' % equity
print 'Difference: %.2f' % (equity - start_capital)
def run_strategy(smaPeriod): # download a CSV file from yahoo finance yahoofinance.download_daily_bars(ticker, year, csv_file) # Load the yahoo feed from the CSV file feed = yahoofeed.Feed() feed.addBarsFromCSV(ticker, csv_file) # Evaluate the strategy with the feed. myStrategy = MyStrategy(feed, ticker, smaPeriod) myStrategy.run() equity = myStrategy.getBroker().getEquity() print '\nStarting portfolio value: $%.2f' % start_capital print 'Final portfolio value: $%.2f' % equity print 'Difference: %.2f' % (equity - start_capital)
def RealTime(filepath,instrument):
# Download CSV from yahoo if the CSV does not already exist.
if not isfile(filepath):
download_daily_bars(instrument,2016,filepath)
# Get Live Results from Yahoo Database and append to CSV
s = Share(instrument)
date = datetime.today().strftime('%Y-%m-%d')
O,H,L,C,V,AC = (s.get_open(), s.get_days_high(), s.get_days_low(), s.get_price(),
s.get_volume(),s.get_price())
#Date,Open,High,Low,Close,Volume,Adj Close
field = [date,O,H,L,C,V,AC]
with open(filepath,'a') as csvfile:
old = csv.writer(csvfile)
add = old.writerow(field)
def download_files_for_symbol(symbol, fromYear, toYear):
if not os.path.exists(storage):
logger.info("Creating %s directory" % (storage))
os.mkdir(storage)
status = ""
for year in range(fromYear, toYear+1):
fileName = get_csv_filename(symbol, year)
if not os.path.exists(fileName):
logger.info("Downloading %s %d to %s" % (symbol, year, fileName))
try:
yahoofinance.download_daily_bars(symbol, year, fileName)
status += "1"
except Exception, e:
logger.error(str(e))
status += "0"
else:
status += "1"
def download_files_for_symbol(symbol, fromYear, toYear):
if not os.path.exists(storage):
logger.info("Creating %s directory" % (storage))
os.mkdir(storage)
status = ""
for year in range(fromYear, toYear + 1):
fileName = get_csv_filename(symbol, year)
if not os.path.exists(fileName):
logger.info("Downloading %s %d to %s" % (symbol, year, fileName))
try:
yahoofinance.download_daily_bars(symbol, year, fileName)
status += "1"
except Exception, e:
logger.error(str(e))
status += "0"
else:
status += "1"
def download_files_for_symbol(symbol, fromYear, toYear):
if not os.path.exists(storage):
logger.info("Creating %s directory" % (storage))
os.mkdir(storage)
status = ""
for year in range(fromYear, toYear+1):
fileName = get_csv_filename(symbol, year)
if not os.path.exists(fileName):
logger.info("Downloading %s %d to %s" % (symbol, year, fileName))
try:
yahoofinance.download_daily_bars(symbol, year, fileName)
status += "1"
except Exception as e:
logger.error(str(e))
status += "0"
else:
status += "1"
if status.find("1") == -1:
logger.fatal("No data found for %s" % (symbol))
elif status.lstrip("0").find("0") != -1:
logger.fatal("Some bars are missing for %s" % (symbol))
# Copyright 2015-2017 Isaac de la Pena
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
.. moduleauthor:: Isaac de la Pena <*****@*****.**>
"""
from pyalgotrade.tools import yahoofinance
import os
import IbexAssets as assets
if not os.path.isdir(assets.folder):
os.mkdir(assets.folder)
for instrument, start in assets.all.items():
for year in range(start, assets.endYear):
store = assets.folder + instrument + "-" + str(year) + ".csv"
print store
yahoofinance.download_daily_bars(instrument, year, store)
"glng": 11095,
"simo": 17293,
}
for instrument, quantity in orders.items():
self.marketOrder(instrument,
quantity,
onClose=True,
allOrNone=True)
def onBars(self, bars):
