def Bchange(args):
"""
#Use: Bchange(args)
#Pre: args is a list of strings, args[1] is a optional string that represents a ticker.
#Post:The stockObject has been changed, to args[1] if provided and correct.
"""
global stockObj
if len(args) == 1:
print "Please enter the ticker of the company/index you wish to check."
while True:
ticker = raw_input("Ticker: ")
try:
stockObj = stockInfo(ticker)
print stockObj
break
except ValueError:
print "Ticker '%s' not found. Please enter valid ticker" % (
ticker)
else:
try:
stockObj = stockInfo(args[1])
print stockObj
except ValueError:
print "Ticker '%s' not found. Please enter valid ticker" % (
args[1])
def on_new(self, event):
"""Handles creating new tickers"""
prompt = wx.TextEntryDialog(self, "Enter new ticker", "New ticker",self.panel.stockObj.ticker)
prompt.ShowModal()
#Use this loop and recursion to ensure we get a legal value
try:
self.flash_status_message("Fetching data...")
self.panel.stockObj = stockInfo(prompt.GetValue())
self.flash_status_message("Fetching data...Done")
if not (self.panel.stockObj.validDate(self.panel.fromDate) and self.panel.stockObj.validDate(self.panel.toDate)):
td = self.panel.stockObj.toDate - timedelta(weeks=DEFAULT_PERIOD)
if self.panel.stockObj.validDate(td):
self.panel.fromDate = td
else:
self.panel.fromDate = self.panel.stockObj.fromDate
self.panel.toDate = self.panel.stockObj.toDate
self.panel.Beta = Beta(self.panel.stockObj,self.panel.fromDate, self.panel.toDate)
self.updateCurrentData()
self.updateRSS()
self.draw_figure()
except ValueError:
msg = wx.MessageDialog(self, "Invalid Ticker", "Error", wx.OK|wx.ICON_ERROR)
msg.ShowModal()
self.on_new(None)
def on_new(self, event):
"""Handles creating new tickers"""
prompt = wx.TextEntryDialog(self, "Enter new ticker", "New ticker",
self.panel.stockObj.ticker)
prompt.ShowModal()
#Use this loop and recursion to ensure we get a legal value
try:
self.flash_status_message("Fetching data...")
self.panel.stockObj = stockInfo(prompt.GetValue())
self.flash_status_message("Fetching data...Done")
if not (self.panel.stockObj.validDate(self.panel.fromDate)
and self.panel.stockObj.validDate(self.panel.toDate)):
td = self.panel.stockObj.toDate - timedelta(
weeks=DEFAULT_PERIOD)
if self.panel.stockObj.validDate(td):
self.panel.fromDate = td
else:
self.panel.fromDate = self.panel.stockObj.fromDate
self.panel.toDate = self.panel.stockObj.toDate
self.panel.Beta = Beta(self.panel.stockObj, self.panel.fromDate,
self.panel.toDate)
self.updateCurrentData()
self.updateRSS()
self.draw_figure()
except ValueError:
msg = wx.MessageDialog(self, "Invalid Ticker", "Error",
wx.OK | wx.ICON_ERROR)
msg.ShowModal()
self.on_new(None)
def updateStockInfo(stockList):
filePath = sorted(os.listdir(constants.stockListPath), reverse=True)
startTime = ''
currentTime = filePath[0].replace('stockList_', '').replace('.csv', '')
if len(filePath) > 1:
startTime = filePath[1].replace('stockList_', '').replace('.csv', '')
s = stockInfo()
s.method(stockList, startTime, currentTime)
def infoPage(ticker):
ticker = ticker # place holder so AttributeError: NoneType isn't thrown on page load
# functions to be passed as variables in jinja2 template
info = stockInfo(ticker)
news = stockNews(ticker)
bio = stockBio(ticker)
fin = stockFinancials(ticker)
return render_template('stockInfo.html',
ticker=ticker,
news=news,
bio=bio,
info=info,
fin=fin)
def Bchange(args):
"""
#Use: Bchange(args)
#Pre: args is a list of strings, args[1] is a optional string that represents a ticker.
