def build_key_array(tradeAction, bars_15m, bars_1h, bars_1d):
#These has to be in sequential order since insert adds rather than replace.
cci_key = "long"
if tradeAction == "Sell":
cci_key = "short"
cci_key += categories.categorize_atr15(bars_15m.atr) + categories.categorize_atr1h(bars_1h.atr) + categories.categorize_atr1d(bars_1d.atr) + \
categories.categorize_cci_15(bars_15m.cci) + categories.categorize_cci_15_avg(bars_15m.ccia) + categories.categorize_cci_1h(bars_1h.ccia) + \
categories.categorize_cci_1d(bars_1d.ccia) + categories.categorize_spread(bars_15m.cci_ccia_spread)
#categories.categorize_cci_1d(bars_1d.ccia) + bars_1h.cci_over_ccia_tf + bars_1d.cci_over_ccia_tf + categories.categorize_spread(bars_15m.cci_ccia_spread)
cci_key_no_spread = "long"
if tradeAction == "Sell":
cci_key_no_spread = "short"
cci_key_no_spread += categories.categorize_atr15(bars_15m.atr) + categories.categorize_atr1h(bars_1h.atr) + categories.categorize_atr1d(bars_1d.atr) + \
categories.categorize_cci_15(bars_15m.cci) + categories.categorize_cci_15_avg(bars_15m.ccia) + categories.categorize_cci_1h(bars_1h.ccia) + \
categories.categorize_cci_1d(bars_1d.ccia)
#ccibb_key = cci_key_no_spread + categories.categorize_BBW15(bars_15m.bband_width) + categories.categorize_BBb15(bars_15m.bband_b) + categories.categorize_BBW1h(bars_1h.bband_width) + \
# categories.categorize_BBb1h(bars_1h.bband_b) + categories.categorize_BBW1d(bars_1d.bband_width) + categories.categorize_BBb1d(bars_1d.bband_b)
summ_key = categories.categorize_cci_15_avg(
bars_15m.ccia) + categories.categorize_cci_1h(
bars_1h.ccia) + categories.categorize_cci_1d(
bars_1d.ccia) + categories.categorize_spread(
bars_15m.cci_ccia_spread)
#summ_key = categories.categorize_cci_15_avg(bars_15m.ccia) + categories.categorize_cci_1h(bars_1h.ccia) + categories.categorize_cci_1d(bars_1d.ccia) + bars_1h.cci_over_ccia_tf + bars_1d.cci_over_ccia_tf + categories.categorize_spread(bars_15m.cci_ccia_spread)
#return cci_key, cci_key_no_spread, summ_key
return cci_key, cci_key, summ_key
def run(self):
""" Execute the algorithm """
key_arr = [
'blank', 'ATR15', 'ATR1', 'ATRD', 'CCI15', 'CCIA15', 'CCIA1h',
'CCIA1d', 'BBW15', 'BBb15', 'BBW1h', 'BBb1h', 'BBW1d', 'BBb1d'
]
tradenow = False
not_finished = True
tradenow = False
cci_trade = False
ccibb_trade = False
while not_finished:
print("top of algo run self")
crossed = False
self.app.crossover.update(crossed)
contContract = get_contract(self)
dataContract = Contract(exchange=config.EXCHANGE,
secType="FUT",
localSymbol=contContract.localSymbol)
log.info("Got Contract: {}".format(dataContract.localSymbol))
self.app.contract.update(dataContract.localSymbol)
# my add
nextday = datetime.now().day
nexthour = datetime.now().hour
# endDateTime=datetime(int(date.today().year),int(date.today().month),int(nextday),int(nexthour),int(nextqtr),int(0)),
if datetime.now().minute < 15:
nextqtr = 15
getqtr = 30
elif datetime.now().minute < 30:
nextqtr = 30
getqtr = 45
elif datetime.now().minute < 45:
nextqtr = 45
getqtr = 0
else:
nexthour = nexthour + 1
nextqtr = 0
getqtr = 15
test = (datetime(int(date.today().year), int(date.today().month),
int(nextday), int(nexthour), int(getqtr), int(0)))
print("nextqtr and getqtr {} {}".format(nextqtr, getqtr))
log.info(
"next datetime for 15 minutes - should be 15 minutes ahead of desired nextqtr{}"
.format(test))
#
#nextqtr = datetime.now().minute + 1
#print ("we manually overwrote start time")
#print (nextqtr)
#
self.ib.waitUntil(time(hour=nexthour, minute=nextqtr))
# 15 Minute Data
self.app.qtrhour.update(datetime.now())
print(datetime.now())
log.info(
"requesting info for the following timeframe today: {} nexthour: {} minutes: {}"
.format(date.today().day, nexthour + 1, getqtr))
bars_15m = self.get_bars_data(dataContract, "2 D", "15 mins",
