def work(_1, _2):
portfolio = {}
dtit = dtstart
prevs = []
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA", "y")
traceA['prev_len'] = _1
traceB = core.createNewScatterTrace("traceB", "y")
traceB['prev_len'] = _2
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
price = (o+c)/2 # ok
# price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
# price = random.uniform(l, h) # much worse than [open, close]
buyprice = price
sellprice = price
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
core.addToScatterTrace(traceA, dtit, sig(traceA['prev_len'], traceA['y'], prevs, price))
core.addToScatterTrace(traceB, dtit, sig(traceB['prev_len'], traceB['y'], prevs, price))
if len(traceA['y']) > 1:
if canBuy and (traceA['y'][-2] < traceB['y'][-2] and traceA['y'][-1] > traceB['y'][-1]):
core.portfolioBuy(portfolio, dtit, buyprice, uncertainty_margin)
canSell = True
canBuy = False
elif canSell and (traceA['y'][-2] > traceB['y'][-2] and traceA['y'][-1] < traceB['y'][-1]):
core.portfolioSell(portfolio, dtit, sellprice, uncertainty_margin)
canSell = False
canBuy = True
prevs.append(price)
dtit += datetime.timedelta(minutes=interval)
# beautify (replacing 0's by None )
for i,v in enumerate(traceB['y']):
if v == 0:
traceB['y'][i]=None
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceA, traceB])
def work(_1, _2, _3, _4):
portfolio = {}
dtit = dtstart
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA", "y")
traceB = core.createNewScatterTrace("traceB", "y")
buyPrice = None
prevC = None
prevCavg = None
bucket=[]
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
#price = (o+c+l+h)/4 # ok
#price = (o+c)/2 # ok
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
shouldBuy=False
if idx in preds:
x1,y1=list(preds[idx].items())[0]
x2,y2=list(preds[idx].items())[1]
_2 = 1.002
if ((y2['open']+y2['high']+y2['low']+y2['close'])/4) > ((y1['open']+y1['high']+y1['low']+y1['close'])/4)*_2:
shouldBuy=True
#if canBuy and (prevCavg < 0 and pCavg > 0) and pE > 0:
if canBuy and shouldBuy :
core.portfolioBuy(portfolio, dtit, price, uncertainty_margin)
canSell = True
canBuy = False
buyPrice = price
elif canSell and (price > buyPrice*_3 or price < buyPrice*_4):
core.portfolioSell(portfolio, dtit, price, uncertainty_margin)
canSell = False
canBuy = True
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [ traceA, traceB ])
def work():
portfolio = {}
dtit = dtstart
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA", "y")
traceC = core.createNewScatterTrace("traceC", "y")
hp_arrL = 35
hp_arrEL = 4
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
volume = inp[idx]['volume']
trades = inp[idx]['trades']
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
price = random.randint(
int(l), int(h)) if int(h) > int(l) else random.randint(
int(h), int(l)
) # still "okay" but much worse than [open, close]
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
pA = sigA(traceA['y'], traceA['z'], price, hp_arrL, hp_arrEL)
pC = sigC(traceC['y'], traceA['z'], price, hp_arrL, hp_arrEL)
core.addToScatterTrace(traceA, dtit, pA)
core.addToScatterTrace(traceC, dtit, pC)
#if canBuy and (pC >= o and pC <= c):
if canBuy and (pC >= l and pC <= h):
core.portfolioBuy(portfolio, dtit, price,
uncertainty_margin)
canSell = True
canBuy = False
#elif canSell and (pA >= c and pA <= o):
elif canSell and (pA >= l and pA <= h):
core.portfolioSell(portfolio, dtit, price,
uncertainty_margin)
canSell = False
canBuy = True
dtit += datetime.timedelta(minutes=interval)
finalizeTrace(traceA)
finalizeTrace(traceC)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceA, traceC])
def work(dtstart, dtend):
portfolio = {}
prevPrice = None
prev_slope_pct = None
canBuy = True
canSell = False
dtit = dtstart
while dtit < dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
# let price be any random value in range [open, close]
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
#price = random.uniform(l, h) # much worse than [open, close]
# let the price be any random value in range [open ; (close-open)*x ] where x is in range [0.0 ; 1.0]
#price = o + (c-o)*random.randint(0,10)/10
price = o + (c-o)*random.randint(0,10)/10
# price = o
buyprice = price
sellprice = price
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
if prevPrice != None:
slope_pct = round((price-prevPrice)/prevPrice*100,2)
if canBuy:
if slope_pct > slope_pct_threshold :
# buy
core.portfolioBuy(portfolio, dtit, buyprice, uncertainty_margin)
canSell = True
canBuy = False
elif canSell and slope_pct <= 0:
# sell
core.portfolioSell(portfolio, dtit, sellprice, uncertainty_margin)
canSell = False
canBuy = True
prev_slope_pct = slope_pct
prevPrice = c
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1, 1)
return (proc, portfolio)
def work(dtstart, dtend):
portfolio = {}
prevPrice = None
slopes = []
dtit = dtstart
while dtit < dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
# let price be any random value in range [open, close]
# price = random.uniform(o, c) if c > o else random.uniform(c, o)
# price = random.uniform(l, h) # much worse than [open, close]
# let the price be any random value in range [open ; (close-open)*x ] where x is in range [0.0 ; 1.0]
price = o + (c-o)*random.randint(0,10)/10
# this strategy seems to stop working when we use range [low, high]
# however in reality there is a chance the system takes near-low/high values, as a result the ROI will be low or even negative.
