def getStock(ticker, d1, d2, verbose=False):
if not iterable(d1): d1 = (d1, 1, 1)
if not iterable(d2): d2 = (d2, 1, 1)
saveStock(ticker, d1, d2)
pickleFile = "%s/%s.pklz" % (storageDir, ticker)
d = { }
d["days"] = { }
try:
fh = gzip.open(pickleFile, "rb")
dOld = pickle.load(fh)
fh.close()
except:
if(verbose): print "[MM] Error: file (%s/%s.pklz) does not exist" % (storageDir, ticker)
return d
dt1, dt2 = datetime.datetime(*d1), datetime.datetime(*d2)
day1, day2 = u.tuple2inum(d1), u.tuple2inum(d2)
for day in dOld["days"].keys():
if( day1 <= day <= day2 ):
d["days"][day] = dOld["days"][day]
return d
def getStock(ticker, d1, d2, verbose=False):
if not iterable(d1): d1 = (d1, 1, 1)
if not iterable(d2): d2 = (d2, 1, 1)
saveStock(ticker, d1, d2)
pickleFile = "%s/%s.pklz" % (storageDir, ticker)
d = {}
d["days"] = {}
try:
fh = gzip.open(pickleFile, "rb")
dOld = pickle.load(fh)
fh.close()
except:
if (verbose):
print "[MM] Error: file (%s/%s.pklz) does not exist" % (storageDir,
ticker)
return d
dt1, dt2 = datetime.datetime(*d1), datetime.datetime(*d2)
day1, day2 = u.tuple2inum(d1), u.tuple2inum(d2)
for day in dOld["days"].keys():
if (day1 <= day <= day2):
d["days"][day] = dOld["days"][day]
return d
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
rising = dCrossovers[day]
if(rising):
dBuy[day] = 1
hasBought = True
boughtPrice = quotes[i][4]
return dBuy
symbols = [line.strip() for line in open("../data/nasdaqlisted.txt").readlines()][:1000]
today = datetime.datetime.today()
dtuple = (today.year,today.month,today.day-3)
goodsymbols = []
for symbol in symbols:
stock = gs.getStock(symbol, (2015, 8, 1), dtuple)
quotes = u.dictToList(stock) # [day,o,h,l,c]
array_quotes = np.array(quotes)
print symbol
if(len(quotes) < 25): continue
if np.mean(quotes[:,4]) > 20: continue
if np.mean(quotes[:,4]) < 0.25: continue
buys = crossover(quotes)
if u.tuple2inum(dtuple) in buys:
print symbol, "#"*40
goodsymbols.append(symbol)
print "-"*40
print " ".join(goodsymbols)
print "-"*40
