def crossover(quotes, d1, d2, params={}):
# define a function that takes a quotes object, so it is an array with elements [day,o,h,l,c]
# and returns a dictionary with keys of buy and sell times
# values are not used (1 here), so that gives us room to pack in more information with this function
print d1, d2
timesclose = quotes[:,[0,4]]
p1, p2 = params["p1"], params["p2"]
p1, p2 = min(p1,p2), max(p1,p2)
if(p2 - p1 <= 1): return { }, { }
emas = [ ind.ematimes(timesclose,i) for i in [p1, p2] ]
crossovertimes = ind.crossovertimes(emas)
for t in crossovertimes:
print u.inum2tuple(t[0])
dCrossovers = {} # turn into dict for fast lookup
for time,rising in crossovertimes: dCrossovers[time] = rising
dBuy = { }
dSell = { }
hasBought = False
boughtPrice = -1.0
for i,day in enumerate(quotes[:,0]):
# only trade within specified window
if( day > u.tuple2inum(d2) or day < u.tuple2inum(d1) ): continue
if(day in dCrossovers):
rising = dCrossovers[day]
if(rising):
dBuy[day] = 1
hasBought = True
boughtPrice = quotes[i][4]
else:
if(hasBought): # don't sell if we already sold
dSell[day] = 1
hasBought = False
# if price is x% lower than what we bought for, get the hell out and sell a certain %
if( hasBought and (0.0 < quotes[i][4] / boughtPrice < 0.90) ):
dSell[day] = 1
hasBought = False
return dBuy, dSell
def crossover(quotes):
timesclose = quotes[:,[0,4]]
emas = [ ind.ematimes(timesclose,i) for i in [5, 10] ]
crossovertimes = ind.crossovertimes(emas)
dCrossovers = {} # turn into dict for fast lookup
for time,rising in crossovertimes: dCrossovers[time] = rising
dBuy = { }
hasBought = False
boughtPrice = -1.0
for i,day in enumerate(quotes[:,0]):
#print day
if(day in dCrossovers):
rising = dCrossovers[day]
if(rising):
dBuy[day] = 1
hasBought = True
boughtPrice = quotes[i][4]
return dBuy
import getStocks as gs
import utils as u
import indicators as ind
import tradeReport as tr
#symbol = "WMT"
symbol = "NFLX"
# symbol = "F"
stock = gs.getStock(symbol, (2011, 6, 1), (2015, 6, 1)) # for calculating
quotes = u.dictToList(stock) # [day,o,h,l,c]
timesclose = quotes[:,[0,4]]
emas = []
for i in [1,2]: emas.append( ind.ematimes(timesclose,10*i) )
crossovertimes = ind.crossovertimes(emas)
dCrossovers = {} # turn into dict for fast lookup
for time,rising in crossovertimes: dCrossovers[time] = rising
# CROSSOVER STRATEGY
price = 0
ledger = tr.Ledger(1000)
for quote in quotes:
day,price,h,l,c = quote
if(day in dCrossovers):
rising = dCrossovers[day]
if(rising): ledger.buyStock(symbol, price)
else: ledger.sellStock(symbol,price)
dBuy = {}
dSell = {}
for i,clusterIdx in enumerate(clusters[:-2]):
profit = clustersAndProfits[clusterIdx]
if(profit > 0.03):
dBuy[times[i+1]] = 1
dSell[times[i+2]] = 1
# colors = list("rbgkcmyw") # only allows up to 8
# clustershading = []
# for i, day in enumerate(times):
# clustershading.append([ day, colors[clusters[i]] ])
crossovershading = []
for day, rising in ind.crossovertimes(emas):
crossovershading.append([day, 'g' if rising else 'r'])
# u.makeCandlestick(clusterQuotes, "../plots/candlestick.png",title="cluster centers",vlines=vlines)
u.makeCandlestick(quotes, "../plots/candlestick.png", title="WMT (2009)", \
# shadings=[clustershading,crossovershading], \
shadings=[crossovershading], \
bbands=bbands, \
window=[d1,d2], \
averages=emas, \
rsis=rsis, \
)
u.web("../plots/candlestick.png")