buyprice = price
sellprice = price
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
if prevPrice != None:
slope_pct = round((price-prevPrice)/prevPrice*100,2)
slopes.append(slope_pct)
if price > prevPrice:
slopes.append( slope_pct )
avgS = sum(slopes)/len(slopes)
if avgS > slope_pct_threshold : # len(slopes) > 1 and
# buy
core.portfolioBuy(portfolio, dtit, buyprice, uncertainty_margin)
else:
if len(slopes) > 0:
# sell
core.portfolioSell(portfolio, dtit, sellprice, uncertainty_margin)
slopes = []
prevPrice = c
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio)
def work():
portfolio = {}
dtit = dtstart
prevs = []
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA", "y2")
traceA['prev_len'] = 10
traceB = core.createNewScatterTrace("traceB", "y")
traceB[
'prev_len'] = 12 # make sure it's large enough ( >= 12) for isDownTrend formula
upduration_A = 0
downduration_A = 0
prevBuyPrice = 0
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
price = (o + c) / 2 # ok
# price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
# price = random.uniform(o, c) if c > o else random.uniform(c, o)
# price = random.uniform(l, h) # much worse than [open, close]
buyprice = price
sellprice = price
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
if len(prevs) > 0:
core.addToScatterTrace(
traceA, dtit, sig(traceA['prev_len'], prevs, price, 1))
core.addToScatterTrace(
traceB, dtit, sig2(traceB['prev_len'], prevs, price))
if len(traceA['y']) > 1:
if traceA['y'][-1] > 0 and traceA['y'][
-2] > 0: # A up -> up
upduration_A += 1
if traceA['y'][-1] < 0 and traceA['y'][
-2] > 0: # A up -> down
upduration_A = 0
if traceA['y'][-1] < 0 and traceA['y'][
-2] < 0: # A down -> down
downduration_A += 1
if traceA['y'][-1] > 0 and traceA['y'][
-2] < 0: # A down -> up
downduration_A = 0
if canBuy and isDownTrend(
traceB['y'][-traceB['prev_len']:]) == False:
if traceA['y'][-1] > 0 and traceA['y'][
-2] < 0: # B down -> up
core.portfolioBuy(portfolio, dtit, buyprice,
uncertainty_margin)
prevBuyPrice = buyprice
canSell = True
canBuy = False
elif canSell:
if traceA['y'][-1] < 0 and traceA['y'][
-2] > 0: # B up -> down
core.portfolioSell(portfolio, dtit, sellprice,
uncertainty_margin)
canSell = False
canBuy = True
else:
core.addToScatterTrace(traceA, dtit,
0) # use 0 instead of None
core.addToScatterTrace(traceB, dtit,
0) # use 0 instead of None
prevs.append(price)
# else:
# print("missing: " + str(idx))
dtit += datetime.timedelta(minutes=interval)
# beautify (replacing 0's by None )
for i, v in enumerate(traceB['y']):
if v == 0:
traceB['y'][i] = None
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceA, traceB])
def work(_1, _2, _3, _4, _5, _6):
portfolio = {}
dtit = dtstart
traceA = core.createNewScatterTrace("traceA", "y")
traceA['prev_len'] = _1
traceB = core.createNewScatterTrace("traceB", "y")
traceB['prev_len'] = _2
traceC = core.createNewScatterTrace("W&L", "y2")
usage = {
'canBuy': True,
'canSell': False,
'buyPrice': None,
'sellPrice': None,
'prevPrice': None,
'win': 0,
'loss': 0,
}
bucket = []
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
price = (o + c + l + h) / 4 # ok
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
#price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
pA = sig(
traceA['prev_len'],
np.average(traceA['y'][-_3:]) if len(traceA['y']) > 0 else
(o + c) / 2, (o + c) / 2)
pB = sig(
traceB['prev_len'],
np.average(traceB['y'][-_3:]) if len(traceB['y']) > 0 else
(o + c) / 2, (o + c) / 2)
core.addToScatterTrace(traceA, dtit, pA)
core.addToScatterTrace(traceB, dtit, pB)
bucket.append(pA) # dummy
def buyF():
if np.average(traceB['y'][-_4:]) > traceB['y'][-1]:
return False
if traceB['y'][-2] > traceA['y'][-2] and traceB['y'][
-1] < traceA['y'][-1]:
return True
if traceB['y'][-1] > traceB['y'][-2]:
return True
def sellF():
if price > usage['buyPrice'] * _5 and not buyF():
