def bolling(code='600281'):
try:
dat = pd.read_csv("../../api/stock/csv/%sSH_5min.csv" % code,
encoding='gbk')
dat = dat.fillna(method='pad')
dat['Adj Close'] = dat['Close']
dat = dat.rename(
columns={
'Open': 'open',
'High': 'high',
'Volume': 'volume',
'Close': 'close',
'Low': 'low'
})
dat.index = dat['Date Time']
dat.index.name = 'date'
except:
from api.stock.lib import gm_api as gm
dat = gm.gm_api().get_hist_data(code, '2015-01-01', ktype='5')
print(dat)
dat['Adj Close'] = dat['close']
# dat = dat.ix[17000:18000,:]
feed = dataFramefeed.Feed(frequency=bar.Frequency.MINUTE)
feed.addBarsFromDataFrame("orcl", dat)
myStrategy = mdd.bolling_backtest(feed, 'orcl')
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getOrCreateSubplot("returns").addDataSeries(
"Simple returns", returnsAnalyzer.getReturns())
ds = pyalg_utils.dataSet(myStrategy) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
myStrategy.run()
plt.plot()
print('最大回撤：\t%f\t 交易笔数：\t%d\t 盈利笔数：\t%d\n' %
(ds.getMaxDrawDown(), ds.getCount(), ds.getProfitableCount()))
print('累计收益：\t%f\t 夏普比率：\t%f\t' %
(returnsAnalyzer.getCumulativeReturns()[-1], ds.getSharpeRatio()))
def main():
# Load the orders file.
ordersFile = OrdersFile("orders.csv")
print "First date", ordersFile.getFirstDate()
print "Last date", ordersFile.getLastDate()
print "Symbols", ordersFile.getInstruments()
# Load the data from QSTK storage. QS environment variable has to be defined.
if os.getenv("QS") is None:
raise Exception("QS environment variable not defined")
feed = yahoofeed.Feed()
feed.setBarFilter(
csvfeed.DateRangeFilter(ordersFile.getFirstDate(),
ordersFile.getLastDate()))
feed.setDailyBarTime(
datetime.time(0, 0, 0)
) # This is to match the dates loaded with the ones in the orders file.
for symbol in ordersFile.getInstruments():
feed.addBarsFromCSV(
symbol,
os.path.join(os.getenv("QS"), "QSData", "Yahoo", symbol + ".csv"))
# Run the strategy.
cash = 1000000
useAdjustedClose = True
myStrategy = MyStrategy(feed, cash, ordersFile, useAdjustedClose)
# Attach returns and sharpe ratio analyzers.
retAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(retAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
myStrategy.run()
# Print the results.
print "Final portfolio value: $%.2f" % myStrategy.getResult()
print "Anual 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))
def run_strategy(paras):
feed = dataframefeed.Feed()
feed.addBarsFromDataFrame(instrument, dat)
strat = singleMA.SingleMA(feed, instrument, paras, initialCash)
# attach analyzersgc
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
drawdownAnalyzer = drawdown.DrawDown()
strat.attachAnalyzer(drawdownAnalyzer)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
tradeAnalyzer = trades.Trades()
strat.attachAnalyzer(tradeAnalyzer)
strat.run()
print "Final portfolio value: $%.2f with paras %d" % (
strat.getBroker().getEquity(), paras)
return {
'returns':
returnsAnalyzer.getCumulativeReturns()[-1],
'drawdown':
drawdownAnalyzer.getMaxDrawDown(),
'longestDrawDownDuration':
drawdownAnalyzer.getLongestDrawDownDuration(),
'sr':
sharpeRatioAnalyzer.getSharpeRatio(0.03),
'total trades':
tradeAnalyzer.getCount(),
'win':
tradeAnalyzer.getProfitableCount(),
'lose':
tradeAnalyzer.getUnprofitableCount(),
'average win profit':
tradeAnalyzer.getPositiveReturns().mean(),
'average lose loss':
tradeAnalyzer.getNegativeReturns().mean(),
'wining ratio':
tradeAnalyzer.getProfitableCount() / tradeAnalyzer.getCount(),
'odds':
-tradeAnalyzer.getPositiveReturns().mean() /
tradeAnalyzer.getNegativeReturns().mean()
}
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):
cod = "002739"
#万达院线
cname = 'wanda'
fss = "dat\\" + cod + ".csv"
df = pd.read_csv(fss, encoding='gbk')
#df2=zwBox.zw_df2yhaoo(df);
df2 = zwx.df2yhaoo(df)
cfn = "dat\\" + cod + "_yh.csv"
print(fss)
df2.to_csv(cfn, encoding='utf-8')