date.today().day, nexthour + 1,
getqtr)
x = np.array(bars_15m)
log.debug("15 min bars {}".format(bars_15m[-1]))
#sef.app. barupdateEvent_15m(baas_15m, True)
#aars_15m.updateEvent += self.app.barupdateEvent_15m
log.info("Got 15m data subscription")
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_15m)
atr, atrprior = calculate_atr(bars_15m)
bband_width, bband_b, bband_width_prior, bband_b_prior = calculate_bbands(
bars_15m)
log.info("starting 15 minutes".format(datetime.now()))
log.info("CCI: {} ".format(cci))
log.info("CCIA {} ".format(avg))
log.info("CCIP {} ".format(cci_prior))
log.info("CCIPA: {} ".format(averageh))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
#key_arr = []
if (cci > cci_prior
and cci_prior < cci3) or (cci < cci_prior
and cci_prior > cci3):
crossed = True
tradenow = True
csv_row = "'" + str(datetime.now()) + ",'long'"
key_arr[0] = "long"
else:
crossed = True
tradenow = True
csv_row = "'" + str(datetime.now()) + ",'short'"
key_arr[0] = "short"
csv_row += ",'" + str(crossed) + "'," + str(cci) + "," + str(
avg) + "," + str(cci_prior) + "," + str(averageh) + "," + str(
atr) + "," + str(bband_width) + "," + str(bband_b)
print(key_arr)
key_arr[1] = categories.categorize_atr15(atr)
key_arr[4] = categories.categorize_cci_15(cci)
key_arr[5] = categories.categorize_cci_15_avg(avg)
key_arr[8] = categories.categorize_BBW15(bband_width)
key_arr[9] = categories.categorize_BBb15(bband_b)
stat = "check crossed status"
#print("printing self app ********************************************")
#print(Indicator.data)
self.app.status1.update(stat)
self.app.crossover.update(crossed)
self.app.cci15.update(f"{cci:.02f}")
self.app.cci15_av.update(f"{avg:.02f}")
self.app.cci15p_av.update(f"{averageh:.02f}")
self.app.cci15p.update(f"{cci_prior:.02f}")
self.app.atr15.update(f"{atr:.02f}")
self.app.bband15_width.update(f"{bband_width:.04f}")
self.app.bband15_b.update(f"{bband_b:.04f}")
self.app.qtrhour.update(qtrtime)
#1 hour data
test = (datetime(int(date.today().year), int(date.today().month),
int(nextday), int(nexthour), int(getqtr), int(0)))
#log.info("next datetime for 1 hour - should be 1 hour behind current hour {}".format(test))
log.info(
"requesting info for the following timeframe today: {} nexthour: {} minutes: {} "
.format(date.today().day, nexthour, 0))
bars_1h = self.get_bars_data(dataContract, "5 D", "1 hour",
date.today().day, nexthour, 0)
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1h)
log.debug("bars_1h {}".format(bars_1h[-1]))
atr, atrprior = calculate_atr(bars_1h)
bband_width, bband_b, bband_width_prior, bband_b_prior = calculate_bbands(
bars_1h)
csv_row += "," + str(cci) + "," + str(avg) + "," + str(
atr) + "," + str(bband_width) + "," + str(bband_b)
key_arr[2] = categories.categorize_atr1h(atr)
key_arr[6] = categories.categorize_cci_1h(avg)
key_arr[10] = categories.categorize_BBW1h(bband_width)
key_arr[11] = categories.categorize_BBb1h(bband_b)
log.info("starting 1H ")
log.info("CCI {} ".format(cci))
log.info("CCIA: {} ".format(avg))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
self.app.cci1h.update(f"{cci:.02f}")
self.app.cci1h_av.update(f"{avg:.02f}")
self.app.bband1h_b.update(f"{bband_b:.04f}")
self.app.bband1h_width.update(f"{bband_width:.04f}")
self.app.atr1h.update(f"{atr:.02f}")
log.info(
"requesting info for the following timeframe today: nextday: {} hour: {} minute: {} "
.format((nextday - 1), 0, 0))
bars_1d = self.get_bars_data(dataContract, "75 D", "1 day",
nextday - 1, 0, 0)
log.debug("1d min bars {}".format(bars_1d[-1]))
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1d)
atr, atrprior = calculate_atr(bars_1d)
bband_width, bband_b, bband_width_prior, bband_b_prior = calculate_bbands(
bars_1d)
csv_row += "," + str(cci) + "," + str(avg) + "," + str(
