def testInvalidInstrument(self):
instrument = "inexistent"
# Don't skip errors.
with self.assertRaisesRegexp(Exception, "404 Client Error: Not Found"):
with common.TmpDir() as tmpPath:
quandl.build_feed(instrument, [instrument],
PRICE_CURRENCY,
2010,
2010,
tmpPath,
bar.Frequency.WEEK,
authToken=QUANDL_API_KEY)
# Skip errors.
with common.TmpDir() as tmpPath:
bf = quandl.build_feed(instrument, [instrument],
PRICE_CURRENCY,
2010,
2010,
tmpPath,
bar.Frequency.WEEK,
skipErrors=True,
authToken=QUANDL_API_KEY)
bf.loadAll()
self.assertNotIn(instrument, bf)
def testBuildFeedWeekly(self):
with common.TmpDir() as tmpPath:
instrument = "AAPL"
bf = quandl.build_feed("WIKI", [instrument],
2010,
2010,
tmpPath,
bar.Frequency.WEEK,
authToken=auth_token)
bf.loadAll()
# Quandl used to report 2010-1-3 as the first week of 2010.
self.assertTrue(bf[instrument][0].getDateTime() in [
datetime.datetime(2010, 1, 3),
datetime.datetime(2010, 1, 10)
])
self.assertEquals(bf[instrument][-1].getDateTime(),
datetime.datetime(2010, 12, 26))
self.assertEquals(bf[instrument][-1].getOpen(), 325.0)
self.assertEquals(bf[instrument][-1].getHigh(), 325.15)
self.assertEquals(bf[instrument][-1].getLow(), 323.17)
self.assertEquals(bf[instrument][-1].getClose(), 323.6)
self.assertEquals(bf[instrument][-1].getVolume(), 7969900)
self.assertEquals(bf[instrument][-1].getPrice(), 323.6)
# Not checking against a specific value since this is going to change
# as time passes by.
self.assertNotEquals(bf[instrument][-1].getAdjClose(), None)
def main(plot):
symbol = "GORO"
priceCurrency = "USD"
instrument = "%s/%s" % (symbol, priceCurrency)
initialBalance = {priceCurrency: 1000000}
# Download GORO bars using WIKI source code.
feed = quandl.build_feed("WIKI", [symbol], "USD", 2006, 2012, ".")
# Load Quandl CSV downloaded from http://www.quandl.com/OFDP-Open-Financial-Data-Project/GOLD_2-LBMA-Gold-Price-London-Fixings-P-M
quandlFeed = csvfeed.Feed("Date", "%Y-%m-%d")
quandlFeed.setDateRange(datetime.datetime(2006, 1, 1),
datetime.datetime(2012, 12, 31))
quandlFeed.addValuesFromCSV("quandl_gold_2.csv")
myStrategy = MyStrategy(feed, quandlFeed, instrument, initialBalance)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(myStrategy, True, False, False)
plt.getOrCreateSubplot("quandl").addDataSeries("USD",
quandlFeed["USD"])
plt.getOrCreateSubplot("quandl").addDataSeries("EUR",
quandlFeed["EUR"])
plt.getOrCreateSubplot("quandl").addDataSeries("GBP",
quandlFeed["GBP"])
myStrategy.run()
if plot:
plt.plot()
def testBuildFeedDailyCreatingDir(self):
tmpPath = tempfile.mkdtemp()
shutil.rmtree(tmpPath)
try:
symbol = "ORCL"
instrument = "%s/%s" % (symbol, PRICE_CURRENCY)
bf = quandl.build_feed("WIKI", [symbol],
PRICE_CURRENCY,
2010,
2010,
tmpPath,
authToken=QUANDL_API_KEY)
bf.loadAll()
ds = bf.getDataSeries(instrument)
self.assertEqual(ds[-1].getDateTime(),
datetime.datetime(2010, 12, 31))
self.assertEqual(ds[-1].getOpen(), 31.22)
self.assertEqual(ds[-1].getHigh(), 31.33)
self.assertEqual(ds[-1].getLow(), 30.93)
self.assertEqual(ds[-1].getClose(), 31.3)
self.assertEqual(ds[-1].getVolume(), 11716300)
self.assertEqual(ds[-1].getPrice(), 31.3)
