def findLongCall(symbol, expirations_list):
long_calls = []
#Find long call
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
for option_item in options:
option = util.gatherOptionData(option_item)
if (option['bid'] is None or option['ask'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
option['premium'] = premium
delta = -999
if ('delta' in option):
delta = option['delta']
if (option["type"] == "put" or premium >= 5
or option['volume'] == 0 or delta < .5
or (option['ask'] - option['bid']) >= MAX_BID_ASK_SPREAD):
continue
#Find Long Call
if (option["type"] == "call"):
long_calls.append(option)
return long_calls
def findCoveredCalls(ListOfSymbols):
matching_options = []
for symbol in ListOfSymbols:
last_price = api.getLastStockPrice(symbol)
expirations_list = util.listOfLimitedExpirations(symbol, 20, 50)
numOptions = 0
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
for option_item in options:
option = util.gatherOptionData(option_item)
if (option['strike'] <= last_price):
continue
premium = round((option['bid'] + option['ask']) / 2, 2)
profit = round(100 *
((option['strike'] - last_price) + premium))
debit = round((100 * last_price) - (100 * premium))
if (option['bid'] > 0 and debit <= 1000
and option['type'] == "call" and last_price <= 15
and option['volume'] > 0):
if (numOptions == 0):
matching_options.append(
f"Symbol: {symbol}, Last: {last_price}")
numOptions += 1
option_output = '{} {}, {}, BID:{}, ASK:{}, {}, {}(D), Premium: {}, Debit: {}, Profit: {}' \
.format(option['type'],
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['open_int'],
option['delta'],
premium,
debit,
profit
)
#Print the screen when a match is found
print(f"Found: {option_output}")
matching_options.append(option_output)
return matching_options
def findShortCall(long_call):
symbol = long_call["symbol"]
long_strike = long_call["strike"]
long_exp = long_call["expiration"]
long_prem = long_call["premium"]
expirations_list = util.listOfLimitedExpirations(symbol, 7, 60)
long_delta = long_call["delta"]
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
for option_item in options:
if (option_item['expiration_type'] == "weeklys"):
break
option = util.gatherOptionData(option_item)
if (option['bid'] is None or option['ask'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
delta = -999
if ('delta' in option):
delta = option['delta']
if (option["type"] == "put" or premium <= .3
or option['volume'] == 0 or delta > .3
or (option['ask'] - option['bid']) >= MAX_BID_ASK_SPREAD):
continue
if (option["type"] == "call"):
net_debit = round(long_prem - premium, 2)
width_of_strike = option["strike"] - long_strike
if (net_debit > 2 or (width_of_strike * .75) <= net_debit):
continue
option_output = util.shortCallOptionOutput(option)
print("---")
print(
f"PMCC - L: {long_strike} | {long_exp} | {long_delta}(D)")
print(f"PMCC - S: {option_output}")
print(f"Net Debit: {net_debit} Width: {width_of_strike}")
def findWheels(ListOfSymbols):
matching_options = []
for symbol in ListOfSymbols:
print(f"Processing {symbol}...")
expirations_list = util.listOfLimitedExpirations(symbol, 1, 15)
numOptions = 0
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
for option_item in options:
option = util.gatherOptionData(option_item)
if (option['bid'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
if ('delta' in option):
delta = option['delta']
if (option['type'] == "put" and option['bid'] > 0
and delta >= -.16 and premium >= .19 and
(option['ask'] - option['bid']) <= MAX_BID_ASK_SPREAD
and option['volume'] > 0):
option_output = '{}, {}, BID:{}, ASK:{}, {}, {}(D), Premium: {}'\
.format(
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['volume'],
option['delta'],
premium)
if (numOptions == 0):
matching_options.append(f"Symbol: {symbol}")
numOptions += 1
#Print the screen when a match is found
print(f"Found: {option_output} - ({datetime.now()})")
return matching_options
def findPutSpreads(ListOfSymbols):
#Options criteria
MIN_VOLUME = 1
MAX_BID_ASK_SPREAD = .15
MAX_STRIKES_WIDTH = 5
MAX_DELTA = -.2
MIN_PREMIUM = .21
matching_options = []
data_frame = []
for symbol in ListOfSymbols:
print(f"Processing {symbol}...")