atr) + "," + str(bband_width) + "," + str(bband_b)
key_arr[3] = categories.categorize_atr1d(atr)
key_arr[7] = categories.categorize_cci_1d(avg)
key_arr[12] = categories.categorize_BBW1d(bband_width)
key_arr[13] = categories.categorize_BBb1d(bband_b)
log.info("starting 1H ")
log.info("starting 1D ")
log.info("CCIP {} ".format(cci))
log.info("CCIPA: {} ".format(avg))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
qtrtime = datetime.now()
self.app.cci1d.update(f"{cci:.02f}")
self.app.cci1d_av.update(f"{avg:.02f}")
self.app.bband1d_b.update(f"{bband_b:.04f}")
self.app.bband1d_width.update(f"{bband_width:.04f}")
self.app.atr1d.update(f"{atr:.02f}")
if tradenow:
csv_file = csv.reader(open('data/ccibb.csv', "rt"),
delimiter="'")
for row in csv_file:
if (''.join(key_arr)) == row[0]:
print("we have a match in ccibb.csv")
print(row)
ccibb_trade = True
csv_file = csv.reader(open('data/cci.csv', "rt"),
delimiter="'")
for row in csv_file:
if (''.join(key_arr[0:7])) == row[0]:
print("we have a match in cci.csv")
print(row)
cci_trade = True
csv_row += "," + (''.join(key_arr)) + "," + str(
ccibb_trade) + "," + str(ccibb_trade)
with open('data/hist15.csv', mode='a') as hist15:
histwriter = csv.writer(hist15,
delimiter=',',
quotechar='"',
quoting=csv.QUOTE_MINIMAL)
histwriter.writerow([csv_row])
print("key array comming *************************")
print(''.join(key_arr))
log.info("key array {}".format(key_arr))
#key_arr.clear()
tradenow = False
cci_trade = False
ccibb_trade = False
def run(self):
""" Execute the algorithm """
key_arr = ['blank','ATR15','ATR1','ATRD','CCI15','CCIA15','CCIA1h','CCIA1d','BBW15','BBb15','BBW1h','BBb1h','BBW1d','BBb1d']
tradenow = False
not_finished = True
pendingshort = False
pendinglong = False # this is when the cross over is not wide enough
PendingLongCnt = 0
PendingShortCnt = 0
tradenow = False
cci_trade = False
ccibb_trade = False
while not_finished:
print ("top of algo run self*************************************************")
#top of logic - want to check status as we enter a new bar/hour/day/contract
crossed = False
contContract, contracthours = get_contract(self) #basic information on continuious contact
#i NEW
tradeContract = self.ib.qualifyContracts(contContract)[0] # gives all the details of a contract so we can trade it
open_long, open_short, position_qty = self.have_position(self.ib.positions()) # do we have an open position?
open_today = helpers.is_open_today(contracthours)
dataContract = Contract(exchange=config.EXCHANGE, secType="FUT", localSymbol=contContract.localSymbol)
log.debug("Got Contract: {}".format(dataContract.localSymbol))
#pnl = self.ib.pnl()
log.debug("account names: {}".format(self.ib.managedAccounts()))
log.info("PNL : {PNL} ".format(PNL=self.ib.pnl("all")))
self.app.contract.update(dataContract.localSymbol)
wait_time, datetime_15, datetime_1h, datetime_1d = self.define_times()
log.debug("next datetime for 15 minutes - should be 15 minutes ahead of desired nextqtr{}".format(wait_time))
self.ib.waitUntil(wait_time)
self.app.qtrhour.update(wait_time)
log.debug("requesting info for the following timeframe today: {} ".format(wait_time))
#
#start of study
#
bars_15m = self.get_bars_data(dataContract,"2 D","15 mins",datetime_15)
print("bar data close: ",bars_15m[-1].close)
x = np.array(bars_15m)
log.debug("15 min bars {}".format(str(bars_15m[-1])))
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_15m)
atr, atrprior = calculate_atr(bars_15m)
bband_width, bband_b,bband_width_prior, bband_b_prior = calculate_bbands(bars_15m)
logged_it = self.log_value("Starting 15 minutes", cci,avg,cci_prior, averageh,atr,bband_width,bband_b)
qtrtime = datetime.now()
print("stop loss = ",round((bars_15m[-1].close + (atr *2))*4,0)/4)
if cci > avg and cci_prior < averageh:
crossed = True
