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 = "002941"
bBandsPeriod = 10
# Download the bars.
feed = yahoofeed.Feed()
feed.addBarsFromCSV("002941", "F:/shuju/002941-orcl.csv")
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 Function_form( bBandsPeriod,smaPeriod_short,smaPeriod_long, slopePeriod,plot=False):
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
from pyalgotrade import strategy
from pyalgotrade.strategy import position
from pyalgotrade import plotter
from pyalgotrade.tools import yahoofinance
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.technical import bollinger
from pyalgotrade.stratanalyzer import sharpe
import BBands_mod
#import report
import matplotlib.pyplot as plt
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV("orcl", "data_daily.csv")
#def main(plot):
instrument = "orcl"
# Evaluate the strategy with the feed's bars.
myStrategy = BBands_mod.BBands(feed, instrument, bBandsPeriod,smaPeriod_short,smaPeriod_long,slopePeriod)
if plot:
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries("upper", myStrategy.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries("middle", myStrategy.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries("lower", myStrategy.getBollingerBands().getLowerBand())
# Attach different analyzers to a strategy before executing it.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
myStrategy.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
myStrategy.attachAnalyzer(tradesAnalyzer)
# Run the strategy.
myStrategy.run()
print "Final portfolio value: $%.2f" % myStrategy.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
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())
returns = tradesAnalyzer.getAllReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Profitable trades: %d" % (tradesAnalyzer.getProfitableCount())
if tradesAnalyzer.getProfitableCount() > 0:
profits = tradesAnalyzer.getProfits()
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())
returns = tradesAnalyzer.getPositiveReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Unprofitable trades: %d" % (tradesAnalyzer.getUnprofitableCount())
if tradesAnalyzer.getUnprofitableCount() > 0:
losses = tradesAnalyzer.getLosses()
print "Avg. loss: $%2.f" % (losses.mean())
print "Losses std. dev.: $%2.f" % (losses.std())
print "Max. loss: $%2.f" % (losses.min())
print "Min. loss: $%2.f" % (losses.max())
returns = tradesAnalyzer.getNegativeReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
if plot:
plt.plot()
return (myStrategy.getResult(),retAnalyzer.getCumulativeReturns()[-1] * 100,
sharpeRatioAnalyzer.getSharpeRatio(0.05), drawDownAnalyzer.getMaxDrawDown() * 100)
#def main(plot):
instrument = "orcl"
bBandsPeriod = 48
smaPeriod_short = 20
smaPeriod_long = 35
slopePeriod = 40
plot = True
# Evaluate the strategy with the feed's bars.
myStrategy = BBands_mod.BBands(feed, instrument, bBandsPeriod, smaPeriod_short,
smaPeriod_long, slopePeriod)
if plot:
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"upper",
myStrategy.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"middle",
myStrategy.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"lower",
myStrategy.getBollingerBands().getLowerBand())
# Attach different analyzers to a strategy before executing it.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
myStrategy.attachAnalyzer(drawDownAnalyzer)
path = "..\\histdata\\day\\"
elif frequency == bar.Frequency.SECOND:
path = "..\\histdata\\tick\\"
filepath = path +'stock_'+ instrument + "_"+date+".csv"
#############################################don't change ############################33
from pyalgotrade.barfeed.csvfeed import GenericBarFeed
barfeed = GenericBarFeed(frequency)
barfeed.setDateTimeFormat('%Y-%m-%d %H:%M:%S')
barfeed.addBarsFromCSV(instrument, filepath)
strat = strat(barfeed, instrument, *paras)
if plot:
plt = plotter.StrategyPlotter(strat)
plt.getInstrumentSubplot(instrument).addDataSeries("upper", strat.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries("middle", strat.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries("lower", strat.getBollingerBands().getLowerBand())
position = strat.getTest()
plt.getOrCreateSubplot("position").addDataSeries("position", position)
#position = strat.getTest()
#plt.getOrCreateSubplot("position").addDataSeries("position", position)
#plt.getOrCreateSubplot("macd").addDataSeries('macd2',strat.getMACD2())
strat.run()
if plot:
plt.plot()
def Function_form(bBandsPeriod,
smaPeriod_short,
smaPeriod_long,
slopePeriod,
plot=False):
from pyalgotrade.stratanalyzer import returns
from pyalgotrade.stratanalyzer import sharpe
from pyalgotrade.stratanalyzer import drawdown
from pyalgotrade.stratanalyzer import trades
from pyalgotrade import strategy
from pyalgotrade.strategy import position
from pyalgotrade import plotter
from pyalgotrade.tools import yahoofinance
from pyalgotrade.barfeed import yahoofeed
from pyalgotrade.technical import bollinger
from pyalgotrade.stratanalyzer import sharpe
import BBands_mod
#import report
import matplotlib.pyplot as plt
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV("orcl", "data_daily.csv")
#def main(plot):
instrument = "orcl"