# Not checking against a specific value since this is going to change
# as time passes by.
self.assertNotEqual(ds[-1].getAdjClose(), None)
finally:
shutil.rmtree(tmpPath)
def testBuildFeedWeekly(self):
with common.TmpDir() as tmpPath:
symbol = "AAPL"
instrument = "%s/%s" % (symbol, PRICE_CURRENCY)
bf = quandl.build_feed("WIKI", [symbol],
PRICE_CURRENCY,
2010,
2010,
tmpPath,
bar.Frequency.WEEK,
authToken=QUANDL_API_KEY)
bf.loadAll()
ds = bf.getDataSeries(instrument)
# Quandl used to report 2010-1-3 as the first week of 2010.
self.assertTrue(ds[0].getDateTime() in [
datetime.datetime(2010, 1, 3),
datetime.datetime(2010, 1, 10)
])
self.assertEqual(ds[-1].getDateTime(),
datetime.datetime(2010, 12, 26))
self.assertEqual(ds[-1].getOpen(), 325.0)
self.assertEqual(ds[-1].getHigh(), 325.15)
self.assertEqual(ds[-1].getLow(), 323.17)
self.assertEqual(ds[-1].getClose(), 323.6)
self.assertEqual(ds[-1].getVolume(), 7969900)
self.assertEqual(ds[-1].getPrice(), 323.6)
# Not checking against a specific value since this is going to change
# as time passes by.
self.assertNotEqual(ds[-1].getAdjClose(), None)
def main(plot):
instruments = ["GORO"]
# Download GORO bars using WIKI source code.
feed = quandl.build_feed("WIKI", instruments, 2006, 2012, ".")
# Load Quandl CSV downloaded from http://www.quandl.com/OFDP-Open-Financial-Data-Project/GOLD_2-LBMA-Gold-Price-London-Fixings-P-M
quandlFeed = csvfeed.Feed("Date", "%Y-%m-%d")
quandlFeed.setDateRange(datetime.datetime(2006, 1, 1),
datetime.datetime(2012, 12, 31))
quandlFeed.addValuesFromCSV("WIKI-GORO-2006-quandl.csv")
myStrategy = MyStrategy(feed, quandlFeed, instruments[0])
if plot:
plt = plotter.StrategyPlotter(myStrategy, True, False, False)
plt.getOrCreateSubplot("quandl").addDataSeries("USD",
quandlFeed["USD"])
plt.getOrCreateSubplot("quandl").addDataSeries("EUR",
quandlFeed["EUR"])
plt.getOrCreateSubplot("quandl").addDataSeries("GBP",
quandlFeed["GBP"])
myStrategy.run()
if plot:
plt.plot()
def genetic_algoritm(N,
gens,
s,
m,
data,
tech_indicators,
instrument,
year,
red_rules=None):
global data_set, total_crossovers, total_mutate, y_info, inst
inst = instrument
start = int(year.split('-')[2])
y_info = quandl.build_feed("WIKI", [instrument], start, start, ".")