#
#instrument = "yhoo" #使用新变量名cname替代
#bBandsPeriod = 40
bBandsPeriod = 10
# Download the bars.
#feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(cname, cfn)
strat = BBands(feed, cname, bBandsPeriod)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
mpl.style.use('seaborn-whitegrid')
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(cname).addDataSeries(
"upper",
strat.getBollingerBands().getUpperBand())
plt.getInstrumentSubplot(cname).addDataSeries(
"middle",
strat.getBollingerBands().getMiddleBand())
plt.getInstrumentSubplot(cname).addDataSeries(
"lower",
strat.getBollingerBands().getLowerBand())
strat.run()
print("夏普指数 Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def main():
instruments = ["000651"]
feeds = tools.build_feed(instruments, 2009, 2019, "histdata")
# 3.实例化策略
strat = MyStrategy(feeds, instruments[0])
# 4.设置指标和绘图
ratio = sharpe.SharpeRatio()
strat.attachAnalyzer(ratio)
plter = plotter.StrategyPlotter(strat)
# 5.运行策略
strat.run()
strat.info("最终收益: %.2f" % strat.getResult())
# 6.输出夏普率、绘图
strat.info("夏普比率: " + str(ratio.getSharpeRatio(0)))
plter.plot()
def main(plot):
initialCash = 10000
instrumentsByClass = {
"US Stocks": ["VTI"],
"Foreign Stocks": ["VEU"],
"US 10 Year Government Bonds": ["IEF"],
"Real Estate": ["VNQ"],
"Commodities": ["DBC"],
}
# Download the bars.
instruments = ["SPY"]
for assetClass in instrumentsByClass:
instruments.extend(instrumentsByClass[assetClass])
feed = yahoofinance.build_feed(instruments,
2007,
2013,
"data",
skipErrors=True)
strat = MarketTiming(feed, instrumentsByClass, initialCash)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, False, False, True)
plt.getOrCreateSubplot("cash").addCallback(
"Cash", lambda x: strat.getBroker().getCash())
# Plot strategy vs. SPY cumulative returns.
plt.getOrCreateSubplot("returns").addDataSeries(
"SPY", cumret.CumulativeReturn(feed["SPY"].getPriceDataSeries()))
plt.getOrCreateSubplot("returns").addDataSeries(
"Strategy", returnsAnalyzer.getCumulativeReturns())
strat.run()
print "Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05)
print "Returns: %.2f %%" % (returnsAnalyzer.getCumulativeReturns()[-1] *
100)
if plot:
plt.plot()
def main(plot):
bBandsPeriod = 40
start = datetime(2000, 1, 1, 0, 0, 0, 0, pytz.utc)
end = datetime(2015, 7, 1, 0, 0, 0, 0, pytz.utc)
data = web.DataReader('DEXJPUS', 'fred', start, end)
frslt = open('./hoge.csv', 'w')
frslt.write("Date,Open,High,Low,Close,Volume,Adj Close\n")
for k, v in data["DEXJPUS"].iteritems():
if v != v: # if nan
continue
frslt.write(str(k) + "," + str(v) + "," + \
str(v) + "," + str(v) + \
"," + str(v) + ",1000000,"+ str(v) + "\n")
frslt.close()
instrument = "USDJPY"
feed = yahoofeed.Feed()
feed.addBarsFromCSV(instrument, "./hoge.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 main(plot):