# Evaluate the strategy with the feed's bars.
myStrategy = BBands_mod.BBands(feed, instrument, bBandsPeriod,
smaPeriod_short, smaPeriod_long,
slopePeriod)
if plot:
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"upper",
myStrategy.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"middle",
myStrategy.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(instrument).addDataSeries(
"lower",
myStrategy.getBollingerBands().getLowerBand())
# Attach different analyzers to a strategy before executing it.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
drawDownAnalyzer = drawdown.DrawDown()
myStrategy.attachAnalyzer(drawDownAnalyzer)
tradesAnalyzer = trades.Trades()
myStrategy.attachAnalyzer(tradesAnalyzer)
# Run the strategy.
myStrategy.run()
print "Final portfolio value: $%.2f" % myStrategy.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
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())
returns = tradesAnalyzer.getAllReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Profitable trades: %d" % (tradesAnalyzer.getProfitableCount())
if tradesAnalyzer.getProfitableCount() > 0:
profits = tradesAnalyzer.getProfits()
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())
returns = tradesAnalyzer.getPositiveReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
print
print "Unprofitable trades: %d" % (tradesAnalyzer.getUnprofitableCount())
if tradesAnalyzer.getUnprofitableCount() > 0:
losses = tradesAnalyzer.getLosses()
print "Avg. loss: $%2.f" % (losses.mean())
print "Losses std. dev.: $%2.f" % (losses.std())
print "Max. loss: $%2.f" % (losses.min())
print "Min. loss: $%2.f" % (losses.max())
returns = tradesAnalyzer.getNegativeReturns()
print "Avg. return: %2.f %%" % (returns.mean() * 100)
print "Returns std. dev.: %2.f %%" % (returns.std() * 100)
print "Max. return: %2.f %%" % (returns.max() * 100)
print "Min. return: %2.f %%" % (returns.min() * 100)
if plot:
plt.plot()
return (myStrategy.getResult(),
retAnalyzer.getCumulativeReturns()[-1] * 100,
sharpeRatioAnalyzer.getSharpeRatio(0.05),
drawDownAnalyzer.getMaxDrawDown() * 100)
@author: syono
"""
from cybos import *
import pandas as pd
import matplotlib.pyplot as plt
from strategy import BollingerStrategy, BuyAndHoldStrategy
from barfeed import dataframefeed
from pyalgotrade import plotter
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)
myStrategy = BollingerStrategy(feed, 'targetStock', initialCash, 20, 1.8)
plt = plotter.StrategyPlotter(myStrategy)
subplot = plt.getInstrumentSubplot('targetStock')
subplot.addDataSeries("Middle", myStrategy.getMiddle())
subplot.addDataSeries("Upper", myStrategy.getUpper())
subplot.addDataSeries("Lower", myStrategy.getLower())
myStrategy.run()
print "Bollinger Band: Final portfolio value: $%.2f" % myStrategy.getBroker(
).getEquity()
plt.plot()