total_crossovers = 0
total_mutate = 0
population = makePopulation(data, tech_indicators, N)
if red_rules is not None:
population = set_red_rules(population, red_rules)
for i in range(gens):
print "Create %d generation" % i
population = next_generation(s, m, population)
#createPic(population[len(population)-1],"1")
print "Delete logic violation"
print "Testing stage is over, best fitness is %f" % population[
len(population) - 1].fitness
print "Total mutates %d" % total_mutate
print "Total crossovers %d" % total_crossovers
#createPic(population[len(population)-1],"data/strat_fruct")
#population[len(population)-1].getFitness(data_set,False)
return population[len(population) - 1]
def testMapColumnNames(self):
column_names = {
"open": "Open",
"high": "High",
"low": "Low",
"close": "Last",
"volume": "Volume",
}
with common.TmpDir() as tmpPath:
symbol = "ADYEN"
instrument = "%s/%s" % (symbol, PRICE_CURRENCY)
year = 2018
bf = quandl.build_feed("EURONEXT", [symbol],
PRICE_CURRENCY,
year,
year,
tmpPath,
columnNames=column_names,
skipMalformedBars=True,
authToken=QUANDL_API_KEY)
bf.setNoAdjClose()
bf.loadAll()
ds = bf.getDataSeries(instrument)
self.assertEqual(ds[0].getDateTime(),
datetime.datetime(year, 6, 13))
self.assertEqual(ds[0].getOpen(), 400.00)
self.assertEqual(ds[0].getHigh(), 503.90)
self.assertEqual(ds[0].getLow(), 400.00)
self.assertEqual(ds[0].getClose(), 455.00)
self.assertEqual(ds[0].getVolume(), 1529232)
self.assertEqual(ds[0].getAdjClose(), None)
self.assertEqual(ds[0].getPrice(), 455.00)
def main(plot):
instrument = "yhoo"
bBandsPeriod = 40
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = BBands(feed, instrument, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"upper",
strat.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"middle",
strat.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"lower",
strat.getBollingerBands().getLowerBand())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def testMapColumnNames(self):
column_names = {
"open": "Price",
"close": "Price",
}
with common.TmpDir() as tmpPath:
instrument = "IWG"
year = 2017
bf = quandl.build_feed("LSE", [instrument],
year,
year,
tmpPath,
columnNames=column_names,
skipMalformedBars=True,
authToken=QUANDL_API_KEY)
bf.setNoAdjClose()
bf.loadAll()
self.assertEqual(bf[instrument][0].getDateTime(),
datetime.datetime(year, 1, 3))
self.assertEqual(bf[instrument][0].getOpen(), 237.80)
self.assertEqual(bf[instrument][0].getHigh(), 247.00)
self.assertEqual(bf[instrument][0].getLow(), 236.30)
self.assertEqual(bf[instrument][0].getClose(), 237.80)
self.assertEqual(bf[instrument][0].getVolume(), 3494173)
self.assertEqual(bf[instrument][0].getAdjClose(), None)
self.assertEqual(bf[instrument][0].getPrice(), 237.80)
def calcStrategy(instrument, start, end, size, gens):
data = get_stock(instrument, start, end, save=True)
tech_indicators = get_indicators(data)
result = parse_data_to_levels(data, tech_indicators)
data = result["data"]
calc_str = genetic_algoritm(size, gens, 0.25, 0.3, data, tech_indicators,
instrument, start)
start_year2 = int(start.split('-')[2]) + 1
start2 = start.split('-')[0] + "-" + start.split('-')[1] + "-" + str(
start_year2)
end2 = end.split('-')[0] + "-" + end.split('-')[1] + "-" + str(start_year2)
data2 = get_stock(instrument, start2, end2)
data2 = parse_data_to_levels(data2, tech_indicators)
getFitness(data2["data"], calc_str, setResults=True)
result = data2["data"]
weights = result["Weight"]
t = Test(
quandl.build_feed("WIKI", [instrument], start_year2, start_year2, "."),
instrument, weights)
stats = Statistics(t)
print "Final Strategy"
print calc_str
#generatePDF(stats, start+" по " +end, start2 + " по " + end2)
stats.printResults()
def main(plot):
symbol = "yhoo"
priceCurrency = "USD"
instrument = "%s/%s" % (symbol, priceCurrency)
bBandsPeriod = 40
# Download the bars.
feed = quandl.build_feed("WIKI", [symbol], priceCurrency, 2011, 2012, ".")