pass
# Load the yahoo feed from CSV files.
feed = yahoofeed.Feed()
yahoofinance.download_daily_bars("aeti", 2011,
"D:\\aeti-2011-yahoofinance.csv")
yahoofinance.download_daily_bars("egan", 2011,
"D:\\egan-2011-yahoofinance.csv")
yahoofinance.download_daily_bars("glng", 2011,
"D:\\glng-2011-yahoofinance.csv")
yahoofinance.download_daily_bars("simo", 2011,
"D:\\simo-2011-yahoofinance.csv")
feed.addBarsFromCSV("aeti", "D:\\aeti-2011-yahoofinance.csv")
feed.addBarsFromCSV("egan", "D:\\egan-2011-yahoofinance.csv")
feed.addBarsFromCSV("glng", "D:\\glng-2011-yahoofinance.csv")
feed.addBarsFromCSV("simo", "D:\\simo-2011-yahoofinance.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = MyStrategy(feed)
# Attach returns and sharpe ratio analyzers.
bar = bars[self.__instrument]
# If a position was not opened, check if we should enter a long position.
if self.__position is None:
if bar.getPrice() > self.__sma[-1]:
# Enter a buy market order for 10 shares. The order is good till canceled.
self.__position = self.enterLong(self.__instrument, 10, True)
# Check if we have to exit the position.
elif bar.getPrice(
) < self.__sma[-1] and not self.__position.exitActive():
self.__position.exitMarket()
def run_strategy(smaPeriod, ticker, filename):
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV(ticker, filename)
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed, ticker, smaPeriod)
myStrategy.run()
print "Final portfolio value: $%.2f" % myStrategy.getBroker().getEquity()
print 'Argument List:', str(sys.argv)
ticker = sys.argv[1]
smaval = sys.argv[2]
#Fetch the datafile for the given stock
yahoofinance.download_daily_bars(ticker, 2014, 'datafile.csv')
run_strategy(int(smaval), ticker, 'datafile.csv')
# Place the orders to get them processed on the first bar.
orders = {
"aeti": 297810,
"egan": 81266,
"glng": 11095,
"simo": 17293,
}
for instrument, quantity in orders.items():
self.marketOrder(instrument, quantity, onClose=True, allOrNone=True)
def onBars(self, bars):
pass
# Load the yahoo feed from CSV files.
feed = yahoofeed.Feed()
yahoofinance.download_daily_bars("aeti",2011, "D:\\aeti-2011-yahoofinance.csv")
yahoofinance.download_daily_bars("egan", 2011, "D:\\egan-2011-yahoofinance.csv")
yahoofinance.download_daily_bars("glng", 2011, "D:\\glng-2011-yahoofinance.csv")
yahoofinance.download_daily_bars("simo", 2011, "D:\\simo-2011-yahoofinance.csv")
feed.addBarsFromCSV("aeti", "D:\\aeti-2011-yahoofinance.csv")
feed.addBarsFromCSV("egan", "D:\\egan-2011-yahoofinance.csv")
feed.addBarsFromCSV("glng", "D:\\glng-2011-yahoofinance.csv")
feed.addBarsFromCSV("simo", "D:\\simo-2011-yahoofinance.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = MyStrategy(feed)
# Attach returns and sharpe ratio analyzers.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
from pyalgotrade.tools import yahoofinance
yahoofinance.download_daily_bars('AXP', 2008, 'data/AXP-2008.csv')
yahoofinance.download_daily_bars('BA', 2008, 'data/BA-2008.csv')
yahoofinance.download_daily_bars('CAT', 2008, 'data/CAT-2008.csv')
yahoofinance.download_daily_bars('CSCO', 2008, 'data/CSCO-2008.csv')
yahoofinance.download_daily_bars('CVX', 2008, 'data/CVX-2008.csv')
yahoofinance.download_daily_bars('DD', 2008, 'data/DD-2008.csv')
yahoofinance.download_daily_bars('DIS', 2008, 'data/DIS-2008.csv')