#Post:The stockObject has been changed, to args[1] if provided and correct.
"""
global stockObj
if len(args) == 1:
print "Please enter the ticker of the company/index you wish to check."
while True:
ticker = raw_input("Ticker: ")
try:
stockObj = stockInfo(ticker)
print stockObj
break
except ValueError:
print "Ticker '%s' not found. Please enter valid ticker" % (ticker)
else:
try:
stockObj = stockInfo(args[1])
print stockObj
except ValueError:
print "Ticker '%s' not found. Please enter valid ticker" % (args[1])
def Beta(s, fromDate=None, toDate=None):
"""
# U: b=Beta(s,fd,td)
# Pre: s is stockInfo object, fd, td are optional date objects
# Post: b is a number describing our stock's Beta value for the time period from fromDate to toDate if data exists for those dates,
# otherwise raises exception
"""
if fromDate == None:
fromDate = s.fromDate
if toDate == None:
toDate = s.toDate
if not (s.validDate(fromDate) and s.validDate(toDate)):
raise ValueError("Invalid dates")
price = lambda d: d[6]
def log_returns(l):
"""
# U: l_r=log_returns(l)
# Pre: l is a list of numbers, the length of which is n
# Post: l_r is a list the length of which is one shorter than the length of l, where
# l_r[k]=log(l[k]/l[k-1]) for k=1,...,n-1
"""
l_r = []
for i in range(1, len(l)):
r = math.log(l[i] / l[i - 1])
l_r.append(r)
return l_r
datelist = s.listFromTo(fromDate, toDate)
pricelist = map(price, datelist)
SP = stockInfo("^GSPC", fromDate, toDate)
SPlist = SP.listFromTo(fromDate, toDate)
SPprices = map(price, SPlist)
r_a = log_returns(pricelist)
r_b = log_returns(SPprices)
cov_ab = cov(array(r_a), array(r_b))[0][
1] # We extract the covariance between r_a and r_b from the covariance matrix
return round(cov_ab, 6) / round(
var(array(r_b)),
6) #: some error in cov or var, we must round to get correct value
def Beta(s, fromDate=None, toDate=None):
"""
# U: b=Beta(s,fd,td)
# Pre: s is stockInfo object, fd, td are optional date objects
# Post: b is a number describing our stock's Beta value for the time period from fromDate to toDate if data exists for those dates,
# otherwise raises exception
"""
if fromDate==None:
fromDate=s.fromDate
if toDate==None:
toDate=s.toDate
if not (s.validDate(fromDate) and s.validDate(toDate)):
raise ValueError("Invalid dates")
price = lambda d: d[6]
def log_returns(l):
"""
# U: l_r=log_returns(l)
# Pre: l is a list of numbers, the length of which is n
# Post: l_r is a list the length of which is one shorter than the length of l, where
# l_r[k]=log(l[k]/l[k-1]) for k=1,...,n-1
"""
l_r=[]
for i in range(1,len(l)):
r=math.log(l[i]/l[i-1])
l_r.append(r)
return l_r
datelist=s.listFromTo(fromDate,toDate)
pricelist=map(price, datelist)
SP=stockInfo("^GSPC",fromDate,toDate)
SPlist=SP.listFromTo(fromDate,toDate)
SPprices=map(price,SPlist)
r_a=log_returns(pricelist)
r_b=log_returns(SPprices)
cov_ab=cov(array(r_a),array(r_b))[0][1] # We extract the covariance between r_a and r_b from the covariance matrix
return round(cov_ab,6)/round(var(array(r_b)),6) #: some error in cov or var, we must round to get correct value
def setUp(self):
self.testobj = stockInfo("MSFT")
# Pre: l is a list of numbers, the length of which is n
# Post: l_r is a list the length of which is one shorter than the length of l, where
# l_r[k]=log(l[k]/l[k-1]) for k=1,...,n-1
"""
l_r = []
for i in range(1, len(l)):
r = math.log(l[i] / l[i - 1])
l_r.append(r)
return l_r
datelist = s.listFromTo(fromDate, toDate)
pricelist = map(price, datelist)
SP = stockInfo("^GSPC", fromDate, toDate)
SPlist = SP.listFromTo(fromDate, toDate)
SPprices = map(price, SPlist)
r_a = log_returns(pricelist)
r_b = log_returns(SPprices)
cov_ab = cov(array(r_a), array(r_b))[0][
1] # We extract the covariance between r_a and r_b from the covariance matrix
return round(cov_ab, 6) / round(
var(array(r_b)),
6) #: some error in cov or var, we must round to get correct value
if __name__ == "__main__":
SP = stockInfo("^GSPC")
print Beta(SP)
#Google = stockInfo("GOOG",date(2000,1,1),date.today())
#virkar ekki, getum ekki importad i hring.