broker = backtesting.Broker({priceCurrency: 1000000}, feed)
strat = BBands(feed, broker, instrument, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio(priceCurrency)
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries("upper", strat.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries("middle", strat.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries("lower", strat.getBollingerBands().getLowerBand())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main(plot):
symbol = "AAPL"
priceCurrency = "USD"
instrument = "%s/%s" % (symbol, priceCurrency)
initialBalance = {priceCurrency: 1000000}
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
feed = quandl.build_feed("WIKI", [symbol], priceCurrency, 2011, 2012, ".")
strat = VWAPMomentum(feed, instrument, initialBalance, vwapWindowSize,
threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio(priceCurrency)
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"vwap", strat.getVWAP())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def testInvalidInstrument(self):
instrument = "inexistent"
# Don't skip errors.
with self.assertRaisesRegexp(Exception, "HTTP Error 404: Not Found"):
with common.TmpDir() as tmpPath:
quandl.build_feed(
instrument, [instrument], 2010, 2010, tmpPath, bar.Frequency.WEEK, authToken=auth_token
)
# Skip errors.
with common.TmpDir() as tmpPath:
bf = quandl.build_feed(
instrument, [instrument], 2010, 2010, tmpPath, bar.Frequency.WEEK, authToken=auth_token, skipErrors=True
)
bf.loadAll()
self.assertNotIn(instrument, bf)
def testMapColumnNames(self):
with common.TmpDir() as tmpPath:
bf = quandl.build_feed("YAHOO", ["AAPL"], 2010, 2010, tmpPath, columnNames={"adj_close": "Adjusted Close"})
bf.setUseAdjustedValues(True)
bf.loadAll()
self.assertEquals(bf["AAPL"][-1].getClose(), 322.560013)
self.assertIsNotNone(bf["AAPL"][-1].getAdjClose())
self.assertIsNotNone(bf["AAPL"][-1].getPrice())
def main(plot):
instruments = ["IBM", "AES", "AIG"]
feed = quandl.build_feed("WIKI", instruments, 2008, 2009, ".")
predicate = BuyOnGap(feed)
eventProfiler = eventprofiler.Profiler(predicate, 5, 5)
eventProfiler.run(feed, True)
results = eventProfiler.getResults()
print("%d events found" % (results.getEventCount()))
if plot:
eventprofiler.plot(results)
def testExtraColumns(self):
with common.TmpDir() as tmpPath:
columnNames = {
"open": "Last",
"close": "Last"
}
bf = quandl.build_feed("BITSTAMP", ["USD"], 2014, 2014, tmpPath, columnNames=columnNames)
bf.loadAll()
self.assertEquals(bf["USD"][-1].getExtraColumns()["Bid"], 319.19)
self.assertEquals(bf["USD"][-1].getExtraColumns()["Ask"], 319.63)
bids = bf["USD"].getExtraDataSeries("Bid")
self.assertEquals(bids[-1], 319.19)
def testMapColumnNames(self):
with common.TmpDir() as tmpPath:
bf = quandl.build_feed("YAHOO", ["AAPL"],
2010,
2010,
tmpPath,
columnNames={"adj_close": "Adjusted Close"})
bf.setUseAdjustedValues(True)
bf.loadAll()
self.assertEquals(bf["AAPL"][-1].getClose(), 322.560013)
self.assertIsNotNone(bf["AAPL"][-1].getAdjClose())
self.assertIsNotNone(bf["AAPL"][-1].getPrice())
def testBuildFeedDaily(self):
with common.TmpDir() as tmpPath:
instrument = "ORCL"