tradenow = True
csv_row = "'"+str(datetime.now())+",'long'"
key_arr[0] = "long"
tradeAction = "BUY"
stoplossprice = round((bars_15m[-1].close - (atr * 2))*4,0)/4
elif cci < avg and cci_prior > averageh:
crossed = True
tradenow = True
csv_row = "'"+str(datetime.now())+",'short'"
key_arr[0] = "short"
tradeAction = "SELL"
stoplossprice = round((bars_15m[-1].close + (atr * 2))*4,0)/4
else:
csv_row = "'"+str(datetime.now())+",'cash'"
crossed = False
tradenow = False
stoplossprice = 0
stoploss = 0
if abs(cci - avg) > config.SPREAD:
log.info("Pending ".format(cci-avg))
pendinglong = True
pendingshort = True
csv_header = "Date,Status,Crossed,CCI15,CCIA15,CCI15P,CCIA15P,ATR15,BBw15,BBB15"
csv_row += ",'"+str(crossed)+"',"+str(cci)+","+str(avg)+","+str(cci_prior)+","+str(averageh)+","+str(atr)+","+str(bband_width)+","+str(bband_b)
key_arr[1] = categories.categorize_atr15(atr)
key_arr[4] = categories.categorize_cci_15(cci)
key_arr[5] = categories.categorize_cci_15_avg(avg)
key_arr[8] = categories.categorize_BBW15(bband_width)
key_arr[9] = categories.categorize_BBb15(bband_b)
#
#1 hour data
#
log.debug("next datetime for 1 hour - should be 1 hour behind current hour {}".format(datetime_1h))
bars_1h = self.get_bars_data(dataContract,"5 D","1 hour",datetime_1h)
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1h)
log.debug("bars_1h {}".format(str(bars_1h[-1])))
atr,atrprior = calculate_atr(bars_1h)
bband_width, bband_b,bband_width_prior, bband_b_prior = calculate_bbands(bars_1h)
csv_row += ","+str(cci)+","+str(avg)+","+str(atr)+","+str(bband_width)+","+str(bband_b)
csv_header += ",CCI1h,CCIA1h,ATR1h,BBW1h,BBB1h"
key_arr[2] = categories.categorize_atr1h(atr)
key_arr[6] = categories.categorize_cci_1h(avg)
key_arr[10] = categories.categorize_BBW1h(bband_width)
key_arr[11] = categories.categorize_BBb1h(bband_b)
#logged_it = self.log_value("Starting 1 hour", cci,avg,cci_prior, averageh,atr,bband_width,bband_b)
qtrtime = datetime.now()
log.debug("requesting info for the following timeframe today: nextday: ".format(datetime_1d))
bars_1d = self.get_bars_data(dataContract,"75 D","1 day",datetime_1d)
log.debug("1d min bars {}".format(str(bars_1d[-1])))
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1d)
atr, atrprior = calculate_atr(bars_1d)
bband_width, bband_b,bband_width_prior, bband_b_prior = calculate_bbands(bars_1d)
csv_row += ","+str(cci)+","+str(avg)+","+str(atr)+","+str(bband_width)+","+str(bband_b)
csv_header += ",CCI1d,CCIA1d,ATR1d,BBB1d,BBW1d"
key_arr[3] = categories.categorize_atr1d(atr)
key_arr[7] = categories.categorize_cci_1d(avg)
key_arr[12] = categories.categorize_BBW1d(bband_width)
key_arr[13] = categories.categorize_BBb1d(bband_b)
#logged_it = self.log_value("Starting 1 Day", cci,avg,cci_prior, averageh,atr,bband_width,bband_b)
qtrtime = datetime.now()
setsum = self.setupsummary(key_arr)
log.info("tradenow: {trade}".format(trade = tradenow))
#
# starting trade logic
#
# test buy
if tradenow:
log.info("Tradeing this bar {}".format(str(''.join(key_arr))," - ",''.join(key_arr[0:8])))
csv_file1 = csv.reader(open('data/ccibb.csv', "rt"), delimiter = ",")
for row1 in csv_file1:
print("ccibb row: ",row1[0],row1[13])
if ((''.join(key_arr)) == row1[0]) and row1[13] == "Y": #13 is winrisk - whether we trade or not
quantity = 2
log.info("we have a match in ccibb.csv")
log.info("found a match in CCIBB ".format(str(row1[0])))
ccibb_trade = True
if open_long or open_short:
quantity = 4
ParentOrderID = orders.buildOrders(self.ib,tradeContract,tradeAction,quantity,"ccibb_day",stoplossprice)
log.info("order placed, parentID: {}".format(ParentOrderID))
open_long = False
open_short = False
tradenow = False
status_done = self.row_results(row1,cci_trade,ccibb_trade)
break
csv_file2 = csv.reader(open('data/cci.csv', "rt"), delimiter = ",")
