def build_candles(ticker: str, trader: shift.Trader, state: Dict[str, Any],
end_time):
queue_size = 30
while trader.get_last_trade_time() < end_time:
s = 0
price = trader.get_last_price(ticker)
candle = Candle(price, price, price, price)
while s < candle_size:
price = trader.get_last_price(ticker)
if price < candle.low:
candle.setLow(price)
if price > candle.high:
candle.setHigh(price)
sleep(1)
s += 1
price = trader.get_last_price(ticker)
candle.setClose(price)
try:
state[candles_key][ticker] += [candle]
except KeyError:
state[candles_key][ticker] = deque(maxlen=queue_size)
sleep(0.5)
state[candles_key][ticker] += [candle]
def run_save_prices(ticker: str, trader: shift.Trader, state: Dict[str, Any]) -> None:
"""
save prices for a given ticker to the state
"""
queue_size = 30
frequency = 60
# if prices_key not in state:
# state[prices_key] = {}
print = False
while True:
price = trader.get_last_price(ticker)
try:
state[prices_key][ticker] += [trader.get_last_price(ticker)]
except KeyError:
state[prices_key][ticker] = deque(maxlen=queue_size)
sleep(0.5)
state[prices_key][ticker] += [trader.get_last_price(ticker)]
# # print(f"Prices Stored: {state[prices_key][ticker]}")
# print(f"Last Price: {trader.get_last_price(ticker)}")
# print(f"updated prices for AAPL @ {trader.get_last_trade_time()} there are {len(state[prices_key][ticker])} entries for price - last price {price}")
# print(f"{ticker} PRICE UPDATED")
sleep(frequency)
def longer(trader: shift.Trader, tickers):
today = trader.get_last_trade_time()
endTime = dt.time(15, 50, 0)
dayEnd = dt.datetime.combine(today, endTime)
tickSize = 0.01
bp = (trader.get_portfolio_summary().get_total_bp())
dpa = bp / float(len(tickers))
for t in tickers:
lastPrice = trader.get_last_price(t)
while lastPrice == 0:
lastPrice = trader.get_last_price(t)
s = int((dpa / lastPrice) / 100)
for i in range(0, s):
# limitBuyPrice = lastPrice - tickSize
limit_sell = shift.Order(shift.Order.Type.MARKET_BUY, t, 1)
trader.submit_order(limit_sell)
while trader.get_last_trade_time() < dayEnd:
time.sleep(1)
for order in trader.get_waiting_list():
trader.submit_cancellation(order)
for t in tickers:
print(t)
lastPrice = trader.get_last_price(t)
item = trader.get_portfolio_item(t)
if item.get_shares() > 0:
sell = shift.Order(
shift.Order.Type.MARKET_SELL, t,
int(item.get_shares() /
100)) # Order size in 100's of shares, strictly as an int
trader.submit_order(sell)
elif item.get_shares() < 0:
buy = shift.Order(
shift.Order.Type.MARKET_BUY, t,
int(-1 * item.get_shares() /
100)) # Order size in 100's of shares, strictly as an int
trader.submit_order(buy)
print(f'submitted buy for {t}')
time.sleep(15)
utils.print_portfolio_information(trader)
utils.print_all_submitted_order(trader)
print(trader.get_last_trade_time())
return
def market_maker_one(trader: shift.Trader, ticker: str):