usage['win'] += 1
return True
if price < usage['buyPrice'] * _6:
usage['loss'] += 1
return True
if len(bucket) > 2:
if usage['canBuy'] and buyF():
core.portfolioBuy(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = True
usage['canBuy'] = False
usage['buyPrice'] = price
elif usage['canSell'] and sellF():
core.portfolioSell(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = False
usage['canBuy'] = True
usage['sellPrice'] = price
core.addToScatterTrace(traceC, dtit, (1 + usage['win']) /
(1 + usage['loss']))
usage['prevPrice'] = price
dtit += datetime.timedelta(minutes=interval)
for i, v in enumerate(
traceB['y']): # beautify (replacing 0's by None )
if v == 0:
traceB['y'][i] = None
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [
traceA,
traceB,
traceC,
])
def work(_1, _2, _3):
portfolio = {}
dtit = dtstart
traceD = core.createNewScatterTrace("traceD", "y2")
usage = {
'canBuy': True,
'canSell': False,
'buyPrice': None,
'sellPrice': None,
'prevPrice': None,
}
bucket = []
bucketstd = []
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
price = (o + c + l + h) / 4 # ok
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
def buyF():
if len(traceD['y']) < 2:
return False
if traceD['y'][-2] == 1 and traceD['y'][-1] == -1:
return True
#if traceD['y'][-1] == 1 and traceD['y'][-2] == -1:
# return True
def sellF():
if price > usage['buyPrice'] * _1:
return True
if price < usage['buyPrice'] * _2:
return True
if len(bucket) > 2:
pD = np.average(bucket[-_3:])
pD = 1 if pD > 1 else -1
core.addToScatterTrace(traceD, dtit, pD)
if usage['canBuy'] and buyF():
core.portfolioBuy(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = True
usage['canBuy'] = False
usage['buyPrice'] = price
elif usage['canSell'] and sellF():
core.portfolioSell(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = False
usage['canBuy'] = True
usage['sellPrice'] = price
usage['countSinceSell'] = 0
if usage['prevPrice'] != None:
bucket.append(price / usage['prevPrice'])
usage['prevPrice'] = price
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceD])
def work(_1, _2, _3, _4):
portfolio = {}
dtit = dtstart
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA", "y")
traceA['prev_len'] = _1
traceB = core.createNewScatterTrace("traceB", "y")
traceB['prev_len'] = _2
traceC = core.createNewScatterTrace("traceC", "y2")
traceD = core.createNewScatterTrace("traceD", "y2")
buyPrice = None
prevC = None
prevCavg = None
bucket = []
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
#price = (o+c+l+h)/4 # ok
#price = (o+c)/2 # ok
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
pA = sig(traceA['prev_len'], traceA['y'], o)
pB = sig(traceB['prev_len'], traceB['y'], c)
pC = pA - pB
pC = sig(3, [prevC if prevC != None else pC], pC)
bucket.append(pC)
pCavg = np.average(bucket[-10:])
core.addToScatterTrace(traceA, dtit, pA)
core.addToScatterTrace(traceB, dtit, pB)
core.addToScatterTrace(traceC, dtit, pC)
core.addToScatterTrace(traceD, dtit, pCavg)
if len(bucket) > 2:
if canBuy and (prevCavg < 0 and pCavg > 0):
core.portfolioBuy(portfolio, dtit, price,
uncertainty_margin)
canSell = True
canBuy = False
buyPrice = price
elif canSell and (price > buyPrice * _3
or price < buyPrice * _4):
core.portfolioSell(portfolio, dtit, price,
uncertainty_margin)
canSell = False
canBuy = True
prevC = pC
prevCavg = pCavg
dtit += datetime.timedelta(minutes=interval)
for i, v in enumerate(
traceB['y']): # beautify (replacing 0's by None )
if v == 0:
traceB['y'][i] = None
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceA, traceB, traceC, traceD])
def work(dtstart, dtend, inp, interval, uncertainty_margin, _1, _2, _3):
portfolio = {}
dtit = dtstart
traceA = core.createNewScatterTrace("traceA", "y2")
traceB = core.createNewScatterTrace("traceB", "y2")
traceC = core.createNewScatterTrace("traceC", "y2")