#smaPlot(Google,fromDate = date(2010,1,2), toDate = date(2011,1,2)).show()
price = lambda d: d[6]
def log_returns(l):
"""
# U: l_r=log_returns(l)
# Pre: l is a list of numbers, the length of which is n
# Post: l_r is a list the length of which is one shorter than the length of l, where
# l_r[k]=log(l[k]/l[k-1]) for k=1,...,n-1
"""
l_r=[]
for i in range(1,len(l)):
r=math.log(l[i]/l[i-1])
l_r.append(r)
return l_r
datelist=s.listFromTo(fromDate,toDate)
pricelist=map(price, datelist)
SP=stockInfo("^GSPC",fromDate,toDate)
SPlist=SP.listFromTo(fromDate,toDate)
SPprices=map(price,SPlist)
r_a=log_returns(pricelist)
r_b=log_returns(SPprices)
cov_ab=cov(array(r_a),array(r_b))[0][1] # We extract the covariance between r_a and r_b from the covariance matrix
return round(cov_ab,6)/round(var(array(r_b)),6) #: some error in cov or var, we must round to get correct value
if __name__ == "__main__":
SP = stockInfo("^GSPC")
print Beta(SP)
#Google = stockInfo("GOOG",date(2000,1,1),date.today())
#virkar ekki, getum ekki importad i hring.
#smaPlot(Google,fromDate = date(2010,1,2), toDate = date(2011,1,2)).show()
ticker)
else:
try:
stockObj = stockInfo(args[1])
print stockObj
except ValueError:
print "Ticker '%s' not found. Please enter valid ticker" % (
args[1])
print "Welcome to Bangsimon Stocks!"
print "Please enter the ticker of the company/index you wish to check."
while True:
ticker = raw_input("Ticker: ")
try:
stockObj = stockInfo(ticker)
break
except ValueError:
print "%s ticker not found. Please enter valid ticker" % (ticker)
c = 'help'
print stockObj
commands = {
'plot': Bplot,
'help': Bhelp,
'quit': Bquit,
'change': Bchange,
'current': Bcurrent,
'beta': Bbeta,
'ma': Bma,
'news': Bnews
def create_main_panel(self):
""" Creates the main panel and everything"""
self.panel = wx.Panel(self)
self.panel.stockObj = stockInfo(DEFAULT_TICKER)
#Put up some default values that are used in plot
self.panel.currentAttr = "Adj Close"
td = self.panel.stockObj.toDate - timedelta(weeks=DEFAULT_PERIOD)
if self.panel.stockObj.validDate(td):
self.panel.fromDate = td
else:
self.panel.fromDate = self.panel.stockObj.fromDate
self.panel.toDate = self.panel.stockObj.toDate
self.panel.MovingAvg = False
self.panel.Volume = False
self.panel.MovingAvgN = 20
self.panel.Beta = Beta(self.panel.stockObj,self.panel.fromDate, self.panel.toDate)
#adding the pllot
self.fig = matplotlib.pyplot.gcf()
self.canvas = FigCanvas(self.panel, -1, self.fig)
#Add slider to change n of moving average
self.slider_label = wx.StaticText(self.panel, -1,
"Moving Average N: ")
self.slider_width = wx.Slider(self.panel, -1,
value=20,
minValue=20,
maxValue=200,
style=wx.SL_AUTOTICKS | wx.SL_LABELS)
self.slider_width.SetTickFreq(10, 1)
self.Bind(wx.EVT_COMMAND_SCROLL_THUMBTRACK, self.on_slider_width, self.slider_width)