tickSize = 0.01
# james code need to change maybe?
today = trader.get_last_trade_time()
endTime = dt.time(15, 30, 0)
dayEnd = dt.datetime.combine(today, dt.datetime(endTime))
rightNow = trader.get_last_trade_time()
#right < the end of day at 3:50
while today < dayEnd:
'''
check inventory here
'''
trader.sub_all_order_book()
lastPrice = trader.get_last_price("AAPL")
limitBuyPrice = lastPrice - tickSize
limitSellPrice = lastPrice + tickSize
limit_buy = shift.Order(shift.Order.Type.LIMIT_BUY, "AAPL", 1,
limitBuyPrice)
limit_sell = shift.Order(shift.Order.Type.LIMIT_SELL, "AAPL", 1,
limitSellPrice)
# market_buy = shift.Order(shift.Order.Type.MARKET_BUY, "AAPL", 1)
# trader.submit_order(market_buy)
trader.submit_order(limit_buy)
trader.submit_order(limit_sell)
time.sleep(10)
return
def get_unrealized_pl(ticker: str, trader: shift.Trader):
p = trader.get_last_price(ticker)
item = trader.get_portfolio_item(ticker)
upl = -1 if item.get_shares() < 0 else 1
currValue = item.get_shares() * p
cost = item.get_shares() * item.get_price()
if cost == 0:
return 0
upl = upl*((currValue - cost)/cost)
return upl
def algo_1(trader: shift.Trader):
'''Moving average algorithm'''
print(trader.get_last_price("MSFT"))
best_price = trader.get_best_price("MSFT")
print(f"ask price: {best_price.get_ask_price()}")
print(f"local ask: {best_price.get_local_ask_price()}")
print(f"global ask: {best_price.get_global_ask_price()}")
print(f"bid price: {best_price.get_bid_price()}")
print(f"local bid: {best_price.get_local_bid_price()}")
print(f"global bid: {best_price.get_global_bid_price()}")
print(trader.get_close_price("MSFT"))
def collect_data(trader: shift.Trader, ticker: str):
today = trader.get_last_trade_time()
print(today)
endTime = dt.time(9, 35, 0)
end_of_data_collection_period = dt.datetime.combine(today, endTime)
prices = []
while (trader.get_last_trade_time() < end_of_data_collection_period):
prices.append(trader.get_last_price(ticker))
print(trader.get_last_trade_time())
time.sleep(5)
return {"prices": prices, **calculate_statistics(prices)}
def run_trades(trader: shift.Trader, state: Dict[str, Any]) -> None:
"""
run buy / sell trades
"""
run_trades_interval = 60 # seconds
while True:
sleep(run_trades_interval)
unsorted_differences: List[float] = []
unsorted_tickers: List[str] = []
for ticker in tickers:
prices = np.array(list(state[prices_key][ticker]))
ema_difference, price_minus_bollinger = get_should_long(prices)
unsorted_differences.append(ema_difference)
unsorted_tickers.append(ticker)
_, ranked_tickers = map(
list, zip(*sorted(zip(unsorted_differences, unsorted_tickers))))
for ticker in ranked_tickers:
prices = np.array(list(state[prices_key][ticker]))
ema_difference, price_minus_bollinger = get_should_long(prices)
item = trader.get_portfolio_item(ticker)
if item.get_shares() > 0:
# check to sell
if price_minus_bollinger > 0 or ema_difference < 0:
sell = shift.Order(
shift.Order.Type.MARKET_SELL, ticker,
int(math.ceil((item.get_shares() / 2) / 100.0)))
trader.submit_order(sell)
else:
for order in trader.get_waiting_list():
if order.symbol == ticker and order.type == shift.Order.Type.MARKET_BUY:
trader.submit_cancellation(order)
if ema_difference > 0:
bp = trader.get_portfolio_summary().get_total_bp()
amount = 200e3
if bp >= amount:
lastPrice = trader.get_last_price(ticker)
s = int((amount / lastPrice) / 100.)