yahoofinance.download_daily_bars('GE', 2008, 'data/GE-2008.csv')
yahoofinance.download_daily_bars('GS', 2008, 'data/GS-2008.csv')
yahoofinance.download_daily_bars('HD', 2008, 'data/HD-2008.csv')
yahoofinance.download_daily_bars('IBM', 2008, 'data/IBM-2008.csv')
yahoofinance.download_daily_bars('INTC', 2008, 'data/INTC-2008.csv')
yahoofinance.download_daily_bars('JNJ', 2008, 'data/JNJ-2008.csv')
yahoofinance.download_daily_bars('JPM', 2008, 'data/JPM-2008.csv')
yahoofinance.download_daily_bars('KO', 2008, 'data/KO-2008.csv')
yahoofinance.download_daily_bars('MCD', 2008, 'data/MCD-2008.csv')
yahoofinance.download_daily_bars('MMM', 2008, 'data/MMM-2008.csv')
yahoofinance.download_daily_bars('MRK', 2008, 'data/MRK-2008.csv')
yahoofinance.download_daily_bars('MSFT', 2008, 'data/MSFT-2008.csv')
yahoofinance.download_daily_bars('NKE', 2008, 'data/NKE-2008.csv')
yahoofinance.download_daily_bars('PFE', 2008, 'data/PFE-2008.csv')
yahoofinance.download_daily_bars('PG', 2008, 'data/PG-2008.csv')
yahoofinance.download_daily_bars('T', 2008, 'data/T-2008.csv')
yahoofinance.download_daily_bars('TRV', 2008, 'data/TRV-2008.csv')
yahoofinance.download_daily_bars('UNH', 2008, 'data/UNH-2008.csv')
yahoofinance.download_daily_bars('UTX', 2008, 'data/UTX-2008.csv')
yahoofinance.download_daily_bars('V', 2008, 'data/V-2008.csv')
yahoofinance.download_daily_bars('VZ', 2008, 'data/VZ-2008.csv')
yahoofinance.download_daily_bars('WMT', 2008, 'data/WMT-2008.csv')
elif(self.sma[-1] < bar.getPrice() and self.position) :
print "buy " + str(bar.getDateTime())
self.position.exitMarket()
#self.info("%s %s" % (bar.getClose(), self.__sma[-1]))
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
self.info('BUY ' + str(self.order) + ' ' + tick + ' at $%.2f/share' % (execInfo.getPrice()))
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
self.info('SELL ' + str(self.order) + ' ' + tick + ' at $%.2f/share' % (execInfo.getPrice()))
self.position = None
# Load the yahoo feed from the CSV file
filename = 'orcl-2016.csv'
tick = 'infy.ns'
year = 2016
yahoofinance.download_daily_bars(tick, year, filename)
feed = yahoofeed.Feed()
feed.addBarsFromCSV(tick, filename)
# Evaluate the strategy with the feed's bars.
myStrategy = MyStrategy(feed, tick, 10)
myStrategy.run()
import sys
from pyalgotrade.tools import yahoofinance;
yahoofinance.download_daily_bars('2342.hk',int(sys.argv[1]), 'comb-%s.csv' % sys.argv[1])
from pyalgotrade.tools import yahoofinance
import sys
for i in range(2010,2017):
yahoofinance.download_daily_bars(sys.argv[1], i, sys.argv[1] + '-' + str(i) + '.csv')
print 'Done..'
from pyalgotrade.tools import yahoofinance
yahoofinance.download_daily_bars('aeti', 2011, 'aeti-2011-yahoofinance.csv')
yahoofinance.download_daily_bars('egan', 2011, 'egan-2011-yahoofinance.csv')
yahoofinance.download_daily_bars('glng', 2011, 'glng-2011-yahoofinance.csv')
yahoofinance.download_daily_bars('simo', 2011, 'simo-2011-yahoofinance.csv')
from pyalgotrade import strategy
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.technical import ma
from pyalgotrade.tools import yahoofinance
yahoofinance.download_daily_bars('orcl', 2000, 'orcl-2000.csv')
main_out = []
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, smaPeriod):
strategy.BacktestingStrategy.__init__(self, feed, 1000)
