class Strategy(object):
def __init__(self, balance, log=False, commission=.0002, flat_rate=8):
self.portfolio = Portfolio(balance, commission, flat_rate)
self._log = log
self._today_data = None
self.day = 0
def run(self, data_stream):
for i in range(data_stream.shape[1]):
self._today_data = data_stream.iloc[:, i, :]
self.observe_datum(data_stream.iloc[:, i, :])
self.act()
self.day += 1
def observe_datum(self, datum):
raise NotImplementedError
def log(self, string):
if self._log:
print(string)
def liquidate(self):
for ticker in self.portfolio.tickers():
self.sell_max(ticker)
def act(self):
raise NotImplementedError
def price(self, tickers):
return self._today_data['Adj Close'][tickers]
def value(self, correct=True):
datum = self._today_data
return self.portfolio.value(datum, correct)
def sell(self, ticker, shares=1):
self.portfolio.sell(ticker, self.price(ticker), shares)
def sell_max(self, ticker):
self.portfolio.sell_max(ticker, self.price(ticker))
def buy(self, ticker, shares=1):
self.portfolio.buy(ticker, self.price(ticker), shares)
def buy_max(self, ticker, weight=1.):
self.portfolio.buy_max(ticker, self.price(ticker), weight)
def batch_buy(self, tickers, weights):
if type(weights) is dict:
weights = [weights[ticker] for ticker in tickers]
if sum(weights) > 1:
weights = [w / sum(weights) for w in weights]
self.portfolio.batch_buy(tickers, self.price(tickers), weights)
class Strategy(object):
def __init__(self, balance, log=False, commission=.0002, flat_rate=8):
self.portfolio = Portfolio(balance, commission, flat_rate)
self._log = log
self._today_data = None
self.day = 0
def run(self, data_stream):
for i in range(data_stream.shape[1]):
self._today_data = data_stream.iloc[:, i, :]
self.observe_datum(data_stream.iloc[:, i, :])
self.act()
self.day += 1
def observe_datum(self, datum):
raise NotImplementedError
def log(self, string):
if self._log:
print(string)
def liquidate(self):
for ticker in self.portfolio.tickers():
self.sell_max(ticker)
def act(self):
raise NotImplementedError
def price(self, tickers):
return self._today_data['Adj Close'][tickers]
def value(self, correct=True):
datum = self._today_data
return self.portfolio.value(datum, correct)
def sell(self, ticker, shares=1):
self.portfolio.sell(ticker, self.price(ticker), shares)
def sell_max(self, ticker):
self.portfolio.sell_max(ticker, self.price(ticker))
def buy(self, ticker, shares=1):
self.portfolio.buy(ticker, self.price(ticker), shares)
def buy_max(self, ticker, weight=1.):
self.portfolio.buy_max(ticker, self.price(ticker), weight)
def batch_buy(self, tickers, weights):
if type(weights) is dict:
weights = [weights[ticker] for ticker in tickers]
if sum(weights) > 1:
weights = [w / sum(weights) for w in weights]
self.portfolio.batch_buy(tickers, self.price(tickers), weights)
class StockAnalyzer:
def __init__(self, stock):
self.stock = stock
self.time_series = TimeSeries('R6XCN2331MT9VVZM')
self.stock_candles = []
#self.highest_price = []
self.account = Portfolio(self.stock)
#self.minimum_stock_price = 0
def get_stock_candle_info(self, stock_candle):
open_price, close_price, high_price, low_price = 0, 0, 0, 0
stock_info = str(stock_candle).split(", ")
#print(stock_info)
for i in range(len(stock_info)):
stock_info[i] = stock_info[i].replace("'", "")
if i == 0:
open_cost = stock_info[i].split(": ")
open_price = float(open_cost[1])
#print(open_price)
elif i == 1:
high = stock_info[i].split(": ")
high_price = float(high[1])
elif i == 2:
low = stock_info[i].split(": ")
low_price = float(low[1])
elif i == 3:
close = stock_info[i].split(": ")
close_price = float(close[1])
return [open_price, close_price, high_price, low_price]