buy = shift.Order(shift.Order.Type.MARKET_BUY, ticker,
s)
trader.submit_order(buy)
def get_unrealized_pl(ticker: str, trader: shift.Trader):
p = trader.get_last_price(ticker)
item = trader.get_portfolio_item(ticker)
long_shares = item.get_long_shares()
short_shares = item.get_short_shares()
upl = 0
curr_long_value = long_shares * p
cost_long = long_shares * item.get_long_price()
curr_short_value = short_shares * p
cost_short = short_shares * item.get_short_price()
if cost_long != 0:
upl += (curr_long_value - cost_long)/float(cost_long)
if cost_short != 0:
upl -= (curr_short_value - cost_short)/float(cost_short)
return upl
def run_save_prices(ticker: str, trader: shift.Trader,
state: Dict[str, Any]) -> None:
"""
save prices for a given ticker to the state
"""
queue_size = 30
get_data_interval = 60 # seconds
save_interval = timedelta(
seconds=1) # minimum time in between saving to state
if prices_key not in state:
state[prices_key] = {}
last_save_time = datetime.now()
current_data = []
while True:
sleep(get_data_interval)
current_data.append(trader.get_last_price(ticker))
curr_time = datetime.now()
if curr_time > last_save_time + save_interval:
if ticker not in state[prices_key]:
state[prices_key][ticker] = deque(maxlen=queue_size)
state[prices_key][ticker].extend(current_data)
current_data = []
last_save_time = curr_time
def run_trades(trader: shift.Trader, state: Dict[str, Any]) -> None:
"""
run buy / sell trades
"""
run_trades_interval = 60 # seconds
maxLoss = 0.01
while True:
# if (len())
unsorted_differences: List[float] = []
unsorted_tickers: List[str] = []
for ticker in tickers:
print(f"entered run trades: {ticker}")
if (ticker not in state[prices_key]) or len(list(state[prices_key][ticker])) < 22:
# print(f"have {len(list(state[prices_key][ticker]))} prices for {ticker}...moving on")
continue
prices = np.array(list(state[prices_key][ticker]))
# print(f"Prices({len(prices)}): {prices} ")
should_long = get_should_long(prices)
if(should_long is None):
# print(f"should_long is None {ticker}")
continue
ema_difference = should_long["ema_difference"]
prev_ema_difference = should_long["prev_ema_difference"]
# print(f"emaaaaa {ticker}: {ema_difference}")
unsorted_differences.append(ema_difference)
unsorted_tickers.append(ticker)
if(len(unsorted_differences) < 5):
sleep(5)
continue
print(unsorted_differences)
print(unsorted_tickers)
_, ranked_tickers = (reversed(list(t)) for t in zip(*sorted(zip(unsorted_differences, unsorted_tickers))))
for ticker in ranked_tickers:
prices = np.array(list(state[prices_key][ticker]))
should_long = get_should_long(prices)
if(should_long is None):
sleep(1)
continue
ema_difference = should_long["ema_difference"]
price_minus_bollinger_high = should_long["bollinger_band_high_difference"]
price_minus_bollinger_low = should_long["bollinger_band_low_difference"]
last_upper_bollinger_band = should_long["last_bollinger_band_high"]
last_lower_bollinger_band = should_long["last_bollinger_band_low"]
item = trader.get_portfolio_item(ticker)
if item.get_shares() > 0:
# check to sell
target_hit_count = state[target_key][ticker][0]
if ema_difference < 0:
cancel_all_trades(trader, ticker)
sleep(2)
print(f"{ticker} : HAVE SHARES, EMA CROSSED DOWN, SELL")
sell = shift.Order(shift.Order.Type.MARKET_SELL, ticker, int(item.get_shares()/100.0))
trader.submit_order(sell)
# over band, never hit
elif price_minus_bollinger_high > 0 and target_hit_count == 0:
cancel_all_trades(trader, ticker)
sleep(2)
s = item.get_shares()
print(f"{ticker} : HAVE SHARES, FIRST TARGET HIT, SELL HALF")