bf = quandl.build_feed("WIKI", [instrument], 2010, 2010, tmpPath, authToken=auth_token)
bf.loadAll()
self.assertEquals(bf[instrument][-1].getDateTime(), datetime.datetime(2010, 12, 31))
self.assertEquals(bf[instrument][-1].getOpen(), 31.22)
self.assertEquals(bf[instrument][-1].getHigh(), 31.33)
self.assertEquals(bf[instrument][-1].getLow(), 30.93)
self.assertEquals(bf[instrument][-1].getClose(), 31.3)
self.assertEquals(bf[instrument][-1].getVolume(), 11716300)
self.assertEquals(bf[instrument][-1].getAdjClose(), 30.23179912467581)
self.assertEquals(bf[instrument][-1].getPrice(), 31.3)
def testNoAdjClose(self):
with common.TmpDir() as tmpPath:
columnNames = {"open": "Last", "close": "Last", "adj_close": None}
bf = quandl.build_feed("BITSTAMP", ["USD"],
2014,
2014,
tmpPath,
columnNames=columnNames,
authToken=QUANDL_API_KEY)
bf.loadAll()
self.assertFalse(bf.barsHaveAdjClose())
self.assertEqual(bf["USD"][-1].getAdjClose(), None)
def testExtraColumns(self):
with common.TmpDir() as tmpPath:
columnNames = {"open": "Last", "close": "Last"}
bf = quandl.build_feed("BITSTAMP", ["USD"],
2014,
2014,
tmpPath,
columnNames=columnNames)
bf.loadAll()
self.assertEquals(bf["USD"][-1].getExtraColumns()["Bid"], 319.19)
self.assertEquals(bf["USD"][-1].getExtraColumns()["Ask"], 319.63)
bids = bf["USD"].getExtraDataSeries("Bid")
self.assertEquals(bids[-1], 319.19)
def main(plot):
symbols = ["IBM", "AES", "AIG"]
priceCurrency = "USD"
feed = quandl.build_feed("WIKI", symbols, priceCurrency, 2008, 2009, ".")
instruments = ["%s/%s" % (symbol, priceCurrency) for symbol in symbols]
predicate = BuyOnGap(feed, instruments)
eventProfiler = eventprofiler.Profiler(predicate, 5, 5)
eventProfiler.run(feed, True)
results = eventProfiler.getResults()
print("%d events found" % (results.getEventCount()))
if plot:
eventprofiler.plot(results)
def testBuildFeedDaily(self):
with common.TmpDir() as tmpPath:
instrument = "ORCL"
bf = quandl.build_feed("WIKI", [instrument], 2010, 2010, tmpPath, authToken=auth_token)
bf.loadAll()
self.assertEquals(bf[instrument][-1].getDateTime(), datetime.datetime(2010, 12, 31))
self.assertEquals(bf[instrument][-1].getOpen(), 31.22)
self.assertEquals(bf[instrument][-1].getHigh(), 31.33)
self.assertEquals(bf[instrument][-1].getLow(), 30.93)
self.assertEquals(bf[instrument][-1].getClose(), 31.3)
self.assertEquals(bf[instrument][-1].getVolume(), 11716300)
self.assertEquals(bf[instrument][-1].getPrice(), 31.3)
# Not checking against a specific value since this is going to change
# as time passes by.
self.assertNotEquals(bf[instrument][-1].getAdjClose(), None)
def testBuildFeedDaily(self):
with common.TmpDir() as tmpPath:
instrument = "ORCL"
bf = quandl.build_feed("WIKI", [instrument], 2010, 2010, tmpPath, authToken=auth_token)
bf.loadAll()
self.assertEquals(bf[instrument][-1].getDateTime(), datetime.datetime(2010, 12, 31))
self.assertEquals(bf[instrument][-1].getOpen(), 31.22)
self.assertEquals(bf[instrument][-1].getHigh(), 31.33)
self.assertEquals(bf[instrument][-1].getLow(), 30.93)
self.assertEquals(bf[instrument][-1].getClose(), 31.3)
self.assertEquals(bf[instrument][-1].getVolume(), 11716300)
self.assertEquals(bf[instrument][-1].getPrice(), 31.3)