traceD = core.createNewScatterTrace("traceD", "y2")
usage = {
'canBuy': True,
'canSell': False,
'buyPrice': None,
'sellPrice': None,
'prevPrice': None,
'prevClose': None,
}
bucket_gain = []
bucket_loss = []
counter = 0
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
price = (o + c + l + h) / 4 # ok
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
#price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
if usage['prevClose']:
dx = price - usage['prevClose']
if (dx > 0):
bucket_gain.append(abs(dx)) # dummy
core.addToScatterTrace(traceA, dtit, 1)
else:
bucket_loss.append(abs(dx))
core.addToScatterTrace(traceA, dtit, -1)
counter += 1
if counter > _1:
# print(bucket_gain)
# print(bucket_loss)
aGain = np.average(
bucket_gain[-_1:]) if len(bucket_gain[-_1:]) > 0 else 0
aLoss = np.average(
bucket_loss[-_1:]) if len(bucket_loss[-_1:]) > 0 else 0
#aGain = sig(_1, np.average(bucket_gain[-_1:-1]), bucket_gain[-1]) if len(bucket_gain[-_1:])>0 else 0
#aLoss = sig(_1, np.average(bucket_loss[-_1:-1]), bucket_loss[-1]) if len(bucket_loss[-_1:])>0 else 0
if (aLoss != 0):
RSI = (100 - (100 / (1 + (aGain / aLoss))))
#if (abs(RSI) > 100): print(aGain, aLoss)
core.addToScatterTrace(traceB, dtit, RSI)
if len(traceB['y']) > 0:
p = 10 if np.average(
traceB['y'][-10:]) > traceB['y'][-1] else 0
core.addToScatterTrace(traceC, dtit, p)
def buyF():
if len(traceC['y']) <= 1: return False
# if traceC['y'][-1] < 35: return False
# if traceC['y'][-1] > 60: return False
# if np.average(traceC['y'][-5:]) > traceC['y'][-1]: return False
# #if traceC['y'][-2] > traceD['y'][-2] and traceC['y'][-1] < traceD['y'][-1]:
# if traceC['y'][-2] < traceD['y'][-2] and traceC['y'][-1] > traceD['y'][-1]:
# return True
#return False
if np.average(traceC['y'][-5:]) > 6:
return True
def sellF():
if price > usage['buyPrice'] * _2 and not buyF():
return True
if price < usage['buyPrice'] * _3:
return True
if counter > _1:
if usage['canBuy'] and buyF():
core.portfolioBuy(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = True
usage['canBuy'] = False
usage['buyPrice'] = price
elif usage['canSell'] and sellF():
core.portfolioSell(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = False
usage['canBuy'] = True
usage['sellPrice'] = price
usage['prevPrice'] = price
usage['prevClose'] = c
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceA, traceB, traceC, traceD])
def work(_1, _2):
portfolio = {}
dtit = dtstart
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA", "y")
traceC = core.createNewScatterTrace("traceC", "y3")
traceD = core.createNewScatterTrace("traceD", "y3")
traceE = core.createNewScatterTrace("traceE", "y3")
traceF = core.createNewScatterTrace("traceF", "y3")
hp_arrL = 35
hp_arrEL = 4
usage = {
'canBuy': True,
'canSell': False,
'buyPrice': None,
'prevPrice': None
}
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
volume = inp[idx]['volume']
trades = inp[idx]['trades']
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
price = (o + c + l + h) / 4 # ok
#price = (o+c)/2
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
#price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
core.addToScatterTrace(traceC, dtit, (c - o))
core.addToScatterTrace(
traceD, dtit,
np.std(traceC['y'][-16:]) * 2 +
np.average([abs(x) for x in traceC['y'][-16:]]))
def buyF():
if len(traceD['y']) < 2: return False
if traceC['y'][-2] < traceD['y'][-2] and traceC['y'][
-1] > traceD['y'][-1]:
return True
def sellF():
if price > usage['buyPrice'] * _1: #and not buyF():
return True
if price < usage['buyPrice'] * _2:
return True
if usage['canBuy'] and buyF():
core.portfolioBuy(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = True
usage['canBuy'] = False
usage['buyPrice'] = price
elif usage['canSell'] and sellF():
core.portfolioSell(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = False
usage['canBuy'] = True
