def main(self, stock, action, quantity):
username = ""
password = ""
rh = Robinhood()
rh.login(username=username, password=password)
instrument = rh.instruments(stock)[0]
if (action == "buy"):
rh.place_buy_order(instrument, quantity)
self.enteredTrade = True
if (action == "sell"):
rh.place_sell_order(instrument, quantity)
self.enteredTrade = False
while 1:
current_price = get_current_price(rh)
for instrument_url, info in current_price.items():
if instrument_url in bought:
bought_info = bought[instrument_url]
# Compute percentage
if bought_info["price"] > 1e-8:
percent = (info["price"] / bought_info["price"]) - 1
print(info["symbol"], percent)
#TODO: could sell based of percentage
# Compute price difference is below threshold, then sell the stock
price_diff = info["price"] - bought_info["price"]
# If the diff
if price_diff < PRICE_DIFF_LIMIT:
print("Selling {} shares of {}".format(info["quantity"],
info["symbol"]))
instrument = {"url": instrument_url, "symbol": info["symbol"]}
rh.place_sell_order(instrument, info["quantity"])
# refresh bought list
bought = obtain_bought(rh)
# Detected a new entry, so refresh bought list
else:
bought = obtain_bought(rh)
# Refresh every hour
time.sleep(REFRESH_TIME)
class RHTrader:
"""
Algorithmic trader using Robinhood API to enter positions based on RSI period and historical prices.
"""
def __init__(self, username, pwd, rsi=5):
self.rh = Robinhood()
self.rh.login(username=username, password=pwd)
self.rsiPeriod = rsi
self.enteredPosition = False
self.s = sched.scheduler(time.time, time.sleep)
self.data = np.array([])
self.closePrices = []
def populate(self):
historical_quotes = self.rh.get_historical_quotes(
"F", "5minute", "day")
index = 0
support = 0
resistance = 0
for key in historical_quotes["results"][0]["historicals"]:
if index >= len(historical_quotes["results"][0]["historicals"]) - (
self.rsiPeriod + 1):
if (index >= (self.rsiPeriod - 1) and datetime.strptime(
key['begins_at'], '%Y-%m-%dT%H:%M:%SZ').minute == 0):
support = 0
resistance = 0
print("Resetting support and resistance")
if float(key['close_price']) < support or support == 0:
support = float(key['close_price'])
print("Current Support is : ")
print(support)
if float(key['close_price']) > resistance:
resistance = float(key['close_price'])
print("Current Resistance is : ")
print(resistance)
self.closePrices.append(float(key['close_price']))
index += 1
self.data = np.array(self.closePrices)
def execute(self, sc):
if len(self.closePrices) > self.rsiPeriod:
# Calculate RSI
rsi = ti.rsi(self.data, period=self.rsiPeriod)
instrument = self.rh.instruments("F")[0]
# If rsi is less than or equal to 30 buy
if rsi[len(rsi) - 1] <= 30 and not self.enteredPosition:
print("Buying RSI is below 30!")
self.rh.place_buy_order(instrument, 1)
self.enteredPosition = True
# Sell when RSI reaches 70
if rsi[len(rsi) - 1] >= 70 and self.enteredPosition:
print("Selling RSI is above 70!")
self.rh.place_sell_order(instrument, 1)
self.enteredPosition = False
print(rsi)
# call this method again every 5 minutes for new price changes
self.s.enter(300, 1, self.execute, (sc, ))
def run(self):
self.s.enter(1, 1, self.execute, (self.s, ))
self.s.run()