def stock_json(self, stock_candle, stock_trade, trade_method):
json_string = {
"Time": stock_candle[0],
"Trading": stock_trade,
"Method": trade_method,
"Close": stock_candle[1][1],
"Open": stock_candle[1][0],
"High": stock_candle[1][2],
"Low": stock_candle[1][3]
}
return json_string
def write_json(self, data, filename='trading.json'):
with open(filename, 'w') as f:
json.dump(data, f, indent=4)
def create_json(self, filename='trading.json'):
with open(filename, 'w') as f:
data = {"Transcript": []}
json.dump(data, f, indent=4)
def get_latest_date(self, first_stock_call):
return str(first_stock_call)[2:12]
def selling_stock(self, candle_trend, transcript):
self.account.sell(self.final_price())
json_string = self.stock_json(self.stock_candles[0], candle_trend,
"Should Sell")
transcript.append(json_string)
def buying_stock(self, candle_trend, transcript):
self.account.buy(self.final_price())
json_string = self.stock_json(self.stock_candles[0], candle_trend,
"Should Buy")
transcript.append(json_string)
def amount_of_stock_intervals(self, stock_intervals):
stock_interval_amount = 0
for stock_interval in range(len(stock_intervals)):
if self.get_latest_date(
stock_intervals[0]) in stock_intervals[stock_interval]:
stock_interval_amount += 1
return stock_interval_amount
def start_and_end_of_intervals(self, stock_intervals):
start_found = False
end_found = False
stock_interval_position = 0
start_interval = 0
end_interval = 0
stock_interval_amount = self.amount_of_stock_intervals(stock_intervals)
while end_found is False and stock_interval_position <= stock_interval_amount:
if self.get_latest_date(
stock_intervals[0]
) in stock_intervals[stock_interval_position]:
if int(stock_intervals[stock_interval_position][12:14]) <= 15:
end_found = True
end_interval = stock_interval_position
stock_interval_position += 1
while start_found is False and stock_interval_position <= stock_interval_amount and end_found is True:
if self.get_latest_date(
stock_intervals[0]
) in stock_intervals[stock_interval_position]:
if int(stock_intervals[stock_interval_position][12:14]) <= 8:
start_found = True
start_interval = stock_interval_position
stock_interval_position += 1
return start_interval, end_interval
def get_time(self):
current_dt = datetime.datetime.now()
date = str(current_dt).split(" ")
final_time = date[1].rsplit(":", 1)
return final_time[0]
def final_price(self):
return self.stock_candles[0][1][1]
def check_stock(self):
try:
stock_data, stock_meta = TimeSeries(
'R6XCN2331MT9VVZM').get_intraday(symbol=self.stock,
interval='1min',
outputsize='compact')
return True
except:
return False
def realtime_candle_trends(self):
stock_analysis = StockCandlesAnalysis()
self.create_json()
with open('trading.json') as json_file:
data = json.load(json_file)
transcript = data['Transcript']
current_time = self.get_time().split(":")
bought_price = 0
while (9 <= int(current_time[0]) <= 15):
stock_data, stock_meta = self.time_series.get_intraday(
symbol=self.stock, interval='1min', outputsize='compact')
stock_intervals = str(stock_data).split("}, ")
stock_intervals[0] = stock_intervals[0][1:]
#print(stock_intervals)
#print(stock_interval_amount)
trading = False
stock_call = str(stock_intervals[0]).split(': ', 1)
info = self.get_stock_candle_info(stock_call[1])
stock_date = stock_call[0].replace("{", "")
self.stock_candles.insert(0, [stock_date, info])
if len(self.stock_candles) > 5:
if trading:
if stock_analysis.bearish_engulfing(self.stock_candles) and bought_price < \
self.stock_candles[0][1][1]:
self.selling_stock("Bearish Engulfing", transcript)
trading = False
elif stock_analysis.bearish_evening(self.stock_candles) and bought_price < \