self.Bind(wx.EVT_COMMAND_SCROLL_CHANGED, self.on_slider_width, self.slider_width)
#Toolbar of chart
self.toolbar = NavigationToolbar(self.canvas)
self.SetToolBar(self.toolbar)
self.toolbar.Realize()#: Windows fix, does not work
#We use boxes to get a dynamic layout
self.vbox = wx.BoxSizer(wx.VERTICAL)
self.vbox.Add(self.canvas, 0, wx.LEFT | wx.TOP | wx.EXPAND)
self.hbox = wx.BoxSizer(wx.HORIZONTAL)
flags = wx.ALIGN_LEFT | wx.ALL | wx.ALIGN_CENTER_VERTICAL
self.hbox.AddSpacer(30)
self.hbox.Add(self.slider_label, 0, flag=flags)
self.hbox.Add(self.slider_width, 1, border=3, flag=flags |wx.EXPAND)
self.vbox.Add(self.hbox, 0, flag = wx.ALIGN_LEFT | wx.TOP| wx.EXPAND)
self.vbox.AddSpacer(10)
#Add NewsFeed
self.RssBox = wx.BoxSizer(wx.VERTICAL)
self.RssPanel = wx.lib.scrolledpanel.ScrolledPanel(self.panel)
self.RssPanel.SetMinSize((-1,100))
self.RssPanel.SetSizer(self.RssBox)
self.updateRSS()
self.RssBox.Fit(self.RssPanel)
self.RssPanel.SetupScrolling()
self.vbox.Add(self.RssPanel,1, flag= wx.EXPAND | wx.ALIGN_CENTER)
self.panel.SetSizer(self.vbox)
self.vbox.Fit(self)
self.updateCurrentData()
print "Ticker '%s' not found. Please enter valid ticker" % (ticker)
else:
try:
stockObj = stockInfo(args[1])
print stockObj
except ValueError:
print "Ticker '%s' not found. Please enter valid ticker" % (args[1])
print "Welcome to Bangsimon Stocks!"
print "Please enter the ticker of the company/index you wish to check."
while True:
ticker = raw_input("Ticker: ")
try:
stockObj = stockInfo(ticker)
break
except ValueError:
print "%s ticker not found. Please enter valid ticker" % (ticker)
c = 'help'
print stockObj
commands = {'plot': Bplot, 'help':Bhelp, 'quit':Bquit, 'change': Bchange, 'current':Bcurrent, 'beta':Bbeta, 'ma':Bma, 'news':Bnews} #: Dictionary of functions
Bhelp(['help'])
while c != "quit":
c = raw_input(">> ")
args = c.split()
if len(args) >= 1:
if args[0] not in commands:
print "invalid command"
continue
def create_main_panel(self):
""" Creates the main panel and everything"""
self.panel = wx.Panel(self)
self.panel.stockObj = stockInfo(DEFAULT_TICKER)
#Put up some default values that are used in plot
self.panel.currentAttr = "Adj Close"
td = self.panel.stockObj.toDate - timedelta(weeks=DEFAULT_PERIOD)
if self.panel.stockObj.validDate(td):
self.panel.fromDate = td
else:
self.panel.fromDate = self.panel.stockObj.fromDate
self.panel.toDate = self.panel.stockObj.toDate
self.panel.MovingAvg = False
self.panel.Volume = False
self.panel.MovingAvgN = 20
self.panel.Beta = Beta(self.panel.stockObj, self.panel.fromDate,
self.panel.toDate)
#adding the pllot
self.fig = matplotlib.pyplot.gcf()
self.canvas = FigCanvas(self.panel, -1, self.fig)
#Add slider to change n of moving average
self.slider_label = wx.StaticText(self.panel, -1, "Moving Average N: ")
self.slider_width = wx.Slider(self.panel,
-1,
value=20,
minValue=20,
maxValue=200,