initialCash = 10000
instrumentsByClass = {
# "bitmex_LTCZ18": ["bitmex_LTCZ18"],
"okex_LIGHTBTC": ["okex_LIGHTBTC"],
"binance_ADABTC": ["binance_ADABTC"],
}
# Download the bars.
instruments = []
for assetClass in instrumentsByClass:
instruments.extend(instrumentsByClass[assetClass])
# feed = yahoofinance.build_feed(instruments, 2007, 2013, "data", skipErrors=True)
instrument = "bitmex_LTCZ18"
feed = Feed(Frequency.MINUTE)
# feed.loadBars(instrument, test_back=True)
feed.loadBars('okex_LIGHTBTC', test_back=True)
feed.loadBars("binance_ADABTC", test_back=True)
strat = MarketTiming(feed, instrumentsByClass, initialCash)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
strat.attachAnalyzer(returnsAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, False, False, True)
plt.getOrCreateSubplot("cash").addCallback(
"Cash", lambda x: strat.getBroker().getCash())
# Plot strategy vs. SPY cumulative returns.
# plt.getOrCreateSubplot("returns").addDataSeries("SPY", cumret.CumulativeReturn(feed["SPY"].getPriceDataSeries()))
plt.getOrCreateSubplot("returns").addDataSeries(
"Strategy", returnsAnalyzer.getCumulativeReturns())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
print("Returns: %.2f %%" %
(returnsAnalyzer.getCumulativeReturns()[-1] * 100))
if plot:
plt.plot()
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(plot):
instrument = "aapl"
smaPeriod = 20
feed = yahoofinance.build_feed([instrument], 2014, 2015, ".")
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 run_strategy(smaPeriod):
# Evaluate the strategy with the feed.
# Load the yahoo feed from the CSV file
feed = yahoofeed.Feed()
feed.addBarsFromCSV("zggf", "E:/PythonData/CSV/000938.csv")
myStrategy = MyStrategy(feed, "zggf", smaPeriod)
myStrategy2 = sma_crossover.SMACrossOver(feed, "zggf", smaPeriod)
plt = plotter.StrategyPlotter(myStrategy)
plt.getInstrumentSubplot("zggf").addDataSeries("SMA", myStrategy2.getSMA())
sharpe_ratio = sharpe.SharpeRatio()
trade_situation = trades.Trades()
myStrategy.attachAnalyzer(sharpe_ratio)
myStrategy.attachAnalyzer(trade_situation)
myStrategy.run()
print("Final portfolio value: $%.2f" % myStrategy.getBroker().getEquity())
print("sharpe_ratio", sharpe_ratio.getSharpeRatio(0))
print("total number of trades", trade_situation.getCount())
print("Profit times number of trades ",
trade_situation.getProfitableCount())
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 testSharpeRatioIGE_SPY_Broker(self):
# This testcase is based on an example from Ernie Chan's book:
# 'Quantitative Trading: How to Build Your Own Algorithmic Trading Business'
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
"ige", common.get_data_file_path("sharpe-ratio-test-ige.csv"))
barFeed.addBarsFromCSV(
"spy", common.get_data_file_path("sharpe-ratio-test-spy.csv"))
strat = strategy_test.TestStrategy(barFeed, 1000)
strat.getBroker().setUseAdjustedValues(True)
strat.setBrokerOrdersGTC(True)
stratAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(stratAnalyzer)
# Manually place IGE order to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(broker.Order.Action.BUY,
"ige", 1,
True) # Adj. Close: 42.09
