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()
def watcher():
global graph_msg, graph_min, graph_max
rh = Robinhood()
rh.login(username=rh_user, password=rh_pass, qr_code=rh_qr)
raw_result = rh.positions()
result = raw_result['results']
shares_total = []
port_msg = f"Your portfolio ({rh.get_account()['account_number']}):\n"
loss_output = 'Loss:'
profit_output = 'Profit:'
loss_total = []
profit_total = []
graph_msg = None # initiates a variable graph_msg as None for looped condition below
n = 0
n_ = 0
for data in result:
share_id = str(data['instrument'].split('/')[-2])
buy = round(float(data['average_buy_price']), 2)
shares_count = int(data['quantity'].split('.')[0])
if shares_count != 0:
n = n + 1
n_ = n_ + shares_count
else:
continue
raw_details = rh.get_quote(share_id)
share_name = raw_details['symbol']
call = raw_details['instrument']
share_full_name = loads(get(call).text)['simple_name']
total = round(shares_count * float(buy), 2)
shares_total.append(total)
current = round(float(raw_details['last_trade_price']), 2)
current_total = round(shares_count * current, 2)
difference = round(float(current_total - total), 2)
if difference < 0:
loss_output += (
f'\n{share_full_name}:\n{shares_count} shares of {share_name} at ${buy} Currently: ${current}\n'
f'Total bought: ${total} Current Total: ${current_total}'
f'\nLOST ${-difference}\n')
loss_total.append(-difference)
else:
profit_output += (
f'\n{share_full_name}:\n{shares_count} shares of {share_name} at ${buy} Currently: ${current}\n'
f'Total bought: ${total} Current Total: ${current_total}'
f'\nGained ${difference}\n')
profit_total.append(difference)
if graph_min and graph_max:
graph_min = float(graph_min)
graph_max = float(graph_max)
if difference > graph_max or difference < -graph_min:
time_now = datetime.now()
metrics = time_now - timedelta(days=7)
numbers = []
historic_data = (rh.get_historical_quotes(
share_name, '10minute', 'week'))
historical_values = historic_data['results'][0]['historicals']
for close_price in historical_values:
numbers.append(round(float(close_price['close_price']), 2))
fig, ax = plt.subplots()
if difference > graph_max:
plt.title(
f"Stock Price Trend for {share_full_name}\nShares: {shares_count} Profit: ${difference}"
)
elif difference < graph_min:
plt.title(
f"Stock Price Trend for {share_full_name}\nShares: {shares_count} LOSS: ${-difference}"
)
plt.xlabel(
f"1 Week trend with 10 minutes interval from {metrics.strftime('%m-%d %H:%M')} to "
f"{time_now.strftime('%m-%d %H:%M')}")
plt.ylabel('Price in USD')
ax.plot(numbers, linewidth=1.5)
if not path.isdir('img'):
mkdir('img')
fig.savefig(f"img/{share_full_name}.png", format="png")
plt.close(
) # close plt to avoid memory exception when more than 20 graphs are generated
# stores graph_msg only if a graph is generated else graph_msg remains None
if not graph_msg: # used if not to avoid storing the message repeatedly
graph_msg = f"Attached are the graphs for stocks which exceeded a profit of " \
f"${graph_max} or deceeded a loss of ${graph_min}"
elif not graph_msg: # used elif not to avoid storing the message repeatedly
graph_msg = "Add the env variables for <graph_min> and <graph_max> to include a graph of previous " \
"week's trend."
lost = round(fsum(loss_total), 2)
gained = round(fsum(profit_total), 2)
port_msg += f'The below values will differ from overall profit/loss if shares were purchased ' \
f'with different price values.\nTotal Profit: ${gained}\nTotal Loss: ${lost}\n'
net_worth = round(float(rh.equity()), 2)
output = f'Total number of stocks purchased: {n}\n'
output += f'Total number of shares owned: {n_}\n\n'
output += f'Current value of your total investment is: ${net_worth}\n'
total_buy = round(fsum(shares_total), 2)
output += f'Value of your total investment while purchase is: ${total_buy}\n'
total_diff = round(float(net_worth - total_buy), 2)
if total_diff < 0:
output += f'Overall Loss: ${total_diff}'
else:
output += f'Overall Profit: ${total_diff}'
yesterday_close = round(float(rh.equity_previous_close()), 2)
two_day_diff = round(float(net_worth - yesterday_close), 2)
output += f"\n\nYesterday's closing value: ${yesterday_close}"
if two_day_diff < 0:
output += f"\nCurrent Dip: ${two_day_diff}"
else:
output += f"\nCurrent Spike: ${two_day_diff}"
if not graph_msg: # if graph_msg was not set above
graph_msg = f"You have not lost more than ${graph_min} or gained more than " \
f"${graph_max} to generate a graph."
return port_msg, profit_output, loss_output, output, graph_msg
# Log in to Robinhood app (will prompt for two-factor)
rh = Robinhood()
rh.login(username=config.USERNAME,
password=config.PASSWORD,
qr_code=config.MFA)
# STOCK TICKER
stock_ticker = input("Enter Stock ticker you would like to trade: ").upper()
# Create a User and set the day trade limit.
number_of_trades = database_function.get_number_of_trades("database.txt")
user = User(0,0,0,0,int(number_of_trades),None)
# Get quote data from RH API
day_year_quotes = rh.get_historical_quotes(stock_ticker, 'day', 'year')
#print(* day_year_quotes["results"][0]["historicals"], sep='\n')
async def run():
while True:
time_string = time.strftime("%m/%d/%Y, %H:%M:%S", time.localtime())
# POST TIME
print("\nGetting historical quotes on {}".format(time_string))
# This gets the last 60 days including today.
five_min_day_yahoo = yahoo_finance.get_stock_history(stock_ticker, "5m")
# Create list of closing prices from RH API
close_prices = []
[close_prices.append(float(key['close_price'])) for key in day_year_quotes["results"][0]["historicals"]]