expirations_list = util.listOfLimitedExpirations(symbol, 21, 47)
numOptions = 0
for expiration in expirations_list:
#This is temporary... add actual dates later
if (expiration == "2020-12-08"):
continue
options = api.getOptionsChain(symbol, expiration)
prev_option_strike = 0
prev_option_prem = 0
for option_item in options:
#Ignore weeklys?
if (option_item['expiration_type'] == "weeklys"):
break
option = util.gatherOptionData(option_item)
if (option['bid'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
#Figure out net credit from credit spread
net_credit = round((premium - prev_option_prem), 2)
if ('delta' in option):
delta = option['delta']
delta = round(delta, 2)
#Criteria here
if (option['type'] == "put" and option['bid'] > 0.0
and premium >= MIN_PREMIUM and delta >= MAX_DELTA and
(option['ask'] - option['bid']) <= MAX_BID_ASK_SPREAD
and option['volume'] > MIN_VOLUME):
option_output = '{}, {}, BID:{}, ASK:{}, {}, {}(D), Premium: {}'\
.format(
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['volume'],
delta,
premium)
if (numOptions == 0):
matching_options.append(f"Symbol: {symbol}")
numOptions += 1
#Mark a strike where the width between the current strike and the previous strike meets the criteria
if (net_credit >= MIN_PREMIUM and prev_option_prem > 0
and option['strike'] - prev_option_strike <=
MAX_STRIKES_WIDTH):
option_output = option_output + " <<<<<< "
option_output = option_output + f"{net_credit}"
data_frame.append([
symbol, option['expiration'], option['strike'],
option['bid'], option['ask'], option['volume'],
delta, premium, net_credit
])
#Print the screen when a match is found
print(f"Found: {option_output} - ({datetime.now()})")
#matching_options.append(option_output)
if (option['type'] == "put"):
prev_option_prem = premium
prev_option_strike = option['strike']
panda_files.exportToFile(data_frame, "output_spreads.csv")
#print(data_frame)
return matching_options
def findPutSpreads(ListOfSymbols):
#Options criteria
MIN_VOLUME = 1
MAX_BID_ASK_SPREAD = .15
MAX_STRIKES_WIDTH = 5
DELTA = -.2
MIN_PREMIUM = .29
data_frame = []
for symbol in ListOfSymbols:
print(f"Processing {symbol}...")
expirations_list = util.listOfLimitedExpirations(symbol, 21, 47)
#Try hard-coded expirations for faster processing
#expirations_list = ["2021-02-19"]
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
prev_option_strike = 0
prev_option_prem = 0
for option_item in options:
#Ignore weeklys?
if (option_item['expiration_type'] == "weeklys"):
break
option = util.gatherOptionData(option_item)
if (option['bid'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
#Figure out net credit from credit spread
net_credit = round((premium - prev_option_prem), 2)
if ('delta' in option):
delta = option['delta']
delta = round(delta, 2)
#Criteria here
if (option['type'] == "put" and option['bid'] > 0.0
and premium >= MIN_PREMIUM and delta >= DELTA and
(option['ask'] - option['bid']) <= MAX_BID_ASK_SPREAD
and option['volume'] > MIN_VOLUME):
option_output = '{}, {}, BID:{}, ASK:{}, {}, {}(D), Premium: {}'\
.format(
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['volume'],
delta,
premium)
#Mark a strike where the width between the current strike and the previous strike meets the criteria
if (net_credit >= MIN_PREMIUM and prev_option_prem > 0
and option['strike'] - prev_option_strike <=
MAX_STRIKES_WIDTH):
option_output = option_output + " <<<<<< "
option_output = option_output + f"{net_credit}"
data_frame.append([
symbol, option['expiration'], option['strike'],
option['bid'], option['ask'], option['volume'],
delta, premium, net_credit,
util.getTimeStamp()
])
#Print the screen when a match is found
print(
f"Found: {option_output} - ({util.getTimeStamp()})"
)
if (option['type'] == "put"):
prev_option_prem = premium
prev_option_strike = option['strike']
panda_files.exportToFile(data_frame, "output_spreads.csv")
if (config.REMOTE):
panda_files.exportToWeb(data_frame, "output_spreads")
panda_files.exportToJson(data_frame, "output_spreads")
def findWheels(ListOfSymbols):
#filename_out = "output_{}.txt".format(config.STRATEGY)
MAX_BID_ASK_SPREAD = .10
MIN_PRICE = 10
MAX_PRICE = 20
MIN_PREM = .2
MAX_DELTA = -.16
matching_options = []
data_frame = []
for symbol in ListOfSymbols:
print(f"Processing {symbol}...")
