def start():
with open("white_list.txt", 'r') as f:
sp500 = f.read()
sp500_list = sp500.split(",")
# Different strategies initiated with a number
if sys.argv[1] == '1':
earnings_map = Strategy.AM_strategy1(pull_list=sp500_list)
elif sys.argv[1] == '2':
if len(sys.argv) > 2:
pull_list = Strategy.AM_PM_Change_Average(pull_list=[sys.argv[2]], additional_pull=True)
else:
earnings_map = Strategy.AM_PM_Change_Average(pull_list=sp500_list)
def start(arg=None):
if arg:
symbol = arg
else:
symbol = sys.argv[1]
try:
current_price = float(sys.argv[2])
except:
# Code for gathering the latest day
latest_day = date.today() - timedelta(days=1)
if latest_day.strftime('%A') == 'Saturday':
latest_day = latest_day - timedelta(days=3)
elif latest_day.strftime('%A') == 'Sunday':
latest_day = latest_day - timedelta(days=3)
latest_day_str = latest_day.strftime('%Y-%m-%d')
day_before_latest = latest_day - timedelta(days=1)
if day_before_latest.strftime('%A') == "Sunday":
day_before_latest = day_before_latest - timedelta(days=2)
day_before_latest_str = day_before_latest.strftime('%Y-%m-%d')
print(day_before_latest_str)
print(latest_day_str)
symbol_yahoo_finance_interactor = YahooFinancials(symbol)
earnings_days_data = symbol_yahoo_finance_interactor.get_historical_price_data(
day_before_latest_str, latest_day_str, 'daily')
print(earnings_days_data)
try:
current_price = earnings_days_data[symbol]['prices'][0]['close']
except:
print(
'Was not able to pull price from Yahoo Finance for symbol %s' %
symbol)
try:
symbol_file = os.getcwd(
) + "/earnings_call_difference_data/%s.csv" % symbol
csv_file = open(symbol_file, "r")
except:
import Strategy
pull_list = Strategy.AM_PM_Change_Average(pull_list=[symbol],
additional_pull=True)
symbol_file = os.getcwd(
) + "/earnings_call_difference_data/%s.csv" % symbol
try:
csv_file = open(symbol_file, "r")
except:
print("No data for earnings calls could be called for %s" % symbol)
return None
lines = csv_file.readlines()
print(symbol)
absolute_diff = float(lines[7].rstrip().split(',')[1][:-1])
positive_diff = float(lines[8].rstrip().split(',')[1][:-1])
negative_diff = float(lines[9].rstrip().split(',')[1][:-1])
earnings_date_list = lines[0].rstrip().split(',')
diff_list = lines[3].rstrip().split(',')
fin_string = ""
fin_string += "-----------------------------------------\n"
for i in range(1, len(lines[0])):
if diff_list[i] == "":
break
fin_string += "Earnings Date %s: %f%%\n" % (earnings_date_list[i],
float(diff_list[i][:-1]))
fin_string += "-----------------------------------------\n"
fin_string += "Chance of Rising: %s\n" % lines[4].split(',')[1].rstrip()
fin_string += "Chance of Falling: %s\n" % lines[5].split(',')[1].rstrip()
fin_string += "-----------------------------------------\n"
fin_string += "Absolute Difference Average: %f%%\n" % absolute_diff
fin_string += "Positive Difference Average: %f%%\n" % positive_diff
fin_string += "Negative Difference Average: %f%%\n" % negative_diff
fin_string += "-----------------------------------------\n"
fin_string += "Current Price: %f\n" % current_price
lower_strike = (round(
(current_price -
((abs(negative_diff) / 100) * current_price)) * 2)) / 2
higher_strike = (round(
(current_price + ((positive_diff / 100) * current_price)) * 2)) / 2
fin_string += "Recommended Lower Strike: %f\n" % lower_strike
fin_string += "Recommended Higher Strike: %f\n" % higher_strike
fin_string += "-----------------------------------------\n"
csv_file.close()
print(fin_string)
return fin_string