order.setGoodTillCanceled(True)
strat.getBroker().placeOrder(order)
strat.addOrder(datetime.datetime(2007, 11, 13),
strat.getBroker().createMarketOrder,
broker.Order.Action.SELL, "ige", 1,
True) # Adj. Close: 127.64
# Manually place SPY order to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(
broker.Order.Action.SELL_SHORT, "spy", 1,
True) # Adj. Close: 105.52
order.setGoodTillCanceled(True)
strat.getBroker().placeOrder(order)
strat.addOrder(datetime.datetime(2007, 11, 13),
strat.getBroker().createMarketOrder,
broker.Order.Action.BUY_TO_COVER, "spy", 1,
True) # Adj. Close: 147.67
strat.run()
self.assertTrue(
round(strat.getBroker().getCash(), 2) == round(
1000 + (127.64 - 42.09) + (105.52 - 147.67), 2))
self.assertTrue(strat.getOrderUpdatedEvents() == 4)
def kdj(param=[14, 3, 0, 3, 0, 70, 30]):
# dat = ts.get_k_data("000001", start='2006-07-01', end='2017-01-05', index=True)
# dat.to_csv("000001.csv",encoding='gbk',index=False)
dat = pd.read_csv("../../api/stock/csv/000001.csv", encoding='gbk', parse_dates=[0], index_col=0)
dat = dat.fillna(method='pad')
dat['Adj Close'] = dat['close']
dat.index.name = 'date'
dat = dat[['open', 'close', 'high', 'low', 'volume', 'Adj Close']] # the index catch high<open in 2010-02-01
def handle_data(x):
if x[2] < x[0]:
x[2] = x[0]
if x[3] > x[0]:
x[3] = x[0]
return x
dat = dat.apply(handle_data, axis=1)
# print dat.head()
feed = dataFramefeed.Feed()
feed.addBarsFromDataFrame("orcl", dat)
myStrategy = kdj_backtest(feed, 'orcl', param=param,
df=BBcurve2.BBcurve(data=dat,plot=False)) # set the param of STOCH and crossover
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getOrCreateSubplot("returns").addDataSeries("Simple returns", returnsAnalyzer.getReturns())
ds = pyalg_utils.dataSet(myStrategy) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
myStrategy.run()
plt.plot()
# slowk,slowd = talib.STOCH(dat.high.values,dat.low.values,dat.close.values,14,3,0,3,0)
# print slowk[-1],slowd[-1]
print('drawndown：\t%f\t tradingCount：\t%d\t profitCount：\t%d\n' % (
ds.getMaxDrawDown(), ds.getCount(), ds.getProfitableCount()))
print('culmutiveReturn：\t%f\t sharpRatio：\t%f\t' % (
returnsAnalyzer.getCumulativeReturns()[-1], ds.getSharpeRatio()))
def main():
instrument = "aapl"
vwapWindowSize = 5
threshold = 0.01
# Download the bars.
# feed = yahoofinance.build_feed([instrument], 2011, 2012, ".")
feed = yahoofeed.Feed()
feed.addBarsFromCSV(instrument, "dat\\aapl-201x.csv")
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)
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries("vwap", strat.getVWAP())
strat.run()
plt.plot()
# ==============================
print("最终资产价值 Final portfolio value: $%.2f" % strat.getResult())
print("累计回报率 Cumulative returns: %.2f %%" %
(retAnalyzer.getCumulativeReturns()[-1] * 100))
print("夏普比率 Sharpe ratio: %.2f" %
(sharpeRatioAnalyzer.getSharpeRatio(0.05)))
print("最大回撤率 Max. drawdown: %.2f %%" %
(drawDownAnalyzer.getMaxDrawDown() * 100))
print("最长回撤时间 Longest drawdown duration: %s" %
(drawDownAnalyzer.getLongestDrawDownDuration()))
# ===
fss = 'tmp\k408vwap_dret.csv'
xs1 = ret2csv(fss, retAnalyzer)
def main(plot):
instrument = "AMD" #"orcl"