last_price = api.getLastStockPrice(symbol)
if (last_price <= MIN_PRICE or last_price >= MAX_PRICE):
continue
expirations_list = util.listOfLimitedExpirations(symbol,30,45)
numOptions = 0
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
for option_item in options:
option = util.gatherOptionData(option_item)
if (option['bid'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2,2)
if ('delta' in option):
delta = option['delta']
if (option['type'] == "put"
and option['bid'] > 0
and delta >= MAX_DELTA
and premium >= MIN_PREM
and (option['ask'] - option['bid']) <= MAX_BID_ASK_SPREAD
and option['volume'] > 0
):
option_output = '{}, {}, BID:{}, ASK:{}, {}, {}(D), Premium: {}'\
.format(
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['volume'],
option['delta'],
premium)
if (numOptions == 0):
matching_options.append(f"Symbol: {symbol}")
numOptions += 1
#matching_options.append(f"Wheel: {option_output} - ({datetime.now()})")
#line = f"Wheel: {symbol} {option_output} - ({datetime.now()})"
#files.appendLineToFile(line, filename_out)
#Print the screen when a match is found
print(f"Wheel: {option_output} - ({datetime.now()})")
data_frame.append([symbol,
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['volume'],
delta,
premium,
""])
panda_files.exportToFile(data_frame, "output_wheels.csv")
return ""
def findPutSpreads(ListOfSymbols):
matching_options = []
for symbol in ListOfSymbols:
print(f"Processing {symbol}...")
expirations_list = util.listOfLimitedExpirations(symbol, 20, 50)
numOptions = 0
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
prev_option_strike = 0
prev_option_prem = 0
for option_item in options:
#Ignore weeklys?
if (option_item['expiration_type'] == "weeklys"):
break
option = util.gatherOptionData(option_item)
if (option['bid'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
#Figure out net credit from credit spread
net_credit = round((premium - prev_option_prem), 2)
if ('delta' in option):
delta = option['delta']
#Criteria here
if (option['type'] == "put" and option['bid'] > 0.0
and premium >= MIN_PREMIUM and delta >= MAX_DELTA and
(option['ask'] - option['bid']) <= MAX_BID_ASK_SPREAD
and option['volume'] > MIN_VOLUME):
option_output = '{}, {}, BID:{}, ASK:{}, {}, {}(D), Premium: {}'\
.format(
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['volume'],
option['delta'],
premium)
if (numOptions == 0):
matching_options.append(f"Symbol: {symbol}")
numOptions += 1
#Mark a strike where the width between the current strike and the previous strike meets the criteria
if (net_credit >= MIN_PREMIUM and prev_option_prem > 0
and option['strike'] - prev_option_strike <=
MAX_STRIKES_WIDTH):
option_output = option_output + " <<<<<< "
option_output = option_output + f"{net_credit}"
#Print the screen when a match is found
print(f"Found: {option_output} - ({datetime.now()})")
matching_options.append(option_output)
if (option['type'] == "put"):
prev_option_prem = premium
prev_option_strike = option['strike']
return matching_options
def findHigherRiskCreditSpreads(ListOfSymbols):
for symbol in ListOfSymbols:
expirations_list = util.listOfLimitedExpirations(symbol, 0, 90)
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