sell = shift.Order(shift.Order.Type.MARKET_SELL, ticker, int(math.ceil((s/2) / 100.0)))
trader.submit_order(sell)
sleep(5)
#check if you didn't happen to sell all due to minimum lot
if int(math.ceil((item.get_shares()/2) / 100.0)) < int(s/100):
lastPrice = trader.get_last_price(ticker)
initial_buy_price = item.get_price()
#keep track of this in state
trailing_stop_perc = (lastPrice - initial_buy_price) / initial_buy_price
trailing_stop_price = (1 - trailing_stop_perc) * lastPrice
print(f"{ticker} : HAVE SHARES, FIRST TARGET HIT, RESETTING LIMIT SELL")
sell = shift.Order(shift.Order.Type.LIMIT_SELL, ticker, int(math.ceil((item.get_shares()/2) / 100.0)), trailing_stop_price)
trader.submit_order(sell)
state[target_key][ticker] = [target_hit_count + 1, trailing_stop_perc]
elif target_hit_count > 0:
sold = 0
if price_minus_bollinger_low > 0:
cancel_all_trades(trader, ticker)
sleep(2)
sold = int(math.ceil((item.get_shares()/2) / 100.0))
print(f"{ticker} : HAVE SHARES, OVER FIRST TARGET HIT, TAKING MORE PROFIT SINCE STILL ABOVE BOLLINGER, SELL HALFT")
sell = shift.Order(shift.Order.Type.MARKET_SELL, ticker, sold)
trader.submit_order(sell)
sleep(5)
if sold < int(item.get_shares()/100):
lastPrice = trader.get_last_price(ticker)
avg_last_two_prices = (state[prices_key][ticker][-2] + state[prices_key][ticker][-1]) / 2.
if lastPrice >= avg_last_two_prices:
cancel_all_trades(trader, ticker)
sleep(2)
# keep same percentarange and update the loss PRICE
trailing_stop_perc = state[target_key][ticker][1]
trailing_stop_price = (1 - trailing_stop_perc) * lastPrice
print(f"{ticker} : HAVE SHARES, OVER FIRST TARGET HIT, SOLD MORE PROFIT SINCE STILL ABOVE BOLLINGER, STILL HAVE MORE, RESETTING LIMIT")
sell = shift.Order(shift.Order.Type.LIMIT_SELL, ticker, item.get_shares() / 100.0, trailing_stop_price)
trader.submit_order(sell)
sleep(5)
else:
pass
elif item.get_shares() < 0:
#check to see if we need to exit short positions
target_hit_count = state[target_key][ticker][0]
if ema_difference > 0:
cancel_all_trades(trader, ticker)
sleep(2)
buy = Shift.Order(shift.Order.Type.MARKET_BUY, ticker, -1*int(item.get_shares()/100.0))
trader.submit_order(buy)
elif price_minus_bollinger_low < 0 and target_hit_count == 0:
cancel_all_trades(trader, ticker)
sleep(2)
s = item.get_shares()
buy = shift.Order(shift.Order.Type.MARKET_BUY, ticker, -1*int(math.ceil((s/2) / 100.0)))
trader.submit_order(buy)
sleep(5)
#check if you happen to buy all back due to minimum lot
#if still have short positions, reset limit buy
if -1*int(math.ceil((item.get_shares()/2) / 100.0)) < -1*int(s/100) :
lastPrice = trader.get_last_price(ticker)
initial_sell_price = item.get_price()
trailing_stop_perc = (lastPrice - initial_sell_price) / initial_sell_price
trailing_stop_price = (1 + trailing_stop_perc) * lastPrice
buy = shift.Order(shift.Order.Type.LIMIT_BUY, ticker, int(math.ceil((item.get_shares()/2) / 100.0)), trailing_stop_price)
trader.submit_order(buy)
state[target_key][ticker] = [target_hit_count + 1, trailing_stop_perc]
#no close of position at all, so we just wanna reset the trailing stop loss
elif target_hit_count > 0:
bought = 0
if price_minus_bollinger_low < 0:
cancel_all_trades(trader, ticker)
sleep(2)
bought = -1*int(math.ceil((item.get_shares()/2) / 100.0))
buy = shift.Order(shift.Order.Type.MARKET_BUY, ticker, bought)
trader.submit_order(buy)
sleep(5)
if bought < -1*int(item.get_shares() / 100.0):
lastPrice = trader.get_last_price(ticker)
avg_last_two_prices = (state[prices_key][ticker][-2] + state[prices_key][ticker][-1]) / 2.