self.__position = None
self.__instrument = instrument
# We'll use adjusted close values instead of regular close values.
self.getBroker().setUseAdjustedValues(True)
self.__sma = ma.SMA(feed[instrument].getAdjCloseDataSeries(), smaPeriod)
main_out = []
def onStart(self):
main_out.append("Initial portfolio value: $%.2f" % self.getBroker().getEquity())
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
main_out.append("%s: BUY at $%.2f" % (execInfo.getDateTime(), execInfo.getPrice()))
def onEnterCanceled(self, position):
self.__position = None
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
main_out.append("%s: SELL at $%.2f" % (execInfo.getDateTime(), execInfo.getPrice()))
self.__position = None
import os
import os.path
from pyalgotrade.tools import yahoofinance
dir = 'data'
if not os.path.isdir(dir): os.makedirs(dir)
years = [2016]
for year in years:
with open("atleast20.txt", "r") as ins:
for line in ins:
s = line.strip()
file_name = "%s/%s - %s.csv" % (dir, s, year)
try:
if not os.path.isfile(file_name):
yahoofinance.download_daily_bars(s, year, file_name)
except:
print "ERROR => %s" % s
def build_feed(instruments,
fromYear,
toYear,
storage,
frequency=bar.Frequency.DAY,
timezone=None,
skipErrors=False,
authToken=None,
columnNames={},
forceDownload=False,
skipMalformedBars=False):
"""Build and load a :class:`pyalgotrade.barfeed.coinmarketcapfeed.Feed` using CSV files downloaded from Quandl.
CSV files are downloaded if they haven't been downloaded before.
:param sourceCode: The dataset source code.
:type sourceCode: string.
:param tableCodes: The dataset table codes.
:type tableCodes: list.
:param fromYear: The first year.
:type fromYear: int.
:param toYear: The last year.
:type toYear: int.
:param storage: The path were the files will be loaded from, or downloaded to.
:type storage: string.
:param frequency: The frequency of the bars. Only **pyalgotrade.bar.Frequency.DAY** or **pyalgotrade.bar.Frequency.WEEK**
are supported.
:param timezone: The default timezone to use to localize bars. Check :mod:`pyalgotrade.marketsession`.
:type timezone: A pytz timezone.
:param skipErrors: True to keep on loading/downloading files in case of errors.
:type skipErrors: boolean.
:param authToken: Optional. An authentication token needed if you're doing more than 50 calls per day.
:type authToken: string.
:param columnNames: Optional. A dictionary to map column names. Valid key values are:
* datetime
* open
* high
* low
* close
* volume
* adj_close
:type columnNames: dict.
:param skipMalformedBars: True to skip errors while parsing bars.
:type skipMalformedBars: boolean.
:rtype: :class:`pyalgotrade.barfeed.coinmarketcapfeed.Feed`.
"""
logger = pyalgotrade.logger.getLogger("data")
ret = Feed(frequency, timezone)
# Additional column names.
for col, name in six.iteritems(columnNames):
ret.setColumnName(col, name)
if not os.path.exists(storage):
logger.info("Creating %s directory" % (storage))
os.mkdir(storage)
for year in range(fromYear, toYear + 1):
for instrument in instruments:
datasource = instrument.datasource()
fileName = os.path.join(storage,
f'{instrument}-{year}-{datasource}.csv')
if not os.path.exists(fileName) or forceDownload:
logger.info("Downloading %s %d to %s" %
(instrument, year, fileName))
try:
assert frequency == bar.Frequency.DAY, "Invalid frequency"
if datasource == DATASOURCE_COINMARKETCAP:
coinmarketcap.download_daily_bars(
instrument, year, fileName, authToken)
else:
assert datasource == DATASOURCE_YAHOOFINANCE, "Invalid data source"
yahoofinance.download_daily_bars(
instrument, year, fileName, authToken)
except Exception as e:
if skipErrors:
logger.error(str(e))
continue
else:
raise e
ret.addBarsFromCSV(instrument,
fileName,
skipMalformedBars=skipMalformedBars)
return ret
from pyalgotrade import strategy
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.technical import ma
from pyalgotrade.tools import yahoofinance
yahoofinance.download_daily_bars('orcl', 2000, 'orcl-2000.csv')
main_out = []
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, instrument, smaPeriod):
strategy.BacktestingStrategy.__init__(self, feed, 1000)
