timeData.set_TD_from_google("AAPL", 5, "3d")
#####################################################################3
timeData.set_interval(sdate, edate)
opentime, closetime = timeData.guess_openMarketTime()
period = timeData.guess_period()
print "Period: %f" % period
print "Market Hours " + str(opentime) + " - " + str(closetime)
dataTransform = ["intraday", opentime, closetime]
#dataTransform = None
dataHLOC = timeData.get_timeSeries(["High", "Low", "Open", "Close"])
dates = timeData.get_dates()
gl.barchart(dates,
dataHLOC,
lw=2,
dataTransform=dataTransform,
color="k",
AxesStyle="Normal")
## Define IDs
event_type = "NewAvailableData"
eventID = "AAPL_M5"
handlerID = "handler1"
### Define the event
dataEvent = dict()
dataEvent["symbolID"] = "AAPL"
dataEvent["period"] = 5
dataEvent["src"] = "Google"
myEvent = eSL.CEvent(event_type=event_type, data=dataEvent, eventID=eventID)
colorBB1 = "cobalt blue"
colorBB2 = "irish green"
## Plotting t the BB !!
ax1 = gl.subplot2grid((5, 1), (0, 0), rowspan=4, colspan=1)
# gl.plot(dates, price, ax = ax1, AxesStyle = "Normal - No xaxis",
# labels = ["Volatility indicator BB", "", "Price"],
# legend = ["Price"], color = "dark navy blue")
title = "Bollinger Bands. " + str(
symbols[0]) + "(" + ul5.period_dic[timeData.period] + ")"
##### The problem is that we are using dataTrasnform so the X axis is not being transformed into integers
##### but fed directly, we need to still make such a transformation for this to work?
gl.barchart(dates,
dataHLOC,
ax=ax1,
color=color1,
labels=[title, "", r"Price ($\$$)"],
legend=["HLOC Price"])
BBs = np.concatenate([BB1[:, [0]], BB1[:, [1]]], axis=1)
gl.plot(dates, SMA1, color=colorBB1, legend=["0.95 BB(%i)" % nBB1])
gl.plot(dates, BBs, color=colorBB1, ls="--")
gl.plot_filled(
dates,
BBs,
color=colorBB1,
alpha=0.1,
AxesStyle="Normal - No xaxis",
)
gl.plot(dates, BBs, color=colorBB1, ls="--")
period=period1,
maxPullback=maxPullback)
exitcrosses2, all_stops2, pCheckCross2, datesExit2 = mySalida2.get_TradeSignals(
)
########## Plotting ! ####################
gl.set_subplots(3, 1)
## Price Axes
ax1 = gl.plot(dates,
price,
legend=["Price"],
labels=["Crossing MA Strategy", "", "Price"],
alpha=0,
nf=1)
gl.barchart(dates, dataHLOC)
gl.plot(dates, EMAslow, legend=["Slow"], lw=1, color="b")
gl.plot(dates, EMAfast, legend=["fast"], lw=1, color="r", xaxis_mode="hidden")
## Entry Axes
ax2 = gl.plot(dates,
ul.scale(EMAfast - EMAslow),
legend=["Difference"],
nf=1,
sharex=ax1,
labels=["", "", "Events"],
fill=1,
alpha=0.3)
gl.stem(dates, crosses, legend=["TradeSignal"])
gl.scatter(dates, ul.scale(EMAfast - EMAslow), lw=0.5, alpha=0.5)
precision="m",
start_date=dt.datetime(2016, 1, 1),
end_date=dt.datetime(2017, 1, 1))
TD_google = gdl.download_TD_google("AAPL",
period_seconds=60 * 1440 * 7,
timeInterval="15d")
TD_google = gdl.download_D1_TD_google("AAPL", sdate, edate)
timeData.set_TD(TD_google)
timeData.set_TD_from_google("ONT", 5, "10d")
#####################################################################3
timeData.set_interval(sdate, edate)
opentime, closetime = timeData.guess_openMarketTime()
period = timeData.guess_period()
print "Period: %f" % period
print "Market Hours " + str(opentime) + " - " + str(closetime)
dataTransform = ["intraday", opentime, closetime]
#dataTransform = None
dataHLOC = timeData.get_timeSeries(["High", "Low", "Open", "Close"])
dates = timeData.get_dates()
gl.barchart(dates,
dataHLOC,
lw=2,
dataTransform=dataTransform,
color="k",
labels=[symbols[0], "", "Price"],
legend=[symbols[0]],
AxesStyle="Normal")
gl.set_subplots(4,1)
############# 1: Basic Time Series and Volume
seriesNames = ["Average", "High"]
dataHLOC = timeData.get_timeSeries(["High","Low","Open","Close"])
prices = timeData.get_timeSeries(seriesNames);
dates = timeData.get_dates()
volume = timeData.get_timeSeries(["Volume"]);
Returns = timeData.get_timeSeriesReturn(seriesNames = ["Close"]);
CumReturns = timeData.get_timeSeriesCumReturn(seriesNames = ["Close"]);
nSMA = 10
SMA = timeData.SMA(n = nSMA)
ax1 = gl.plot(dates, SMA, labels = [timeData.symbolID + str(timeData.period), "Time", "Price"],
legend = ["SMA(%i)" % nSMA], nf = 1, dataTransform = dataTransform,
AxesStyle = "Normal - No xaxis", color = "cobalt blue")
gl.barchart(dates, dataHLOC, lw = 2, dataTransform = dataTransform, color = "k",
AxesStyle = "Normal - No xaxis")
# Notice the Weekends and the displacement between bars and step
############# 2: Volume
gl.stem(dates, volume, sharex = ax1, labels = [timeData.symbolID + str(timeData.period), "Time", "Volume"],
legend = ["Volume"], nf = 1, alpha = 0.5, dataTransform = dataTransform,
AxesStyle = "Normal - No xaxis")
############# 3: Returns
gl.stem(dates, Returns, sharex = ax1, labels = [timeData.symbolID + str(timeData.period), "Time", "Return"],
legend = ["Return"], nf = 1, dataTransform = dataTransform,
AxesStyle = "Normal - No xaxis")
############# 4: Commulative Returns
seriesNames = ["Close"]
BB2 = timeData.BBANDS(seriesNames = ["Close"], n = nBB2)
SMA2 = timeData.SMA(n = nBB2)
EMA1 = timeData.EMA(n = nBB1)
BBE1 = timeData.BBANDS(seriesNames = ["Close"], MA = SMA1, n = nBB1)
color1 = "k"
colorBB1 = "cobalt blue"
colorBB2 = "irish green"