style=wx.SL_AUTOTICKS | wx.SL_LABELS)
self.slider_width.SetTickFreq(10, 1)
self.Bind(wx.EVT_COMMAND_SCROLL_THUMBTRACK, self.on_slider_width,
self.slider_width)
self.Bind(wx.EVT_COMMAND_SCROLL_CHANGED, self.on_slider_width,
self.slider_width)
#Toolbar of chart
self.toolbar = NavigationToolbar(self.canvas)
self.SetToolBar(self.toolbar)
self.toolbar.Realize() #: Windows fix, does not work
#We use boxes to get a dynamic layout
self.vbox = wx.BoxSizer(wx.VERTICAL)
self.vbox.Add(self.canvas, 0, wx.LEFT | wx.TOP | wx.EXPAND)
self.hbox = wx.BoxSizer(wx.HORIZONTAL)
flags = wx.ALIGN_LEFT | wx.ALL | wx.ALIGN_CENTER_VERTICAL
self.hbox.AddSpacer(30)
self.hbox.Add(self.slider_label, 0, flag=flags)
self.hbox.Add(self.slider_width, 1, border=3, flag=flags | wx.EXPAND)
self.vbox.Add(self.hbox, 0, flag=wx.ALIGN_LEFT | wx.TOP | wx.EXPAND)
self.vbox.AddSpacer(10)
#Add NewsFeed
self.RssBox = wx.BoxSizer(wx.VERTICAL)
self.RssPanel = wx.lib.scrolledpanel.ScrolledPanel(self.panel)
self.RssPanel.SetMinSize((-1, 100))
self.RssPanel.SetSizer(self.RssBox)
self.updateRSS()
self.RssBox.Fit(self.RssPanel)
self.RssPanel.SetupScrolling()
self.vbox.Add(self.RssPanel, 1, flag=wx.EXPAND | wx.ALIGN_CENTER)
self.panel.SetSizer(self.vbox)
self.vbox.Fit(self)
self.updateCurrentData()
vol=lambda d: d[5]
# create the second axis for the volume bar chart
ax2 = ax.twinx()
# set the position of ax2 so that it is short (y2=0.32) but otherwise the same size as ax
ax2.set_position(matplotlib.transforms.Bbox([[0.125,0.1],[0.9,0.32]]))
# make bar charts and color differently depending on up/down for the day
posList=[]
negList=[]
for i in infoList:
if i[1]-i[4]<0:
posList.append(i)
else: negList.append(i)
ax2.bar(map(date,posList),map(vol,posList),color='green',width=1,align='center')
ax2.bar(map(date,negList),map(vol,negList),color='red',width=1,align='center')
ax2.yaxis.set_label_position("right")
ax2.set_ylabel('Volume')
return fig
def smaPlot(s,N=20,fromDate=None,toDate=None):
return stockPlot(s,"Adj Close",fromDate,toDate,True,N)
if __name__ == "__main__":
Google = stockInfo("GOOG",date(2012,1,1),date.today())
s = stockPlot(Google,'Adj Close',None,None,False,100,None,True)
def test_Beta(self):
with self.assertRaises(ValueError):
Beta(self.testobj, date.min)
self.assertIsInstance(Beta(self.testobj), float)
SP500 = stockInfo("^GSPC")
self.assertEqual(Beta(SP500), 1)
def test_invalidcreation(self):
with self.assertRaises(ValueError):
otherobj = stockInfo("ThingThatDoesNotExist")
def test_invalidcreation(self):
with self.assertRaises(ValueError):
otherobj = stockInfo("ThingThatDoesNotExist")
def setUp(self):
self.testobj = stockInfo("MSFT")
def test_Beta(self):
with self.assertRaises(ValueError):
Beta(self.testobj,date.min)
self.assertIsInstance(Beta(self.testobj),float)
SP500 = stockInfo("^GSPC")
self.assertEqual(Beta(SP500),1)