# keep same percentarange and update the loss PRICE
#TODO: fix a dollar amount instead of percentage
if lastPrice <= avg_last_two_prices:
cancel_all_trades(trader, ticker)
sleep(2)
trailing_stop_perc = state[target_key][1]
trailing_stop_price = (1 + trailing_stop_perc) * lastPrice
buy = shift.Order(shift.Order.Type.LIMIT_BUY, ticker, item.get_shares() / 100.0, trailing_stop_price)
trader.submit_order(buy)
else:
pass
else:
#reset target_hit_count because no shores no more
state[target_key][ticker] = [0,0]
for order in trader.get_waiting_list():
if order.symbol == ticker and order.type == shift.Order.Type.MARKET_BUY:
trader.submit_cancellation(order)
sleep(2)
if ema_difference > 0 and prev_ema_difference < 0:
bp = trader.get_portfolio_summary().get_total_bp()
amount = 200e3
if bp >= amount:
lastPrice = trader.get_last_price(ticker)
s = int((amount / lastPrice) / 100.)
buy = shift.Order(shift.Order.Type.MARKET_BUY, ticker, s)
initial_buy_price = trader.get_last_price(ticker)
initial_stop_loss = shift.Order(shift.Order.Type.LIMIT_SELL, ticker, s, trader.get_last_price(ticker)*(1-maxLoss))
print(f"{ticker} : DONT HAVE SHARES, HIT TARGET, HAVE BP, BUY")
trader.submit_order(buy)
sleep(5)
print(f"{ticker} : DONT HAVE SHARES, HIT TARGET, HAVE BP, SETTING INITIAL STOP LOSS")
trader.submit_order(initial_stop_loss)
elif ema_difference < 0:
bp = trader.get_portfolio_summary().get_total_bp()
short_profit, long_profit = get_unrealized_pl(trader)
#lost money on shorts
amount = (200e3 / 2)
amount_to_subtract = 0
if short_profit < 0:
amount_to_subtract += (-1*short_profit)
if (0.995 * (amount - amount_to_subtract)) < bp:
lastPrice = trader.get_last_price()
s = int((amount / lastPrice) / 100.)
sell = shift.Order(shift.Order.Type.MARKET_SELL, ticker, s)
initial_sell_price = trader.get_last_price(ticker)
initial_stop_loss = shift.Order(shift.Order.Type.LIMIT_BUY, ticker, trader.get_last_price(ticker)*(1+maxLoss), s)
trader.submit_order(sell)
sleep(5)
trader.submit_order(initial_stop_loss)
sleep(5)
sleep(run_trades_interval)
def run_trades(trader: shift.Trader, state: Dict[str, Any]) -> None:
"""
run buy / sell trades
"""
run_trades_interval = 30 # seconds
maxLoss = 0.004
maxGain = 0.004
while True:
unsorted_differences: List[float] = []
unsorted_tickers: List[str] = []
for ticker in tickers:
if (ticker not in state[prices_key]) or len(
list(state[prices_key][ticker])) < 21:
sleep(5)
continue
prices = np.array(list(state[prices_key][ticker]))
should_long = get_should_long(prices)
ema_difference = should_long["ema_difference"]
unsorted_differences.append(ema_difference)
unsorted_tickers.append(ticker)
if ticker == "AAPL":
print("PRE UNPACKING")
print(unsorted_differences)
print(unsorted_tickers)
print((list(t) for t in zip(
*sorted(zip(unsorted_differences, unsorted_tickers)))))
_, ranked_tickers = (list(t) for t in zip(
*sorted(zip(unsorted_differences, unsorted_tickers))))
for ticker in ranked_tickers:
prices = np.array(list(state[prices_key][ticker]))
should_long = get_should_long(prices)
ema_difference = should_long["ema_difference"]