## Plotting t the BB !!
ax1 = gl.subplot2grid((5,1), (0,0), rowspan=4, colspan=1)
# gl.plot(dates, price, ax = ax1, AxesStyle = "Normal - No xaxis",
# labels = ["Volatility indicator BB", "", "Price"],
# legend = ["Price"], color = "dark navy blue")
title = "Bollinger Bands. " + str(symbols[0]) + "(" + ul.period_dic[timeData.period]+ ")"
gl.barchart(dates, dataHLOC, ax = ax1, color = color1,
labels = [title, "", r"Price ($\$$)"],
legend = ["HLOC Price"])
BBs = np.concatenate([BB1[:,[0]],BB1[:,[1]]],axis = 1)
gl.plot(dates, SMA1, color = colorBB1,
legend = ["0.95 BB(%i)"%nBB1])
gl.plot(dates, BBs,
color = colorBB1, ls = "--")
gl.plot_filled(dates, BBs,
color = colorBB1, alpha = 0.1, AxesStyle = "Normal - No xaxis",)
gl.plot(dates, BBs,
color = colorBB1, ls = "--")
gl.plot_filled(dates, BBs,
color = colorBB1, alpha = 0.1, AxesStyle = "Normal - No xaxis",)
period = period1, maxPullback = maxPullback)
exitcrosses, all_stops, pCheckCross, datesExit = mySalida.get_TradeSignals()
# Second Signal
mySalida2 = CTS.CTrailingStop("salircaca",period1,Cartera)
secondEntrySingal = EntrySignals[1]
mySalida2.set_trailingStop(SymbolName = symbol,BUYSELL = secondEntrySingal.BUYSELL, datetime = secondEntrySingal.datetime,
period = period1, maxPullback = maxPullback)
exitcrosses2, all_stops2, pCheckCross2, datesExit2 = mySalida2.get_TradeSignals()
########## Plotting ! ####################
gl.set_subplots(3,1)
## Price Axes
ax1 = gl.plot(dates,price, legend = ["Price"],
labels = ["Crossing MA Strategy", "","Price"], alpha = 0, nf = 1)
gl.barchart(dates, dataHLOC)
gl.plot(dates,EMAslow, legend = ["Slow"], lw = 1, color = "b")
gl.plot(dates,EMAfast, legend = ["fast"], lw = 1, color = "r", xaxis_mode = "hidden")
## Entry Axes
ax2 = gl.plot(dates, ul.scale(EMAfast - EMAslow), legend = ["Difference"]
,nf = 1, sharex = ax1, labels = ["","","Events"], fill = 1, alpha = 0.3)
gl.stem(dates,crosses, legend = ["TradeSignal"] )
gl.scatter(dates, ul.scale(EMAfast - EMAslow), lw = 0.5, alpha = 0.5)
gl.plot(dates,np.zeros(crosses.shape))
## Exit Axes
gl.add_hlines(datesExit, all_stops, ax = ax1, legend = ["TrailingStop"], alpha = 0.8, lw = 0.2)
ax3 = gl.plot(datesExit, ul.scale(-(all_stops - pCheckCross)), legend = ["TrailingStop"]
,nf = 1, sharex = ax1, labels = ["","","TrailingStop"], lw = 0.5, alpha = 0.5, fill = 1)
############# 1: Basic Time Series and Volume
seriesNames = ["Average", "High"]
dataHLOC = timeData.get_timeSeries(["High","Low","Open","Close"])
prices = timeData.get_timeSeries(seriesNames);
dates = timeData.get_dates()
volume = timeData.get_timeSeries(["Volume"]);
Returns = timeData.get_timeSeriesReturn(seriesNames = ["Close"]);
CumReturns = timeData.get_timeSeriesCumReturn(seriesNames = ["Close"]);
nSMA = 10
SMA = timeData.SMA(n = nSMA)
ax1 = gl.plot(dates, SMA, labels = [timeData.symbolID + str(timeData.period), "Time", "Price"],
legend = ["SMA(%i)" % nSMA], nf = 1, dataTransform = dataTransform,
AxesStyle = "Normal - No xaxis", color = "cobalt blue")
gl.barchart(dates, dataHLOC, lw = 2, dataTransform = dataTransform, color = "k",
AxesStyle = "Normal - No xaxis", legend = ["OHCL"])
# Notice the Weekends and the displacement between bars and step
############# 2: Volume
gl.stem(dates, volume, sharex = ax1, labels = ["", "Time", "Volume"],
legend = ["Volume"], nf = 1, alpha = 0.8, dataTransform = dataTransform,
AxesStyle = "Normal - No xaxis")
############# 3: Returns
gl.stem(dates, Returns, sharex = ax1, labels = ["", "Time", "Return"],
legend = ["Return"], nf = 1, dataTransform = dataTransform,
AxesStyle = "Normal - No xaxis")
############# 4: Commulative Returns
seriesNames = ["Close"]