self.__position = None
self.__instrument = instrument
# We'll use adjusted close values instead of regular close values.
self.getBroker().setUseAdjustedValues(True)
self.__sma = ma.SMA(feed[instrument].getAdjCloseDataSeries(), smaPeriod)
main_out = []
def onStart(self):
main_out.append("Initial portfolio value: $%.2f" % self.getBroker().getEquity())
def onEnterOk(self, position):
execInfo = position.getEntryOrder().getExecutionInfo()
main_out.append("%s: BUY at $%.2f" % (execInfo.getDateTime(), execInfo.getPrice()))
def onEnterCanceled(self, position):
self.__position = None
def onExitOk(self, position):
execInfo = position.getExitOrder().getExecutionInfo()
main_out.append("%s: SELL at $%.2f" % (execInfo.getDateTime(), execInfo.getPrice()))
self.__position = None
def onExitCanceled(self, position):
# If the exit was canceled, re-submit it.
self.__position.exit()
def onBars(self, bars):
from pyalgotrade.tools import yahoofinance;
yahoofinance.download_daily_bars('aeti', 2011, 'aeti-2011-yahoofinance.csv')
yahoofinance.download_daily_bars('egan', 2011, 'egan-2011-yahoofinance.csv')
yahoofinance.download_daily_bars('glng', 2011, 'glng-2011-yahoofinance.csv')
yahoofinance.download_daily_bars('simo', 2011, 'simo-2011-yahoofinance.csv')
def main(tick, year, cash, smaPeriod, order):
print 'Welcome, ' + os.environ['USER'] + '!'
print 'Backtesting ' + tick + ' in ' + str(year)
# Download daily bars
filename = tick + '-' + str(year) + '.csv'
yahoofinance.download_daily_bars(tick, year, filename)
# Load CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV(tick, filename)
# Evaluate Strategy
strategySMA = StrategySMA(feed, tick, smaPeriod, order, cash)
# Attach a returns analyzers to the strategy.
retAnalyzer = returns.Returns()
strategySMA.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strategySMA.attachAnalyzer(sharpeRatioAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(strategySMA)
# Include the SMA in the instrument's subplot to get it displayed along with the closing prices.
plt.getInstrumentSubplot(tick).addDataSeries("SMA", strategySMA.getSMA())
# Set portfolio cash
strategySMA.getBroker().setCash(cash)
initial = strategySMA.getBroker().getEquity()
# Run the strategy
strategySMA.run()
# Print the results
print '*' * 60
print 'Initial portfolio value: $%.2f' % initial
final = strategySMA.getBroker().getEquity()
print 'Final portfolio value: $%.2f' % final
net = final - initial
if net > 0:
print 'Net gain: $%.2f' % net
else:
print 'Net loss: $%.2f' % net
percentage = (final - initial) / initial * 100
if percentage > 0:
print 'Percentage gain: +%.2f%%' % percentage
else:
print 'Percentage loss: %.2f%%' % percentage
#print 'Final portfolio value: $%.2f' % strategySMA.getResult()
print 'Annual return: %.2f%%' % (retAnalyzer.getCumulativeReturns()[-1] *
100)
print 'Average daily return: %.2f%%' % (
stats.mean(retAnalyzer.getReturns()) * 100)
print 'Std. dev. daily return: %.4f' % (stats.stddev(
retAnalyzer.getReturns()))
print 'Sharpe ratio: %.2f' % (sharpeRatioAnalyzer.getSharpeRatio(0))
# Plot the strategy
plt.plot()
from pyalgotrade.tools import yahoofinance
yahoofinance.download_daily_bars('orcl', 2000, 'orcl-2000.csv')
# Wait for enough bars to be available to calculate a SMA.
if self.__sma[-1] is None:
return
bar = bars[self.__instrument]
# If a position was not opened, check if we should enter a long position.
if self.__position is None:
if bar.getPrice() > self.__sma[-1]:
# Enter a buy market order for 10 shares. The order is good till canceled.
self.__position = self.enterLong(self.__instrument, 10, True)
# Check if we have to exit the position.
elif bar.getPrice() < self.__sma[-1] and not self.__position.exitActive():
self.__position.exitMarket()
def run_strategy(smaPeriod,ticker,filename):
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV(ticker, filename)
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed,ticker,smaPeriod)
myStrategy.run()
print "Final portfolio value: $%.2f" % myStrategy.getBroker().getEquity()
print 'Argument List:', str(sys.argv)
ticker=sys.argv[1]
smaval=sys.argv[2]
#Fetch the datafile for the given stock
yahoofinance.download_daily_bars(ticker,2014, 'datafile.csv')
run_strategy(int(smaval),ticker,'datafile.csv')