for row2 in csv_file2:
print("cci row: ",row2[0],row2[13])
if ((''.join(key_arr[0:8])) == row2[0]) and row2[13] == "Y":
quantity = 2
log.info("we have a match in cci.csv - tradeAction".format(tradeAction))
log.info("found a math in CCI {}".format(str(row2[0])))
if open_long or open_short:
quantity = 4
ParentOrderID = orders.buildOrders(self.ib,tradeContract,tradeAction,quantity,"cci_day",stoplossprice)
open_long = False
open_short = False
tradenow = False
status_done = self.row_results(row2,cci_trade,ccibb_trade)
break
log.info("did we find a match? If true than no {match}".format(match = tradenow))
if open_long or open_short:
quantity = 2
ParentOrderID = orders.buildOrders(self.ib,tradeContract,tradeAction,quantity,"ccibb_day",stoplossprice)
open_long =False
open_short = False
csv_row += ","+(''.join(key_arr))+","+(''.join(key_arr[0:8]))+","+str(cci_trade)+","+str(ccibb_trade)+","+str(pendinglong)+","+str(pendingshort)
csv_header += ",CCIbbKey,CCIKey,CCI Trade,CCIbbTrade,PendingLong, PendingShort"
with open('data/hist15.csv', mode='a') as hist15:
histwriter = csv.writer(hist15, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
histwriter.writerow([csv_header])
histwriter.writerow([csv_row])
tradenow = False
cci_trade = False
ccibb_trade = False
def run(self):
""" Execute the algorithm """
key_arr = ['blank','ATR15','ATR1','ATRD','CCI15','CCIA15','CCIA1h','CCIA1d','BBW15','BBb15','BBW1h','BBb1h','BBW1d','BBb1d']
tradenow = False
not_finished = True
pendingshort = False
pendinglong = False
tradenow = False
cci_trade = False
ccibb_trade = False
while not_finished:
print ("top of algo run self")
#top of logic - want to check status as we enter a new bar/hour/day/contract
crossed = False
self.app.crossover.update(crossed)
contContract, contracthours = get_contract(self)
# NEW
tradeContract = self.ib.qualifyContracts(contContract) # gives all the details of a contract so we can trade it
#print("fully qualified trading Contract: ",tradeContract)
positions = self.ib.positions()
open = self.have_position(positions)
open_today = helpers.is_open_today(contracthours)
dataContract = Contract(exchange=config.EXCHANGE, secType="FUT", localSymbol=contContract.localSymbol)
log.info("Got Contract: {}".format(dataContract.localSymbol))
self.app.contract.update(dataContract.localSymbol)
wait_time, datetime_15, datetime_1h, datetime_1d = self.define_times()
log.info("next datetime for 15 minutes - should be 15 minutes ahead of desired nextqtr{}".format(wait_time))
#
# starting the analysis section
#
self.ib.waitUntil(wait_time)
#
# 15 Minute Data
#
self.app.qtrhour.update(wait_time)
log.info("requesting info for the following timeframe today: {} ".format(wait_time))
bars_15m = self.get_bars_data(dataContract,"2 D","15 mins",datetime_15)
x = np.array(bars_15m)
log.info("15 min bars {}".format(bars_15m[-1]))
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_15m)
atr, atrprior = calculate_atr(bars_15m)
bband_width, bband_b,bband_width_prior, bband_b_prior = calculate_bbands(bars_15m)
log.info("starting 15 minutes".format(datetime.now()))
log.info("CCI: {} ".format(cci))
log.info("CCIA {} ".format(avg))
log.info("CCIP {} ".format(cci_prior))
log.info("CCIPA: {} ".format(averageh))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
if cci > avg and cci_prior < averageh:
crossed = True
print("crossed long",crossed)
tradenow = True
csv_row = "'"+str(datetime.now())+",'long'"
key_arr[0] = "long"
elif cci < avg and cci_prior > averageh:
crossed = True
tradenow = True
print("crossed short",crossed)
csv_row = "'"+str(datetime.now())+",'short'"
key_arr[0] = "short"
else:
csv_row = "'"+str(datetime.now())+",'cash'"
crossed = False
tradenow = False
print("NOT CROSSED ",crossed)
print("csv row crossed ",csv_row)