# Not checking against a specific value since this is going to change
# as time passes by.
self.assertNotEquals(bf[instrument][-1].getAdjClose(), None)
def testNoAdjClose(self):
with common.TmpDir() as tmpPath:
columnNames = {
"open": "Last",
"close": "Last",
"adj_close": None
}
bf = quandl.build_feed(
"BITSTAMP", ["USD"], 2014, 2014, tmpPath, columnNames=columnNames,
authToken=QUANDL_API_KEY
)
bf.loadAll()
self.assertFalse(bf.barsHaveAdjClose())
self.assertEquals(bf["USD"][-1].getAdjClose(), None)
def testBuildFeedWeekly(self):
with common.TmpDir() as tmpPath:
instrument = "AAPL"
bf = quandl.build_feed("WIKI", [instrument], 2010, 2010, tmpPath, bar.Frequency.WEEK, authToken=auth_token)
bf.loadAll()
self.assertEquals(bf[instrument][0].getDateTime(), datetime.datetime(2010, 1, 3))
self.assertEquals(bf[instrument][-1].getDateTime(), datetime.datetime(2010, 12, 26))
self.assertEquals(bf[instrument][-1].getOpen(), 325.0)
self.assertEquals(bf[instrument][-1].getHigh(), 325.15)
self.assertEquals(bf[instrument][-1].getLow(), 323.17)
self.assertEquals(bf[instrument][-1].getClose(), 323.6)
self.assertEquals(bf[instrument][-1].getVolume(), 7969900)
self.assertEquals(bf[instrument][-1].getPrice(), 323.6)
# Not checking against a specific value since this is going to change
# as time passes by.
self.assertNotEquals(bf[instrument][-1].getAdjClose(), None)
def testNoAdjClose(self):
with common.TmpDir() as tmpPath:
columnNames = {"open": "Last", "close": "Last", "adj_close": None}
symbol = "BTC"
instrument = "%s/%s" % (symbol, PRICE_CURRENCY)
bf = quandl.build_feed("BITSTAMP", {"USD": symbol},
PRICE_CURRENCY,
2014,
2014,
tmpPath,
columnNames=columnNames,
authToken=QUANDL_API_KEY)
bf.loadAll()
ds = bf.getDataSeries(instrument)
self.assertFalse(bf.barsHaveAdjClose())
self.assertEqual(ds[-1].getAdjClose(), None)
def testBuildFeedDaily(self):
with common.TmpDir() as tmpPath:
instrument = "ORCL"
bf = quandl.build_feed("WIKI", [instrument],
2010,
2010,
tmpPath,
authToken=auth_token)
bf.loadAll()
self.assertEquals(bf[instrument][-1].getDateTime(),
datetime.datetime(2010, 12, 31))
self.assertEquals(bf[instrument][-1].getOpen(), 31.22)
self.assertEquals(bf[instrument][-1].getHigh(), 31.33)
self.assertEquals(bf[instrument][-1].getLow(), 30.93)
self.assertEquals(bf[instrument][-1].getClose(), 31.3)
self.assertEquals(bf[instrument][-1].getVolume(), 11716300)
self.assertEquals(bf[instrument][-1].getAdjClose(),
30.23179912467581)
self.assertEquals(bf[instrument][-1].getPrice(), 31.3)
def main(plot):
instrument = "TSLA"
vwapWindowSize = 60
threshold = 0.00000001
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2007, 2018, ".")
