def do_math_for_single_stock(all_simulations, moving_day_average, number_of_days, stock, mode):
print('Mode: ' + mode)
net_profits = []
# The index for each day. We start it at day 5.
todays_index = len(stock.get_data()) - 0 - 1 - 4 - (len(stock.get_data()) - number_of_days)
tomorrows_index = len(stock.get_data()) - 0 - 1 - 5 - (len(stock.get_data()) - number_of_days)
yesterdays_index = len(stock.get_data()) - 0 - 1 - 3 - (len(stock.get_data()) - number_of_days)
counter_index = 0
while tomorrows_index != 0:
debug.logger.log('Doing math for day: ' + str(stock.get_data()[todays_index].get_date()))
#debug.logger.log('Tomorrow is: ' + str(stock.get_data()[tomorrows_index].get_date()))
# Calculate the moving average.
close_moving_average = 0.0
for i in range(0, moving_day_average):
current_index = todays_index + i
close_moving_average += stock.get_data()[current_index].get_close()
debug.logger.log(stock.get_data()[current_index].to_string())
close_moving_average /= 5
debug.logger.log('The moving average is: ' + str(close_moving_average))
if mode == 'LONG':
# Check if today's close is above the moving average. If it is then we do the math.
debug.logger.log('I am checking if today\'s close is above the moving average.')
if stock.get_data()[todays_index].get_close() > close_moving_average:
debug.logger.log('Today\'s close is larger than the close moving average. Doing the math...')
do_sub_math_for_single_day(net_profits, yesterdays_index, todays_index, tomorrows_index, stock, mode)
elif mode == 'SHORT':
debug.logger.log('I am checking if today\'s close is below the moving average.')
# Check if today's close is below the moving average. If it is then we do the math.
if stock.get_data()[todays_index].get_close() < close_moving_average:
debug.logger.log('Today\'s close is below the moving average. Doing the math...')
do_sub_math_for_single_day(net_profits, yesterdays_index, todays_index, tomorrows_index, stock, mode)
else:
if stock.get_data()[todays_index].get_close() > close_moving_average:
do_sub_math_for_single_day(net_profits, yesterdays_index, todays_index, tomorrows_index, stock, 'LONG')
elif stock.get_data()[todays_index].get_close() < close_moving_average:
do_sub_math_for_single_day(net_profits, yesterdays_index, todays_index, tomorrows_index, stock, 'SHORT')
counter_index += 1
todays_index = len(stock.get_data()) - 0 - 1 - 4 - counter_index - (len(stock.get_data()) - number_of_days)
tomorrows_index = len(stock.get_data()) - 0 - 1 - 5 - counter_index - (len(stock.get_data()) - number_of_days)
yesterdays_index = len(stock.get_data()) - 0 - 1 - 3 - counter_index - (len(stock.get_data()) - number_of_days)
# Print out % profits.
if len(net_profits) != 0:
print('Net profits: ' + str(stock_math.average_fast(net_profits)))
if len(net_profits) != 0:
all_simulations.attempt_to_add_best(stock.get_name(), stock_math.average_fast(net_profits))
def do_sub_math_for_single_day(net_profits, yesterdays_index, todays_index, tomorrows_index, stock, mode):
# Calculate a list of the percentage difference between yesterday's close price and today's low.
percentage_difference_between_yesterdays_close_and_todays_low = []
percentage_difference_between_yesterdays_close_and_todays_high = []
for i in range(0, 5):
current_index = len(stock.get_data()) - i - 1
past_index = len(stock.get_data()) - i - 2
local_low_calculation = stock_math.percentage_difference_fast(stock.get_data()[past_index].get_close(), stock.get_data()[current_index].get_low())
local_high_calculation = stock_math.percentage_difference_fast(stock.get_data()[past_index].get_close(), stock.get_data()[current_index].get_high())
percentage_difference_between_yesterdays_close_and_todays_low.append(local_low_calculation)
percentage_difference_between_yesterdays_close_and_todays_high.append(local_high_calculation)
average_for_low = stock_math.average_fast(percentage_difference_between_yesterdays_close_and_todays_low)
average_for_high = stock_math.average_fast(percentage_difference_between_yesterdays_close_and_todays_high)
#print('Close moving average: ' + '\t' + str(close_moving_average))
buy_price = stock_math.buy_price_fast(average_for_low, stock.get_data()[todays_index].get_close())
short_price = stock_math.short_price_fast(average_for_high, stock.get_data()[todays_index].get_close())
debug.logger.log('Buy price: ' + str(buy_price))
debug.logger.log('Short price: ' + str(short_price))
if mode == 'LONG':
# If the buy price is above tomorrow's low, then we buy the stock tomorrow.
if buy_price > stock.get_data()[tomorrows_index].get_low():
#net_profits.append(stock_math.generic_percenatage_difference(buy_price, stock.get_data()[tomorrows_index].get_close()))
local_net_profit = stock_math.generic_percenatage_difference(buy_price, stock.get_data()[tomorrows_index].get_close())
if local_net_profit <= -4.0:
net_profits.append(-4.0)
else:
net_profits.append(local_net_profit)
elif mode == 'SHORT':
# If the short price is below tomorrow's
#local_net_profit = stock_math.generic_percenatage_difference(stock.get_data()[tomorrows_index].get_close(), short_price)
if short_price < stock.get_data()[tomorrows_index].get_high():
local_net_profit = stock_math.generic_percenatage_difference(stock.get_data()[tomorrows_index].get_close(), short_price)
if local_net_profit <= -4.0:
net_profits.append(-4.0)
else:
net_profits.append(local_net_profit)
else:
if buy_price > stock.get_data()[tomorrows_index].get_low():
local_net_profit = stock_math.generic_percenatage_difference(buy_price, stock.get_data()[tomorrows_index].get_close())
if local_net_profit <= -4.0:
net_profits.append(-4.0)
else:
net_profits.append(local_net_profit)
elif short_price < stock.get_data()[tomorrows_index].get_high():
local_net_profit = stock_math.generic_percenatage_difference(stock.get_data()[tomorrows_index].get_close(), short_price)
if local_net_profit <= 4.0:
net_profits.append(-4.0)
else:
net_profits.append(stock_math.generic_percenatage_difference(stock.get_data()[tomorrows_index].get_close(), short_price))
