def run_stock_pipelines(stock_database: [str]):
for ticker_symbol in stock_database:
if ticker_symbol not in trading_constants.blacklist:
try:
trend_following_polarity = trend_following(ticker_symbol)
ema_crossover_polarity = ema_crossover(ticker_symbol)
console_output = "{0} price: {1} at {2}, strategy polarity: {3}\n".format(
ticker_symbol, (yf_extender.get_stock_state(
yf.Ticker(ticker_symbol))['Close'] * 1000) / 1000,
datetime.now().strftime("%H:%M:%S"),
trend_following_polarity + ema_crossover_polarity)
print(console_output, end='')
if (trend_following_polarity + ema_crossover_polarity) >= 0.5:
stock_price = yf_extender.get_stock_state(
yf.Ticker(ticker_symbol))['Close']
stock_quantity = math.floor(
portfolio_manager.buying_power *
trading_constants.max_investment_partition *
(trend_following_polarity + ema_crossover_polarity) /
stock_price)
if stock_quantity > 0 and portfolio_manager.buying_power > (
stock_quantity * stock_price):
portfolio_manager.buy_stock(ticker_symbol,
stock_quantity)
except IndexError:
print(ticker_symbol + ": No Data")
def buy_stock(ticker_symbol: str, quantity: int):
with lock:
global buying_power
json_simp.read_json()
purchased_copy = dict(purchased)
ticker = yf.Ticker(ticker_symbol)
stock_info = yf_ext.get_stock_state(ticker)
if ticker_symbol not in purchased_copy and buying_power > (
quantity * stock_info['Close']):
api.submit_order(symbol=ticker_symbol,
qty=quantity,
side='buy',
type='market',
time_in_force='day')
stock_info['Quantity'] = quantity
purchased[ticker_symbol] = stock_info
console_output = "Buying " + ticker_symbol + " Quantity: {0}".format(
stock_info['Quantity']) + "\n"
print(console_output, end=' ')
buying_power -= (quantity *
yf_ext.get_stock_state(ticker)['Close'])
alerts.say_beep(1)
json_simp.updated_purchased()
json_simp.read_json()
def evaluate_purchased_stocks():
time.sleep(2)
while True:
purchased_copy = dict(portfolio_manager.purchased)
for ticker_symbol in purchased_copy:
ticker = yf.Ticker(ticker_symbol)
stock_info = yf_extender.get_stock_state(ticker)
price_change_since_purchase = stock_info['Close'] - purchased_copy[
ticker_symbol]['Close']
print(
"Checking " + ticker_symbol +
" | Direction: {0} | Price Change: {1} | Gains/Losses: {2}".
format(
yf_extender.get_direction(ticker),
price_change_since_purchase, price_change_since_purchase *
purchased_copy[ticker_symbol]['Quantity']))
if stock_info['Close'] < yf_extender.calculate_ema(ticker):
print("Because stock price dropped below EMA line, " +
ticker_symbol)
portfolio_manager.sell_stock(ticker_symbol)
break
elif yf_extender.get_direction(
ticker) < -0.001: #should depend on proportion
print("Because direction is downward {0}".format(
yf_extender.get_direction(ticker)))
portfolio_manager.sell_stock(ticker_symbol)
break
time.sleep(0.1)
def refresh_account_balance():
with lock:
global buying_power
global account_value
json_simp.read_json()
buying_power = trading_constants.starting_account_value
account_value = trading_constants.starting_account_value
purchased_copy = dict(purchased)
sold_copy = dict(sold)
for ticker_symbol in purchased_copy:
current_ticker_price = yf_ext.get_stock_state(
yf.Ticker(ticker_symbol))['Close']
purchased_ticker_price = purchased_copy[ticker_symbol]['Close']
purchased_ticker_quantity = purchased_copy[ticker_symbol][
'Quantity']
account_value += current_ticker_price - purchased_ticker_price
buying_power -= purchased_ticker_price * purchased_ticker_quantity
for ticker_symbol in sold_copy:
temp = sold[ticker_symbol]['Close'] * abs(
sold[ticker_symbol]['Quantity'])
buying_power += temp
account_value += temp
def trend_following(ticker_symbol: str):
ticker = yf.Ticker(ticker_symbol)
stock_info = yf_extender.get_stock_state(ticker)
previous_2mo_high = yf_extender.previous_high(ticker, "2mo")
if previous_2mo_high < stock_info[
'Close'] and yf_extender.get_high2current_price_change_percent(
ticker) > -0.0025:
return 0.2
return 0.0
def sell_stock(ticker_symbol: str):
api.close_position(ticker_symbol)
global buying_power
refresh_account_balance()
sold_copy = dict(sold)
ticker = yf.Ticker(ticker_symbol)
stock_info = Counter(yf_ext.get_stock_state(ticker))
purchased_copy = dict(purchased)
console_output = "Selling " + ticker_symbol + " Quantity: {0}".format(
stock_info['Quantity']) + "\n"
if ticker_symbol not in sold_copy and ticker_symbol != "":
purchase_info = Counter(purchased.pop(ticker_symbol))
console_output = "Selling " + ticker_symbol + " Quantity: {0}".format(
purchase_info['Quantity']) + "\n"
stock_info.pop('Time')
purchase_info.pop('Time')
stock_info.subtract(purchase_info)
stock_info['Time'] = datetime.now().strftime("%H:%M:%S")
sold[ticker_symbol] = stock_info
buying_power += stock_info['Close'] * abs(stock_info['Quantity'])
elif ticker_symbol in purchased_copy:
purchase_info = Counter(purchased.pop(ticker_symbol))
console_output = "Selling " + ticker_symbol + " Quantity: {0}".format(
purchase_info['Quantity']) + "\n"
sold_info = Counter(sold.pop(ticker_symbol))
stock_info.pop('Time')
purchase_info.pop('Time')
sold_info.pop('Time')
stock_info.subtract(purchase_info)
for i in stock_info and sold_info:
stock_info[i] = stock_info[i] + sold_info[i]
stock_info['Time'] = datetime.now().strftime("%H:%M:%S")
sold[ticker_symbol] = stock_info
buying_power += stock_info['Close'] * abs(stock_info['Quantity'])
json_simp.updated_purchased()
json_simp.updated_sold()
json_simp.read_json()
print(console_output, end=' ')
alerts.say_beep(2)
def ema_crossover(ticker_symbol: str):
ticker = yf.Ticker(ticker_symbol)
stock_info = yf_extender.get_stock_state(ticker)
stock_history = ticker.history(period="1d", interval="5m")
previous_price = stock_history.iloc[len(stock_history) -
2].to_dict()['Close']
ticker_ema = yf_extender.calculate_ema(ticker)
ticker_previous_ema = yf_extender.calculate_previous_ema(ticker)
if stock_info[
'Close'] > ticker_ema and previous_price < ticker_previous_ema and stock_info[
'Close'] > 3:
print(
ticker_symbol +
" previous price ema {0} previous price {1} current price ema {2} current price {3} direction {4}"
.format(ticker_previous_ema, previous_price, ticker_ema,
stock_info['Close'], yf_extender.get_direction(ticker)))
return 0.5
return 0.0