cheapest_option = 0
highest_premium = 0
for option_item in options:
option = util.gatherOptionData(option_item)
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
if ('delta' in option):
delta = option['delta']
#Criteria
if (option['type'] == "put" and option['open_int'] > 0
and option['bid'] > 0.0):
if (cheapest_option == 0):
cheapest_option = option
cheapest_option['premium'] = premium
if (option['type'] == "put" and option['bid'] > 0.0
and option['volume'] > MIN_VOLUME and delta >= -.16):
highest_premium = option
highest_premium['premium'] = premium
if (cheapest_option == 0):
continue
if (highest_premium == 0):
continue
### OUTPUT
high_spread = highest_premium['ask'] - highest_premium['bid']
net = round(
highest_premium['premium'] - cheapest_option['premium'], 2)
max_loss = (
(highest_premium['strike'] - cheapest_option['strike']) - net)
if (max_loss > 0 and net > 0):
risk = round(max_loss / net, 2)
#Only print the options worth our while
if (net >= .3 and max_loss <= 8 and high_spread <= .15):
#Print LONG option
output = 'Buy: {}, {}, {}'\
.format(
cheapest_option['expiration'],
cheapest_option['strike'],
cheapest_option['premium']
)
print(f"{symbol} {output}")
#Print SHORT option
output = 'Sell: {}, {}, {}'\
.format(
highest_premium['expiration'],
highest_premium['strike'],
highest_premium['premium']
)
print(f"{symbol} {output}")
#Print net profit
print(f"Net: {net}")
#Print Max loss
print(f"Max Loss: {max_loss}")
print(f"Risk: {risk}")
print("--")
def findWheels(ListOfSymbols, minDays, maxDays):
MAX_BID_ASK_SPREAD = .15
MIN_PRICE = 10
MAX_PRICE = 70
MIN_PREM = .30
MAX_DELTA = -.2
matching_options = []
data_frame = []
for symbol in ListOfSymbols:
print(f"Processing {symbol}...")
last_price = api.getLastStockPrice(symbol)
if (last_price <= MIN_PRICE or last_price >= MAX_PRICE):
continue
expirations_list = util.listOfLimitedExpirations(
symbol, minDays, maxDays)
numOptions = 0
for expiration in expirations_list:
options = api.getOptionsChain(symbol, expiration)
for option_item in options:
option = util.gatherOptionData(option_item)
if (option['bid'] is None or option['ask'] is None):
continue
#Estimated premium (mid price)
premium = round((option['bid'] + option['ask']) / 2, 2)
delta = -999
if ('delta' in option):
delta = option['delta']
if (option['type'] == "put" and option['bid'] > 0
and delta >= MAX_DELTA and premium >= MIN_PREM and
(option['ask'] - option['bid']) <= MAX_BID_ASK_SPREAD
and option['volume'] > 0):
option_output = '{}, {}, BID:{}, ASK:{}, {}, {}(D), Premium: {}'\
.format(
option['expiration'],
option['strike'],
option['bid'],
option['ask'],
option['volume'],
delta,
premium)
if (numOptions == 0):
matching_options.append(f"Symbol: {symbol}")
numOptions += 1
#Print the screen when a match is found
print(f"Wheel: {option_output} - ({util.getTimeStamp()})")
data_frame.append([
symbol, option['expiration'], option['strike'],
option['bid'], option['ask'], option['volume'], delta,
premium, "",
util.getTimeStamp()
])
panda_files.exportToFile(data_frame, "output_wheels.csv")
if (config.REMOTE):
panda_files.exportToWeb(data_frame, "output_wheels")
panda_files.exportToJson(data_frame, "output_wheels")
return ""