def next(self):
prices = self.data.Close
if len(self.data.Volume) > 66:
last_price = prices[-1]
if self.buy_price == 0 and Ticker.isStockOut(prices):
self.buy_price = last_price
self.buy()
if self.buy_price != 0 and (TakeProfit.takeProfit(
5, last_price, self.buy_price)
or CutLoss.shouldCutLossByPercent(
8, last_price, self.buy_price)):
self.position.close()
self.buy_price = 0
def getResult(ticker_id, np_data):
# rand_from = int(np_data.size / 4)
# rand_to = int(np_data.size / 3)
# look_back = random.randint(rand_from,rand_to) # days
# price_data = np_data[:, close_col_index]
# print(price_data)
# print(len(price_data))
# return
f = open("tracking-history.log", "w+")
close_col_index = 4
date_col_index = 0
sold = True
test_from = 10
test_to = len(np_data) - 5
index = 0
sold_price = 0
commission = 0
train_price = np.array([])
for data in np_data:
index = index + 1
train_price = np.append(train_price, data[close_col_index])
if test_from < index < test_to:
copy_data = np_data.copy()
test_prices = copy_data[index:]
curr_price = data[close_col_index]
cut_loss_price = curr_price * 0.96
if Ticker.isStockOut(train_price):
buy_log = "Mua co phieu " + ticker_id + " o gia: " + str(curr_price) + " ngay " + data[
date_col_index] + "\n"
f.write(buy_log)
# f.write("--" + str(index) + "\n")
for np_test_price in test_prices:
test_price = np_test_price[close_col_index]
if test_price > curr_price:
cut_loss_price = test_price * 0.96
if test_price < cut_loss_price: # Co cut loss
sold_price = test_price
commission = sold_price - curr_price
sold_log = "Ban co phieu " + ticker_id + " o gia: " + str(sold_price) + " ngay " + \
np_test_price[date_col_index] + "\r\n"
f.write(sold_log)
# f.write("---" + str(index) + "\n")
break
f.close()
print("Commission: " + str(commission))