#if abs(cci - avg) > config.SPREAD:
# pending = True
csv_header = "Date,Status,Crossed,CCI15,CCIA15,CCI15P,CCIA15P,ATR15,BBw15,BBB15"
csv_row += ",'"+str(crossed)+"',"+str(cci)+","+str(avg)+","+str(cci_prior)+","+str(averageh)+","+str(atr)+","+str(bband_width)+","+str(bband_b)
print("csv row 15",csv_row)
key_arr[1] = categories.categorize_atr15(atr)
key_arr[4] = categories.categorize_cci_15(cci)
key_arr[5] = categories.categorize_cci_15_avg(avg)
key_arr[8] = categories.categorize_BBW15(bband_width)
key_arr[9] = categories.categorize_BBb15(bband_b)
stat = "check crossed status"
self.app.status1.update(stat)
self.app.crossover.update(crossed)
self.app.cci15.update(f"{cci:.02f}")
self.app.cci15_av.update(f"{avg:.02f}")
self.app.cci15p_av.update(f"{averageh:.02f}")
self.app.cci15p.update(f"{cci_prior:.02f}")
self.app.atr15.update(f"{atr:.02f}")
self.app.bband15_width.update(f"{bband_width:.04f}")
self.app.bband15_b.update(f"{bband_b:.04f}")
self.app.qtrhour.update(qtrtime)
#1 hour data
log.info("next datetime for 1 hour - should be 1 hour behind current hour {}".format(datetime_1h))
bars_1h = self.get_bars_data(dataContract,"5 D","1 hour",datetime_1h)
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1h)
log.info("bars_1h {}".format(bars_1h[-1]))
atr,atrprior = calculate_atr(bars_1h)
bband_width, bband_b,bband_width_prior, bband_b_prior = calculate_bbands(bars_1h)
csv_row += ","+str(cci)+","+str(avg)+","+str(atr)+","+str(bband_width)+","+str(bband_b)
print("csv row 1 hour ",csv_row)
csv_header += ",CCI1h,CCIA1h,ATR1h,BBW1h,BBB1h"
key_arr[2] = categories.categorize_atr1h(atr)
key_arr[6] = categories.categorize_cci_1h(avg)
key_arr[10] = categories.categorize_BBW1h(bband_width)
key_arr[11] = categories.categorize_BBb1h(bband_b)
log.info("starting 1H ")
log.info("CCI {} ".format(cci))
log.info("CCIA: {} ".format(avg))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
self.app.cci1h.update(f"{cci:.02f}")
self.app.cci1h_av.update(f"{avg:.02f}")
self.app.bband1h_b.update(f"{bband_b:.04f}")
self.app.bband1h_width.update(f"{bband_width:.04f}")
self.app.atr1h.update(f"{atr:.02f}")
log.info("requesting info for the following timeframe today: nextday: ".format(datetime_1d))
bars_1d = self.get_bars_data(dataContract,"75 D","1 day",datetime_1d)
log.info("1d min bars {}".format(bars_1d[-1]))
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1d)
atr, atrprior = calculate_atr(bars_1d)
bband_width, bband_b,bband_width_prior, bband_b_prior = calculate_bbands(bars_1d)
csv_row += ","+str(cci)+","+str(avg)+","+str(atr)+","+str(bband_width)+","+str(bband_b)
print("csv row daily ",csv_row)
csv_header += ",CCI1d,CCIA1d,ATR1d,BBB1d,BBW1d"
key_arr[3] = categories.categorize_atr1d(atr)
key_arr[7] = categories.categorize_cci_1d(avg)
key_arr[12] = categories.categorize_BBW1d(bband_width)
key_arr[13] = categories.categorize_BBb1d(bband_b)
log.info("starting 1D ")
log.info("CCIP {} ".format(cci))
log.info("CCIPA: {} ".format(avg))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
qtrtime = datetime.now()
self.app.cci1d.update(f"{cci:.02f}")
self.app.cci1d_av.update(f"{avg:.02f}")
self.app.bband1d_b.update(f"{bband_b:.04f}")
self.app.bband1d_width.update(f"{bband_width:.04f}")
self.app.atr1d.update(f"{atr:.02f}")
print("tradenow: ",tradenow)
if tradenow:
print("Tradeing this bar ",(''.join(key_arr))," - ",''.join(key_arr[0:8]))
csv_file1 = csv.reader(open('data/ccibb.csv', "rt"), delimiter = ",")
for row1 in csv_file1:
print("ccibb row: ",row1[0])
if ((''.join(key_arr)) == row1[0]):
log.info("we have a match in ccibb.csv")
print("found a match in CCIBB ",row1[0])
ccibb_trade = True
tradenow = False
status_done = self.row_results(row1,cci_trade,ccibb_trade)
break
csv_file2 = csv.reader(open('data/cci.csv', "rt"), delimiter = ",")
for row2 in csv_file2:
print("cci row: ",row2[0])
if ((''.join(key_arr[0:8])) == row2[0]):
print("we have a match in cci.csv")
print("found a math in CCI ",row2[0])
cci_trade = True
tradenow = False
status_done = self.row_results(row2,cci_trade,ccibb_trade)
break
print("did we find a match? If true than no ",tradenow)
csv_row += ","+(''.join(key_arr))+","+(''.join(key_arr[0:8]))+","+str(cci_trade)+","+str(ccibb_trade)+","+str(pendinglong)+","+str(pendingshort)
csv_header += ",CCIbbKey,CCIKey,CCI Trade,CCIbbTrade,Pending Long, Pending Short"
print("csv row right before csv write ",csv_row)
with open('data/hist15.csv', mode='a') as hist15:
histwriter = csv.writer(hist15, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
#histwriter.writerow([csv_header])
#histwriter.writerow([csv_row])
tradenow = False
cci_trade = False
ccibb_trade = False
print ("end of run self **********************************************************************************************")
def run(self):
""" Execute the algorithm """
key_arr = [
'blank', 'ATR15', 'ATR1', 'ATRD', 'CCI15', 'CCIA15', 'CCIA1h',
'CCIA1d', 'BBW15', 'BBb15', 'BBW1h', 'BBb1h', 'BBW1d', 'BBb1d'
]
tradenow = False
not_finished = True
tradenow = False
cci_trade = False
ccibb_trade = False
while not_finished:
print("top of algo run self")
crossed = False
self.app.crossover.update(crossed)
contContract = get_contract(self)
#print(contract.tradingHours.split(";"))
#open_today = helpers.is_open_today(contract)
#print("open today ",open_today)
dataContract = Contract(exchange=config.EXCHANGE,
secType="FUT",
localSymbol=contContract.localSymbol)
log.info("Got Contract: {}".format(dataContract.localSymbol))
self.app.contract.update(dataContract.localSymbol)
wait_time, datetime_15, datetime_1h, datetime_1d = self.define_times(
)
log.info(
"next datetime for 15 minutes - should be 15 minutes ahead of desired nextqtr{}"
.format(wait_time))
#
#nextqtr = datetime.now().minute + 1
#print ("we manually overwrote start time")
#print (nextqtr)
#
self.ib.waitUntil(wait_time)
# 15 Minute Data
self.app.qtrhour.update(wait_time)
log.info("requesting info for the following timeframe today: {} ".
format(wait_time))
bars_15m = self.get_bars_data(dataContract, "2 D", "15 mins",
datetime_15)
x = np.array(bars_15m)
log.info("15 min bars {}".format(bars_15m[-1]))
#sef.app. barupdateEvent_15m(baas_15m, True)
#aars_15m.updateEvent += self.app.barupdateEvent_15m
log.info("Got 15m data subscription")
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_15m)
atr, atrprior = calculate_atr(bars_15m)
bband_width, bband_b, bband_width_prior, bband_b_prior = calculate_bbands(
bars_15m)
log.info("starting 15 minutes".format(datetime.now()))
log.info("CCI: {} ".format(cci))
log.info("CCIA {} ".format(avg))
log.info("CCIP {} ".format(cci_prior))
log.info("CCIPA: {} ".format(averageh))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
#key_arr = []
if cci > cci_prior and cci_prior < cci3:
crossed = True
tradenow = True
csv_row = "'" + str(datetime.now()) + ",'long'"
key_arr[0] = "long"
elif cci < cci_prior and cci_prior > cci3:
crossed = True
tradenow = True
csv_row = "'" + str(datetime.now()) + ",'short'"
key_arr[0] = "short"
else:
csv_row = "'" + str(datetime.now()) + ",'flat'"
crossed = False
tradenow = False
csv_row += ",'" + str(crossed) + "'," + str(cci) + "," + str(
avg) + "," + str(cci_prior) + "," + str(averageh) + "," + str(
atr) + "," + str(bband_width) + "," + str(bband_b)
print(key_arr)
key_arr[1] = categories.categorize_atr15(atr)
key_arr[4] = categories.categorize_cci_15(cci)
key_arr[5] = categories.categorize_cci_15_avg(avg)
key_arr[8] = categories.categorize_BBW15(bband_width)
key_arr[9] = categories.categorize_BBb15(bband_b)
stat = "check crossed status"
#print("printing self app ********************************************")