usage['sellPrice'] = price
usage['prevPrice'] = price
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [
traceA,
traceC,
traceD,
traceE,
traceF,
])
def work(_1, _2):
portfolio = {}
dtit = dtstart
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA" ,"y")
traceC = core.createNewScatterTrace("traceC" ,"y2", 'markers')
traceD = core.createNewScatterTrace("traceD" ,"y2", 'markers')
traceE = core.createNewScatterTrace("traceE" ,"y3")
hp_arrL = 35
hp_arrEL = 4
usage = {
'canBuy': True,
'canSell': False,
'buyPrice': None,
'timeHeld': 0,
}
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
volume = inp[idx]['volume']
trades = inp[idx]['trades']
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
#price = (o+c+l+h)/4 # ok
price = (o+c)/2
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
#price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
core.addToScatterTrace(traceA, dtit, (o+h+l+c)/4)
pC = 1-1/(1+(price/np.average(traceA['y'][-24:])))
core.addToScatterTrace(traceC, dtit, pC)
core.addToScatterTrace(traceD, dtit, np.average(traceC['y'][-24:]))
if len(traceD['y']) > 8:
pD = 1 if np.average(traceD['y'][-8:-4]) > np.average(traceD['y'][-4:-2]) and np.average(traceD['y'][-4:-2]) < np.average(traceD['y'][-2:]) else 0
#pD = 1 if traceD['y'][-1] > traceD['y'][-3] and traceD['y'][-2] < traceD['y'][-3] and traceD['y'][-2] < traceD['y'][-1] else 0
core.addToScatterTrace(traceE, dtit, pD )
def buyF():
if len(traceE['y']) < 2: return False
if traceE['y'][-2] == 0 and traceE['y'][-1]==1:
return True
def sellF():
if traceD['y'][-1] < .5 and usage['timeHeld'] > 5:
return True
if price > usage['buyPrice']*_1: #and not buyF():
return True
if price < usage['buyPrice']*_2:
return True
if usage['canBuy'] and buyF():
core.portfolioBuy(portfolio, dtit, price, uncertainty_margin)
usage['canSell'] = True
usage['canBuy'] = False
usage['timeHeld'] = 0
usage['buyPrice'] = price
elif usage['canSell'] and sellF():
core.portfolioSell(portfolio, dtit, price, uncertainty_margin)
usage['canSell'] = False
usage['canBuy'] = True
usage['timeHeld'] = 0
usage['sellPrice'] = price
usage['timeHeld']+=1
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceA, traceC, traceD, traceE, ])
def work(_1, _2):
portfolio = {}
dtit = dtstart
canBuy = True
canSell = False
traceA = core.createNewScatterTrace("traceA", "y")
traceC = core.createNewScatterTrace("traceC", "y")
hp_arrL = 35
hp_arrEL = 4
usage = {
'canBuy': True,
'canSell': False,
'buyPrice': None,
}
while dtit <= dtend:
idx = datetime.datetime.strftime(dtit, '%Y-%m-%dT%H:%M')
if idx in inp:
volume = inp[idx]['volume']
trades = inp[idx]['trades']
c = inp[idx]['close']
o = inp[idx]['open']
l = inp[idx]['low']
h = inp[idx]['high']
#price = (o+c+l+h)/4 # ok
price = (o + c) / 2
#price = c # ok
#price = o + (c-o)*random.randint(0,10)/10 # ok
#price = random.uniform(o, c) if c > o else random.uniform(c, o)
price = random.uniform(l, h) # reality
core.portfolioPriceEntry(portfolio, dtit, price, o, c, l, h)
pA = sigA(traceA['y'], traceA['z'], price, hp_arrL, hp_arrEL)
pC = sigC(traceC['y'], traceA['z'], price, hp_arrL, hp_arrEL)
core.addToScatterTrace(traceA, dtit, pA)
core.addToScatterTrace(traceC, dtit, pC)
def buyF():
#if pC >= o and pC <= c:
if pC >= l and pC <= h:
return True
def sellF():
if price > usage['buyPrice'] * _1: #and not buyF():
return True
if price < usage['buyPrice'] * _2:
return True
if usage['canBuy'] and buyF():
core.portfolioBuy(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = True
usage['canBuy'] = False
usage['buyPrice'] = price
elif usage['canSell'] and sellF():
core.portfolioSell(portfolio, dtit, price,
uncertainty_margin)
usage['canSell'] = False
usage['canBuy'] = True
usage['sellPrice'] = price
dtit += datetime.timedelta(minutes=interval)
proc = core.processPortfolio(portfolio, 1)
return (proc, portfolio, [traceA, traceC])