price_minus_bollinger_high = should_long[
"bollinger_band_high_difference"]
price_minus_bollinger_low = should_long[
"bollinger_band_low_difference"]
last_upper_bollinger_band = should_long["last_bollinger_band_high"]
last_lower_bollinger_band = should_long["last_bollinger_band_low"]
item = trader.get_portfolio_item(ticker)
if item.get_shares() > 0:
# check to sell
target_hit_count = state[target_key][ticker][0]
if ema_difference < 0:
cancel_all_trades(trader, ticker)
sell = shift.Order(shift.Order.Type.MARKET_SELL, ticker,
int(item.get_shares() / 100.0))
trader.submit_order(sell)
elif price_minus_bollinger_high > 0 and target_hit_count == 0:
# over band, never hit
cancel_all_trades(trader, ticker)
s = item.get_shares()
sell = shift.Order(shift.Order.Type.MARKET_SELL, ticker,
int(math.ceil((s / 2) / 100.0)))
trader.submit_order(sell)
#check if you happen to sell all due to minimum lot
#if still have long positions, reset limit sell
if int(math.ceil(
(item.get_shares() / 2) / 100.0)) < int(s / 100):
lastPrice = trader.get_last_price(ticker)
initial_buy_price = item.get_price()
trailing_stop_perc = (
lastPrice - initial_buy_price) / initial_buy_price
trailing_stop_price = (1 -
trailing_stop_perc) * lastPrice
sell = shift.Order(
shift.Order.Type.LIMIT_SELL, ticker,
int(math.ceil((item.get_shares() / 2) / 100.0)),
trailing_stop_price)
trader.submit_order(sell)
#keep track of this in state
state[target_key][ticker] = [
target_hit_count + 1, trailing_stop_perc
]
elif target_hit_count > 0:
sold = 0
if price_minus_bollinger_high > 0:
cancel_all_trades(trader, ticker)
sold = int(math.ceil((item.get_shares() / 2) / 100.0))
sell = shift.Order(shift.Order.Type.MARKET_SELL,
ticker, sold)
trader.submit_order(sell)
if sold < int(item.get_shares() / 100):
lastPrice = trader.get_last_price(ticker)
avg_last_two_prices = (
state[prices_key][ticker][-2] +
state[prices_key][ticker][-1]) / 2.
#we have shares, hits target for 2nd time, and price > upper bo, and we took 1/2 profit, we still have more
if lastPrice >= avg_last_two_prices:
cancel_all_trades(trader, ticker)
# keep same percentarange and update the loss PRICE
#TODO: fix a dollar amount instead of percentage
trailing_stop_perc = state[target_key][ticker][1]
trailing_stop_price = (
1 - trailing_stop_perc) * lastPrice
sell = shift.Order(shift.Order.Type.LIMIT_SELL,
ticker,
item.get_shares() / 100.0,
trailing_stop_price)
trader.submit_order(sell)
else:
pass
#comment this if you want to yeet the short logic
elif item.get_shares() < 0:
#check to see if we need to exit short positions
target_hit_count = state[target_key][ticker][0]
if ema_difference > 0:
cancel_all_trades(trader, ticker)
buy = Shift.Order(shift.Order.Type.MARKET_BUY, ticker,
-1 * int(item.get_shares() / 100.0))
trader.submit_order(buy)
elif price_minus_bollinger_low < 0 and target_hit_count == 0:
cancel_all_trades(trader, ticker)
s = item.get_shares()
buy = shift.Order(shift.Order.Type.MARKET_BUY, ticker,
-1 * int(math.ceil((s / 2) / 100.0)))
trader.submit_order(buy)
#check if you happen to buy all back due to minimum lot
#if still have short positions, reset limit buy