strat = VWAPMomentum(feed, instrument, vwapWindowSize, threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
retAnalyzer = returns.Returns()
strat.attachAnalyzer(retAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
strat.attachAnalyzer(tradesAnalyzer)
returns3 = tradesAnalyzer.getAllReturns()
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"vwap", strat.getVWAP())
strat.run()
print("Final portfolio value: $%.2f" % strat.getResult())
print("Cumulative returns: %.2f %%" %
(retAnalyzer.getCumulativeReturns()[-1] * 100))
print("Sharpe ratio: %.2f" % (sharpeRatioAnalyzer.getSharpeRatio(0.05)))
print("Max. drawdown: %.2f %%" % (drawDownAnalyzer.getMaxDrawDown() * 100))
print("Longest drawdown duration: %s" %
(drawDownAnalyzer.getLongestDrawDownDuration()))
print(retAnalyzer.getReturns())
print("")
print("Total trades: %d" % (tradesAnalyzer.getCount()))
if tradesAnalyzer.getCount() > 0:
profits = tradesAnalyzer.getAll()
print("Avg. profit: $%2.f" % (profits.mean()))
print("Profits std. dev.: $%2.f" % (profits.std()))
print("Max. profit: $%2.f" % (profits.max()))
print("Min. profit: $%2.f" % (profits.min()))
print(stats.ttest_1samp(tradesAnalyzer.getAllReturns(), 0))
if plot:
plt.plot()
def main(plot):
instrument = "AAPL"
smaPeriod = 163
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = sma_crossover.SMACrossOver(feed, instrument, smaPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries("sma", strat.getSMA())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def testBuildFeedDailyCreatingDir(self):
tmpPath = tempfile.mkdtemp()
shutil.rmtree(tmpPath)
try:
instrument = "ORCL"
bf = quandl.build_feed("WIKI", [instrument], 2010, 2010, tmpPath, authToken=QUANDL_API_KEY)
bf.loadAll()
self.assertEquals(bf[instrument][-1].getDateTime(), datetime.datetime(2010, 12, 31))
self.assertEquals(bf[instrument][-1].getOpen(), 31.22)
self.assertEquals(bf[instrument][-1].getHigh(), 31.33)
self.assertEquals(bf[instrument][-1].getLow(), 30.93)
self.assertEquals(bf[instrument][-1].getClose(), 31.3)
self.assertEquals(bf[instrument][-1].getVolume(), 11716300)
self.assertEquals(bf[instrument][-1].getPrice(), 31.3)
# Not checking against a specific value since this is going to change
# as time passes by.
self.assertNotEquals(bf[instrument][-1].getAdjClose(), None)
finally:
shutil.rmtree(tmpPath)
def main(plot):
instrument = "AAPL"
smaPeriod = 30
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument,"NVDA"], 2016, 2018, Constants.data_directory)
strategy = sma_crossover.SMACrossOver(feed, instrument, smaPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strategy.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strategy, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries("sma", strategy.getSMA())
strategy.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main():
instrument = "AAPL"
vwapWindowSize = 5
threshold = 0.01
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = VWAPMomentum(feed, instrument, vwapWindowSize, threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
plter = plotter.StrategyPlotter(strat, True, True, True)
plter.getInstrumentSubplot(instrument).addDataSeries(
"vwap", strat.getVWAP())
strat.run()
print("夏普比例:%.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.03))
print("期末策略市值:%.2f" % strat.getResult())
plter.savePlot("mytry.png")
def main(plot):
instrument = "AAPL"
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = VWAPMomentum(feed, instrument, vwapWindowSize, threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries("vwap", strat.getVWAP())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main(plot):
instrument = "AAPL"
smaPeriod = 163
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = sma_crossover.SMACrossOver(feed, instrument, smaPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"sma", strat.getSMA())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def testExtraColumns(self):
with common.TmpDir() as tmpPath:
columnNames = {"open": "Last", "close": "Last"}
symbol = "BTC"
instrument = "%s/%s" % (symbol, PRICE_CURRENCY)
bf = quandl.build_feed("BITSTAMP", {"USD": symbol},