bBandsPeriod = 40
overBoughtThreshold = 70
overSoldThreshold = 30
# Download the bars.
feed = quandlfeed.Feed()
feed.addBarsFromCSV("AMD", "WIKI-AMD-2016-quandl.csv")
strat = BBands(feed, instrument, bBandsPeriod, overBoughtThreshold,
overSoldThreshold)
strat.getBroker().setCash(1000)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
start = strat.getBroker().getEquity()
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())
plt.getOrCreateSubplot("rsi").addDataSeries("RSI", strat.getRSI())
plt.getOrCreateSubplot("rsi").addLine("Overbought",
overBoughtThreshold)
plt.getOrCreateSubplot("rsi").addLine("Oversold", overSoldThreshold)
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
final = strat.getBroker().getEquity()
print("Net: " + str(final - start))
if plot:
plt.plot()
def run_Ma_Macd(code, arg_set, ma_short, ma_long, macd_fast, macd_slow):
result = {}
feed = yahoofeed.Feed()
trade = trades.Trades()
sharpe_ratio = sharpe.SharpeRatio()
draw_down = drawdown.DrawDown()
if arg_set == "fixed":
feed.addBarsFromCSV(code, csv_path + "%s.csv" % code)
else:
feed.addBarsFromCSV(code, csv_path + "%s_hfq.csv" % code)
myStrategy = MyStrategy.Ma_Macd(feed, code, arg_set, ma_short, ma_long,
macd_fast, macd_slow)
myStrategy.attachAnalyzer(sharpe_ratio)
myStrategy.attachAnalyzer(draw_down)
myStrategy.attachAnalyzer(trade)
plt = plotter.StrategyPlotter(myStrategy)
myStrategy.run()
ProfitableCount = trade.getProfitableCount()
TradeCount = trade.getCount()
result['code'] = code
result['final'] = int(myStrategy.getBroker().getEquity())
result['sharpe'] = "%.2f" % sharpe_ratio.getSharpeRatio(0.04)
result['draw_back'] = "%.2f %%" % (draw_down.getMaxDrawDown() * 100)
if TradeCount == 0:
result['trade'] = 0
result['suc_rate'] = 0
else:
result['trade'] = str(ProfitableCount) + "/" + str(TradeCount)
result['suc_rate'] = "%.2f" % (float(ProfitableCount) /
float(TradeCount))
result["arg"] = "%s, %s, %s, %s" % (ma_short, ma_long, macd_fast,
macd_slow)
result["mode"] = "Ma_Macd"
result["date"] = datetime.now().strftime('%Y-%m-%d')
if myStrategy._Ma_Macd__position:
result['L_state'] = "BUY"
else:
result['L_state'] = "SELL"
if plot_flag:
plt.plot()
return result
def ENE(type='old', code='600281SH'):
dat = pd.read_csv("../../api/stock/csv/%s_5min.csv" % code, encoding='gbk')
dat = dat.fillna(method='pad')
dat['Adj Close'] = dat['Close']
dat = dat.rename(
columns={
'Open': 'open',
'High': 'high',
'Volume': 'volume',
'Close': 'close',
'Low': 'low'
})
dat.index = dat['Date Time']
dat.index.name = 'date'
dat['year'] = dat['Date Time'].map(lambda x: x[0:4])
# dat = dat.ix[17000:18000,:]
feed = dataFramefeed.Feed(frequency=bar.Frequency.MINUTE)
feed.addBarsFromDataFrame("orcl", dat[dat['year'] > '2015'])
if type == 'macd':
myStrategy = mdd.ENE_backtest(feed, 'orcl')
elif type == 'old':
myStrategy = mdd.ENE_backtest(feed, 'orcl')
sharpeRatioAnalyzer = sharpe.SharpeRatio()
myStrategy.attachAnalyzer(sharpeRatioAnalyzer)
returnsAnalyzer = returns.Returns()
myStrategy.attachAnalyzer(returnsAnalyzer)
plt = plotter.StrategyPlotter(myStrategy, True, True, True)
plt.getOrCreateSubplot("returns").addDataSeries(
"Simple returns", returnsAnalyzer.getReturns())
ds = pyalg_utils.dataSet(myStrategy) # 抽取交易数据集语句，若使用系统自带画图功能则不需要该项
myStrategy.run()
plt.plot()
print(u'最大回撤：\t%f\t 交易笔数：\t%d\t 盈利笔数：\t%d\n' %
(ds.getMaxDrawDown(), ds.getCount(), ds.getProfitableCount()))
print(u'累计收益：\t%f\t 夏普比率：\t%f\t' %
(returnsAnalyzer.getCumulativeReturns()[-1], ds.getSharpeRatio()))
def main(plot):
symbol = "DIA"
priceCurrency = "USD"
instrument = "%s/%s" % (symbol, priceCurrency)