if -1 * int(math.ceil(
(item.get_shares() / 2) / 100.0)) < -1 * int(s / 100):
lastPrice = trader.get_last_price(ticker)
initial_sell_price = item.get_price()
trailing_stop_perc = (lastPrice - initial_sell_price
) / initial_sell_price
trailing_stop_price = (1 +
trailing_stop_perc) * lastPrice
buy = shift.Order(
shift.Order.Type.LIMIT_BUY, ticker,
int(math.ceil((item.get_shares() / 2) / 100.0)),
trailing_stop_price)
trader.submit_order(buy)
state[target_key][ticker] = [
target_hit_count + 1, trailing_stop_perc
]
#no close of position at all, so we just wanna reset the trailing stop loss
elif target_hit_count > 0:
bought = 0
if price_minus_bollinger_low < 0:
cancel_all_trades(trader, ticker)
bought = -1 * int(
math.ceil((item.get_shares() / 2) / 100.0))
buy = shift.Order(shift.Order.Type.MARKET_BUY, ticker,
bought)
trader.submit_order(buy)
if bought < -1 * int(item.get_shares() / 100.0):
lastPrice = trader.get_last_price(ticker)
avg_last_two_prices = (
state[prices_key][ticker][-2] +
state[prices_key][ticker][-1]) / 2.
# keep same percentarange and update the loss PRICE
#TODO: fix a dollar amount instead of percentage
if lastPrice <= avg_last_two_prices:
cancel_all_trades(trader, ticker)
trailing_stop_perc = state[target_key][1]
trailing_stop_price = (
1 + trailing_stop_perc) * lastPrice
buy = shift.Order(shift.Order.Type.LIMIT_BUY,
ticker,
item.get_shares() / 100.0,
trailing_stop_price)
trader.submit_order(buy)
else:
pass
else:
#reset target_hit_count because no shares no more
state[target_key][ticker] = [0, 0]
for order in trader.get_waiting_list():
if order.symbol == ticker and order.type == shift.Order.Type.MARKET_BUY:
trader.submit_cancellation(order)
if order.symbol == ticker and order.type == shift.Order.Type.MARKET_SELL:
trader.submit_cancellation(order)
if ema_difference > 0:
bp = trader.get_portfolio_summary().get_total_bp()
amount = 200e3
if bp >= amount:
lastPrice = trader.get_last_price(ticker)
s = int((amount / lastPrice) / 100.)
buy = shift.Order(shift.Order.Type.MARKET_BUY, ticker,
s)
initial_buy_price = trader.get_last_price(ticker)
initial_stop_loss = shift.Order(
shift.Order.Type.LIMIT_SELL, ticker,
trader.get_last_price(ticker) * (1 - maxLoss), s)
trader.submit_order(buy)
trader.submit_order(initial_stop_loss)
#comment this if you want to yeet the short logic
elif ema_difference < 0:
bp = trader.get_portfolio_summary().get_total_bp()
short_profit, long_profit = get_unrealized_pl(trader)
#lost money on shorts
amount = (200e3 / 2)
amount_to_subtract = 0
if short_profit < 0:
amount_to_subtract += (-1 * short_profit)
if (0.995 * (amount - amount_to_subtract)) < bp:
lastPrice = trader.get_last_price()
s = int((amount / lastPrice) / 100.)
sell = shift.Order(shift.Order.Type.MARKET_SELL,
ticker, s)
initial_sell_price = trader.get_last_price(ticker)
initial_stop_loss = shift.Order(
shift.Order.Type.LIMIT_BUY, ticker,
trader.get_last_price(ticker) * (1 + maxLoss), s)
trader.submit_order(sell)
trader.submit_order(initial_stop_loss)
#
# check to see if we should enter short position
pass
sleep(run_trades_interval)
