def resultsAlphaVsSP500(self):
print("This needs to be redone such that a dict is created for the purchase dates and SP500 on that day")
currentSP500 = -1
startSP500 = -1
currentSP500 = float(StockHelper.getSharePrice("%5EGSPC"))
from datetime import date
today = date.today()
if (
self.purchasedate.day == today.day
and self.purchasedate.month == today.month
and self.purchasedate.year == today.year
):
gspcOpenPrice = StockHelper.getShareOpenPrice("^GSPC")
if (
gspcOpenPrice[0] != "N"
): # check for na value, WEAK TEST could do a regex to see if the price contains a letter
startSP500 = float(gspcOpenPrice)
else:
startSP500 = 0.1
else:
startSP500 = float(
StockHelper.get_historical_price("^GSPC", (self.purchasedate.strftime("%Y%m%d")))
) # "%EGSPC",(self.purchasedate.strftime('%Y%m%d')))
if startSP500 != 0 and self.totalpurchaseprice != 0 and self.currentWorth_func() != 0:
return (
(self.currentWorth_func() - (self.totalpurchaseprice * (1 + (currentSP500 - startSP500) / startSP500)))
/ (self.currentWorth_func())
* 100
) # this returns the percentage over/under (alpha) of the current investment when compared to the SP500 index.; negative values are bad, positive are good
else:
return 0
def resultsIfInvestedInX(self):
print("This needs to be redone such that a dict is created for the purchase dates and TickerX on that day")
currentTickerX = -1
startTickerX = -1
currentTickerX = float(StockHelper.getSharePrice(self.comparisonticker))
# we need to check if this is the first day for this security, as we can't get historical data if this is the first day
from datetime import date
today = date.today()
if (
self.purchasedate.day == today.day
and self.purchasedate.month == today.month
and self.purchasedate.year == today.year
):
startTickerX = float(StockHelper.getShareOpenPrice(self.comparisonticker))
else:
startTickerX = float(
StockHelper.get_historical_price(self.comparisonticker, (self.purchasedate.strftime("%Y%m%d")))
)
if startTickerX != 0:
return self.totalpurchaseprice * (1 + (currentTickerX - startTickerX) / startTickerX)
else:
return 0
def __init__(self,data):
self.ticker=data['ticker']
temp=data["purchaseDate"].split('/')
self.purchaseDate=datetime.datetime(int(temp[2]),int(temp[0]),int(temp[1]))
self.totalPurchasePrice=data['totalPurchasePrice']
self.commissionToBuy=data['commissionToBuy']
#self.unitPriceAtPurchase=get_historical_prices_plus_one_day(self.ticker,(self.purchaseDate.strftime('%Y%m%d'))) #NO LONGER USING this version since IBD lists are published the night before their list date, so you could purchase at the open.
self.unitPriceAtPurchase=StockHelper.get_historical_price(self.ticker,(self.purchaseDate.strftime('%Y%m%d')))
self.unitPriceAtPresent=StockHelper.getSharePrice(self.ticker)
def resultsIfInvestedInSP500(self):
print("This needs to be redone such that a dict is created for the purchase dates and SP500 on that day")
currentSP500=-1
startSP500=-1
currentSP500=float(StockHelper.getSharePrice("%5EGSPC"))
#we need to check if this is the first day for this security, as we can't get historical data if this is the first day
from datetime import date
today = date.today()
if ( self.purchasedate.day == today.day and self.purchasedate.month == today.month and self.purchasedate.year == today.year):
startSP500=float(StockHelper.getShareOpenPrice("^GSPC"))
else:
startSP500=float(StockHelper.get_historical_price("^GSPC",(self.purchasedate.strftime('%Y%m%d'))))
if (startSP500 != 0):
return (self.totalpurchaseprice*(1+(currentSP500-startSP500)/startSP500))
else:
return 0