PRICE_CURRENCY,
2014,
2014,
tmpPath,
columnNames=columnNames,
authToken=QUANDL_API_KEY)
bf.loadAll()
ds = bf.getDataSeries(instrument)
self.assertEqual(len(ds[-1].getExtraColumns()), 3)
self.assertEqual(ds[-1].getExtraColumns()["Bid"], 319.19)
self.assertEqual(ds[-1].getExtraColumns()["Ask"], 319.63)
bids = ds.getExtraDataSeries("Bid")
self.assertEqual(bids[-1], 319.19)
def testMapColumnNames(self):
column_names = {
"open": "Price",
"close": "Price",
}
with common.TmpDir() as tmpPath:
instrument = "IWG"
year = 2017
bf = quandl.build_feed(
"LSE", [instrument], year, year, tmpPath, columnNames=column_names, skipMalformedBars=True,
authToken=QUANDL_API_KEY
)
bf.setNoAdjClose()
bf.loadAll()
self.assertEquals(bf[instrument][0].getDateTime(), datetime.datetime(year, 1, 3))
self.assertEquals(bf[instrument][0].getOpen(), 237.80)
self.assertEquals(bf[instrument][0].getHigh(), 247.00)
self.assertEquals(bf[instrument][0].getLow(), 236.30)
self.assertEquals(bf[instrument][0].getClose(), 237.80)
self.assertEquals(bf[instrument][0].getVolume(), 3494173)
self.assertEquals(bf[instrument][0].getAdjClose(), None)
self.assertEquals(bf[instrument][0].getPrice(), 237.80)
def main(plot):
instrument = "yhoo"
bBandsPeriod = 40
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = BBands(feed, instrument, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries("upper", strat.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries("middle", strat.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries("lower", strat.getBollingerBands().getLowerBand())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main(plot):
instrument = "AAPL"
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
feed = quandl.build_feed("WIKI", [instrument], 2011, 2012, ".")
strat = VWAPMomentum(feed, instrument, vwapWindowSize, threshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"vwap", strat.getVWAP())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main(plot):
instruments = ["GORO"]
# Download GORO bars using WIKI source code.
feed = quandl.build_feed("WIKI", instruments, 2006, 2012, "data")
# Load Quandl CSV downloaded from http://www.quandl.com/OFDP-Open-Financial-Data-Project/GOLD_2-LBMA-Gold-Price-London-Fixings-P-M
quandlFeed = csvfeed.Feed("Date", "%Y-%m-%d")
quandlFeed.setDateRange(datetime.datetime(2006, 1, 1), datetime.datetime(2012, 12, 31))
quandlFeed.addValuesFromCSV("quandl_gold_2.csv")
myStrategy = MyStrategy(feed, quandlFeed, instruments[0])
if plot:
plt = plotter.StrategyPlotter(myStrategy, True, False, False)
plt.getOrCreateSubplot("quandl").addDataSeries("USD", quandlFeed["USD"])
plt.getOrCreateSubplot("quandl").addDataSeries("EUR", quandlFeed["EUR"])
plt.getOrCreateSubplot("quandl").addDataSeries("GBP", quandlFeed["GBP"])
myStrategy.run()
if plot:
plt.plot()
def main():
instruments = ["AAPL", "NVDA"]
feed = quandl.build_feed("WIKI", instruments, 2016, 2018,
Constants.data_directory)
strategy = MultipleInstrumentStrategy(feed, instruments)
strategy.run()
bars[self.__instrument].getPrice())
# Enter a buy market order. The order is good till canceled.
self.__position = self.enterLong(self.__instrument, shares,
True)
# Check if we have to exit the position.
elif not self.__position.exitActive() and cross.cross_below(
self.__prices, self.__sma) > 0:
self.__position.exitMarket()
from pyalgotrade import plotter
from pyalgotrade.barfeed import quandlfeed
from pyalgotrade.stratanalyzer import returns
#import sma_crossover
data = quandl.build_feed("WIKI", ['ORCL'], 2000, 2000, ".")
# Load the bar feed from the CSV file
feed = quandlfeed.Feed()
feed.addBarsFromCSV("orcl", "WIKI-ORCL-2000-quandl.csv")
# Evaluate the strategy with the feed's bars.
myStrategy = SMACrossOver(feed, "orcl", 20)
# Attach a returns analyzers to the strategy.
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
# Attach the plotter to the strategy.
plt = plotter.StrategyPlotter(myStrategy)
# Include the SMA in the instrument's subplot to get it displayed along with the closing prices.
plt.getInstrumentSubplot("orcl").addDataSeries("SMA", myStrategy.getSMA())