#print(Indicator.data)
self.app.status1.update(stat)
self.app.crossover.update(crossed)
self.app.cci15.update(f"{cci:.02f}")
self.app.cci15_av.update(f"{avg:.02f}")
self.app.cci15p_av.update(f"{averageh:.02f}")
self.app.cci15p.update(f"{cci_prior:.02f}")
self.app.atr15.update(f"{atr:.02f}")
self.app.bband15_width.update(f"{bband_width:.04f}")
self.app.bband15_b.update(f"{bband_b:.04f}")
self.app.qtrhour.update(qtrtime)
#1 hour data
log.info(
"next datetime for 1 hour - should be 1 hour behind current hour {}"
.format(datetime_1h))
bars_1h = self.get_bars_data(dataContract, "5 D", "1 hour",
datetime_1h)
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1h)
log.info("bars_1h {}".format(bars_1h[-1]))
atr, atrprior = calculate_atr(bars_1h)
bband_width, bband_b, bband_width_prior, bband_b_prior = calculate_bbands(
bars_1h)
csv_row += "," + str(cci) + "," + str(avg) + "," + str(
atr) + "," + str(bband_width) + "," + str(bband_b)
key_arr[2] = categories.categorize_atr1h(atr)
key_arr[6] = categories.categorize_cci_1h(avg)
key_arr[10] = categories.categorize_BBW1h(bband_width)
key_arr[11] = categories.categorize_BBb1h(bband_b)
log.info("starting 1H ")
log.info("CCI {} ".format(cci))
log.info("CCIA: {} ".format(avg))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
self.app.cci1h.update(f"{cci:.02f}")
self.app.cci1h_av.update(f"{avg:.02f}")
self.app.bband1h_b.update(f"{bband_b:.04f}")
self.app.bband1h_width.update(f"{bband_width:.04f}")
self.app.atr1h.update(f"{atr:.02f}")
log.info(
"requesting info for the following timeframe today: nextday: ".
format(datetime_1d))
bars_1d = self.get_bars_data(dataContract, "75 D", "1 day",
datetime_1d)
log.info("1d min bars {}".format(bars_1d[-1]))
cci, avg, cci_prior, averageh, cci3 = calculate_cci(bars_1d)
atr, atrprior = calculate_atr(bars_1d)
bband_width, bband_b, bband_width_prior, bband_b_prior = calculate_bbands(
bars_1d)
csv_row += "," + str(cci) + "," + str(avg) + "," + str(
atr) + "," + str(bband_width) + "," + str(bband_b)
key_arr[3] = categories.categorize_atr1d(atr)
key_arr[7] = categories.categorize_cci_1d(avg)
key_arr[12] = categories.categorize_BBW1d(bband_width)
key_arr[13] = categories.categorize_BBb1d(bband_b)
log.info("starting 1H ")
log.info("starting 1D ")
log.info("CCIP {} ".format(cci))
log.info("CCIPA: {} ".format(avg))
log.info("ATR: {} ".format(atr))
log.info("bband w: {} ".format(bband_width))
log.info("bband p: {} ".format(bband_b))
qtrtime = datetime.now()
qtrtime = datetime.now()
self.app.cci1d.update(f"{cci:.02f}")
self.app.cci1d_av.update(f"{avg:.02f}")
self.app.bband1d_b.update(f"{bband_b:.04f}")
self.app.bband1d_width.update(f"{bband_width:.04f}")
self.app.atr1d.update(f"{atr:.02f}")
if tradenow:
csv_file = csv.reader(open('data/ccibb.csv', "rt"),
delimiter="'")
for row in csv_file:
if (''.join(key_arr)) == row[0]:
print("we have a match in ccibb.csv")
print("found a match in CCIBB ", row)
status_done = self.row_results(self, row)
ccibb_trade = True
csv_file = csv.reader(open('data/cci.csv', "rt"),
delimiter="'")
for row in csv_file:
if (''.join(key_arr[0:8])) == row[0]:
print("we have a match in cci.csv")
print("found a math in CCI ", row)
status_done = self.row_results(self, row)
cci_trade = True
csv_row += "," + (''.join(key_arr)) + "," + (''.join(
key_arr[0:8])) + "," + str(ccibb_trade) + "," + str(
ccibb_trade)
with open('data/hist15.csv', mode='a') as hist15:
histwriter = csv.writer(hist15,
delimiter=',',
quotechar='"',
quoting=csv.QUOTE_MINIMAL)
histwriter.writerow([csv_row])
tradenow = False
cci_trade = False
ccibb_trade = False
print(
"end of run self **********************************************************************************************"
)
import categories test = "long" test += categories.categorize_cci_15(99) print(test)