entrySMA = 200
exitSMA = 5
rsiPeriod = 2
overBoughtThreshold = 90
overSoldThreshold = 10
initialBalance = {priceCurrency: 1000000}
# Load the bars. These files were manually downloaded from Yahoo Finance.
feed = yahoofeed.Feed()
for year in range(2009, 2013):
fileName = "%s-%d-yahoofinance.csv" % (symbol, year)
print("Loading bars from %s" % fileName)
feed.addBarsFromCSV(instrument, fileName)
strat = rsi2.RSI2(feed, instrument, initialBalance, entrySMA, exitSMA,
rsiPeriod, overBoughtThreshold, overSoldThreshold)
sharpeRatioAnalyzer = sharpe.SharpeRatio(priceCurrency)
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
from pyalgotrade import plotter
plt = plotter.StrategyPlotter(strat, True, False, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"Entry SMA", strat.getEntrySMA())
plt.getInstrumentSubplot(instrument).addDataSeries(
"Exit SMA", strat.getExitSMA())
plt.getOrCreateSubplot("rsi").addDataSeries("RSI", strat.getRSI())
plt.getOrCreateSubplot("rsi").addLine("Overbought",
overBoughtThreshold)
plt.getOrCreateSubplot("rsi").addLine("Oversold", overSoldThreshold)
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def __init__(self, myStrategy):
self.myStrategy = myStrategy
self.tradesAnalyzer = trades.Trades()
self.myStrategy.attachAnalyzer(self.tradesAnalyzer)
self.sharpeAnalyzer = sharpe.SharpeRatio()
self.retAnalyzer = Returns()
self.myStrategy.attachAnalyzer(self.retAnalyzer)
self.myStrategy.attachAnalyzer(self.sharpeAnalyzer)
self.myStrategy.run()
self.myStrategy.getResult()
self.retAnalyzer.getCumulativeReturns()
self.result = self.sharpeAnalyzer.getSharpeRatio(0.025)
tr = self.tradesAnalyzer.getAllReturns()
self.streak = 0
temp_streak = 0
for i in tr:
if i > 0:
temp_streak = temp_streak + 1
else:
self.streak = temp_streak if temp_streak > self.streak else self.streak
def main(plot):
# merge_csv("./hoge.csv", ["./USDJPY_M5_2001.txt","./USDJPY_M5_2002.txt","./USDJPY_M5_2003.txt","./USDJPY_M5_2004.txt",\
# "./USDJPY_M5_2005.txt","./USDJPY_M5_2006.txt","./USDJPY_M5_2007.txt","./USDJPY_M5_2008.txt"])
instrument = "USDJPY"
feed = csvfeed.GenericBarFeed(Frequency.MINUTE, pytz.utc)
feed.addBarsFromCSV(instrument, "./hoge.csv")
strat = MATrade(feed, instrument)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, True, True, True)
plt.getInstrumentSubplot(instrument).addDataSeries(
"MA20", strat.getSMA())
strat.run()
print "Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05)
if plot:
plt.plot()
def main(plot):
instruments = ["gld", "gdx"]
windowSize = 50
# Download the bars.
feed = yahoofinance.build_feed(instruments, 2006, 2012, ".")
strat = StatArb(feed, instruments[0], instruments[1], windowSize)
sharpeRatioAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(sharpeRatioAnalyzer)
if plot:
plt = plotter.StrategyPlotter(strat, False, False, True)
plt.getOrCreateSubplot("hedge").addDataSeries("Hedge Ratio", strat.getHedgeRatioDS())
plt.getOrCreateSubplot("spread").addDataSeries("Spread", strat.getSpreadDS())
strat.run()
print("Sharpe ratio: %.2f" % sharpeRatioAnalyzer.getSharpeRatio(0.05))
if plot:
plt.plot()
def __testIGE_BrokerImpl(self, quantity):
# This testcase is based on an example from Ernie Chan's book:
# 'Quantitative Trading: How to Build Your Own Algorithmic Trading Business'
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV("ige", common.get_data_file_path("sharpe-ratio-test-ige.csv"))
strat = strategy_test.TestStrategy(barFeed, 1000)
strat.getBroker().setUseAdjustedValues(True)
strat.setBrokerOrdersGTC(True)
stratAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(stratAnalyzer)
# Manually place the order to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(broker.Order.Action.BUY, "ige", quantity, True) # Adj. Close: 42.09
order.setGoodTillCanceled(True)
strat.getBroker().placeOrder(order)
strat.addOrder(strategy_test.datetime_from_date(2007, 11, 13), strat.getBroker().createMarketOrder, broker.Order.Action.SELL, "ige", quantity, True) # Adj. Close: 127.64
strat.run()
self.assertTrue(round(strat.getBroker().getCash(), 2) == 1000 + (127.64 - 42.09) * quantity)
self.assertTrue(strat.getOrderUpdatedEvents() == 2)