self.stock_candles[0][1][1]:
self.selling_stock("Bearish Evening", transcript)
trading = False
elif stock_analysis.bearish_harami(self.stock_candles) and bought_price < \
self.stock_candles[0][1][1]:
self.selling_stock("Bearish Harami", transcript)
trading = False
elif stock_analysis.bearish_rising_three(self.stock_candles) and bought_price < \
self.stock_candles[0][1][1]:
self.selling_stock("Bearish Rising Three",
transcript)
trading = False
else:
if stock_analysis.bullish_engulfing(
self.stock_candles):
self.buying_stock("Bullish Engulfing", transcript)
bought_price = self.final_price()
trading = True
elif stock_analysis.bullish_rising_three(
self.stock_candles):
self.buying_stock("Bullish Rising Three",
transcript)
bought_price = self.final_price()
trading = True
elif stock_analysis.bullish_harami(self.stock_candles):
self.buying_stock("Bullish Harami", transcript)
bought_price = self.final_price()
trading = True
time.sleep(60)
current_time = self.get_time().split(":")
if trading:
self.account.sell(self.stock_candles[1][1][1])
json_string = self.stock_json(self.stock_candles[1],
"Final Sell", "Should Sell")
transcript.append(json_string)
self.account.get_portfolio()
self.write_json(data)
def day_candle_trends(self):
stock_analysis = StockCandlesAnalysis()
self.create_json()
with open('trading.json') as json_file:
data = json.load(json_file)
transcript = data['Transcript']
stock_data, stock_meta = self.time_series.get_intraday(
symbol=self.stock, interval='1min', outputsize='full')
stock_intervals = str(stock_data).split("}, ")
stock_intervals[0] = stock_intervals[0][1:]
#date = self.get_latest_date(stock_intervals[0])
#print(date)
#print(stock_intervals)
#stock_interval_amount = self.amount_of_stock_intervals(stock_intervals)
#print(stock_interval_amount)
bought_price = 0
trading = False
start_interval, end_interval = self.start_and_end_of_intervals(
stock_intervals)
while start_interval >= end_interval:
stock_call = str(stock_intervals[start_interval]).split(
': ', 1)
info = self.get_stock_candle_info(stock_call[1])
stock_date = stock_call[0].replace("{", "")
self.stock_candles.insert(0, [stock_date, info])
if len(self.stock_candles) > 5:
if trading:
if stock_analysis.bearish_engulfing(
self.stock_candles
) and bought_price < self.stock_candles[0][1][1]:
self.selling_stock("Bearish Engulfing", transcript)
trading = False
elif stock_analysis.bearish_evening(
self.stock_candles
) and bought_price < self.stock_candles[0][1][1]:
self.selling_stock("Bearish Evening", transcript)
trading = False
elif stock_analysis.bearish_harami(
self.stock_candles
) and bought_price < self.stock_candles[0][1][1]:
self.selling_stock("Bearish Harami", transcript)
trading = False
elif stock_analysis.bearish_rising_three(
self.stock_candles
) and bought_price < self.stock_candles[0][1][1]:
self.selling_stock("Bearish Rising Three",
transcript)
trading = False
else:
if stock_analysis.bullish_engulfing(
self.stock_candles):
self.buying_stock("Bullish Engulfing", transcript)
bought_price = self.final_price()
trading = True
elif stock_analysis.bullish_rising_three(
self.stock_candles):
self.buying_stock("Bullish Rising Three",
transcript)
bought_price = self.final_price()
trading = True
elif stock_analysis.bullish_harami(self.stock_candles):
self.buying_stock("Bullish Harami", transcript)
bought_price = self.final_price()
trading = True
start_interval -= 1
if trading:
self.account.sell(self.stock_candles[1][1][1])
json_string = self.stock_json(self.stock_candles[1],
"Final Sell", "Should Sell")
transcript.append(json_string)
self.account.get_portfolio()
self.write_json(data)