# The results are slightly different different only because I'm taking into account the first bar as well.
self.assertTrue(round(stratAnalyzer.getSharpeRatio(0.04, 252, annualized=True), 4) == 0.7889)
def run_strategy(smaPeriod):
# Load the yahoo feed from the CSV file
# feed = yahoofeed.Feed()
feed = GenericBarFeed(Frequency.DAY, None, None)
feed.addBarsFromCSV("zggf", "E:\Stock\Data_Day/000831.SZ.csv")
global myStrategy
# Evaluate the strategy with the feed.
myStrategy = MyStrategy(feed, "zggf", smaPeriod)
plt = plotter.StrategyPlotter(myStrategy)
sharpe_ratio = sharpe.SharpeRatio()
trade_situation = trades.Trades()
myStrategy.attachAnalyzer(sharpe_ratio)
myStrategy.attachAnalyzer(trade_situation)
myStrategy.run()
print("Final portfolio value: $%.2f" % myStrategy.getBroker().getEquity())
print("sharpe_ratio", sharpe_ratio.getSharpeRatio(0))
print("total number of trades", trade_situation.getCount())
print("Profit times number of trades ",
trade_situation.getProfitableCount())
print(myStrategy.Sma_price)
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 main(plot):
from pyalgotrade import bar
from pyalgotrade import plotter
instrument = "002665"
bBandsPeriod = 40
strat = BBands
frequency = bar.Frequency.DAY
plot = True
# Download the bars.
from pyalgotrade.barfeed.csvfeed import GenericBarFeed
barfeed = GenericBarFeed(frequency)
barfeed.setDateTimeFormat('%Y-%m-%d %H:%M:%S')
barfeed.addBarsFromCSV("002665", "F:/shuju/002665-barfeed.csv")
strat = strat(barfeed, instrument, bBandsPeriod)
strat = BBands(barfeed, 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 = yahoofinance.build_feed([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 = "yhoo"
bBandsPeriod = 40
# Download the bars.
feed = yahoofinance.build_feed([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 testIGE_BrokerWithCommission(self):
commision = 0.5
initialCash = 42.09 + commision
# This testcase is based on an example from Ernie Chan's book:
# 'Quantitative Trading: How to Build Your Own Algorithmic Trading Business'
barFeed = yahoofeed.Feed()
barFeed.addBarsFromCSV(
"ige", common.get_data_file_path("sharpe-ratio-test-ige.csv"))
strat = strategy_test.TestStrategy(barFeed, initialCash)
strat.getBroker().setCommission(backtesting.FixedPerTrade(commision))
strat.setUseAdjustedValues(True)
strat.setBrokerOrdersGTC(True)
stratAnalyzer = sharpe.SharpeRatio()
strat.attachAnalyzer(stratAnalyzer)
# Disable volume checks to match book results.
strat.getBroker().getFillStrategy().setVolumeLimit(None)
# Manually place the order to get it filled on the first bar.
order = strat.getBroker().createMarketOrder(broker.Order.Action.BUY,
"ige", 1,
True) # Adj. Close: 42.09
order.setGoodTillCanceled(True)
strat.getBroker().submitOrder(order)
strat.addOrder(datetime.datetime(2007, 11, 13),
strat.getBroker().createMarketOrder,
broker.Order.Action.SELL, "ige", 1,
True) # Adj. Close: 127.64
strat.run()
self.assertTrue(
round(strat.getBroker().getCash(), 2) == initialCash +
(127.64 - 42.09 - commision * 2))
self.assertEqual(strat.orderUpdatedCalls, 6)
# The results are slightly different only because I'm taking into account the first bar as well,
# and I'm also adding commissions.
self.assertEqual(round(stratAnalyzer.getSharpeRatio(0.04, True), 6),
0.776443)
