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tradebotpy.py
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tradebotpy.py
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#@title Trade Bot { form-width: "25%" }
# %tb
# import Alpaca trade API, and install in Colab
try:
import alpaca_trade_api as tradeapi
except:
print("Installing alpaca_trade_api")
#!pip install alpaca_trade_api --quiet
import alpaca_trade_api as tradeapi
import pandas as pd
import numpy as np
from datetime import datetime
import time
from tqdm import tqdm
from tqdm import trange
# authentication and connection details
api_key = ""
api_secret = ""
#base_url = 'https://paper-api.alpaca.markets'
base_url = 'https://api.alpaca.markets'
# instantiate REST API
api = tradeapi.REST(api_key, api_secret, base_url, api_version='v2')
# Debugging
debug = False #@param{type:"boolean"}
verbose = True #@param{type:"boolean"}
# Debugging - set a custom test time
if debug:
current_time = "09:30:00"
# Convert utc time to local?
# Try this if the current time is wrong
convert_time = False
ticker = "SPY"
#investment = 70000
investment = 25100
usable_cash = 20000
keep_as_cash = investment - usable_cash
# keep_as_cash = investment - (380)*3
margin_times = 1
shorting = True #@param{type:"boolean"}
global stop_loss1
stop_loss1 = 0.12
global stop_loss2
stop_loss2 = -0.03
global trade_ext_hours
trade_ext_hours = False #@param{type:"boolean"}
overnight_positions = False
backtesting = False #@param{type:"boolean"}
# if backtesting:
# open = True
# debug = True
# trade_ext_hours = True
start_date = "automatic"
end_date = "automatic"
global start_time
start_time = "10:00"
# print(f"Start time + 10 mins: {start_time+'00:10'}")
global start_time_hour
start_time_hour = int(start_time[:2])
global start_time_minute
start_time_minute = int(start_time[-2:])
global end_time
end_time = "15:40" # 4 p.m.
global end_time_hour
end_time_hour = end_time[:2]
# Initialize
e = ""
portfolio_value = None
def get_current_datetime(verbose=True):
global convert_time
if not convert_time:
now = datetime.now()
else: now = utc_to_local(datetime.now())
#24-hour format
# print(now.strftime('%Y/%m/%d %H:%M:%S'))
current_time = now.strftime('%H:%M:%S')
#12-hour format
curr_datetime = now.strftime('%Y/%m/%d %I:%M:%S %p')
# current_time = now.strftime('%I:%M:%S %p')
if verbose:
print(curr_datetime)
#print(current_time)
return current_time, curr_datetime
def check_if_open(api=api):
# Check when the market opens/closes
from datetime import datetime
todays_date = datetime.today().strftime('%Y-%m-%d')
date = todays_date
calendar = api.get_calendar(start=date, end=date)[0]
print('The market opens at {} and closes at {} on {}.'.format(
calendar.open,
calendar.close,
date
))
# Check if the market is open now.
clock = api.get_clock()
open = clock.is_open
print('The market is {}'.format('open.' if open else 'closed.'))
if debug:
open = True
current_time, curr_datetime = get_current_datetime()
global trade_ext_hours
global ext_hours
ext_hours = False
global start_time
global end_time
if (current_time >= end_time) and (current_time < "18"):
ext_hours = True
if trade_ext_hours:
open = True
if current_time >= "09" and current_time < start_time:
ext_hours = True
if trade_ext_hours:
open = True
if (current_time >= "18") and (current_time < "09"):
ext_hours = False
open = False
#if (current_time > "15:58") and not trade_ext_hours:
#ext_hours = False
#open = False
if (current_time > start_time) and (current_time < end_time):
ext_hours = False
else: open = False
print(f"Open: {open}, ext_hours: {ext_hours}")
return open, calendar.open, calendar.close, date, ext_hours
# https://discuss.codecademy.com/t/how-to-convert-to-12-hour-clock/3920/3
import pytz
local_tz = pytz.timezone('US/Eastern')
def utc_to_local(utc_dt):
local_dt = utc_dt.replace(tzinfo=pytz.utc).astimezone(local_tz)
return local_tz.normalize(local_dt) # .normalize might be unnecessary
if not convert_time:
now = datetime.now()
else: now = utc_to_local(datetime.now())
def wait_for_open():
#global open
open = False
if not open:
print("Getting current time...")
if debug:
global current_time
else:
current_time, curr_datetime = get_current_datetime()
split_time = str(current_time).split(":")
hours = int(split_time[0])
minutes = int(split_time[1])
seconds = int(split_time[2])
#print(hours, minutes, seconds)
global start_time_hour
global start_time_minute
hours_till_open = (23 - hours) + start_time_hour
if hours_till_open >= 23:
hours_till_open = hours_till_open - 24
minutes_till_open = (60 - minutes) + start_time_minute
seconds_till_open = (0 - seconds)
#print(hours_till_open, minutes_till_open, seconds_till_open)
time_till_open = ((hours_till_open*60)*60) + (minutes_till_open*60) + seconds_till_open
print(f"Waiting {hours_till_open} hours, {minutes_till_open} minutes, and {seconds_till_open} seconds until open.")
print(f"Or {time_till_open} seconds until open.")
for i in trange(time_till_open):
time.sleep(1-.01)
open, open_time, close_time, todays_date, ext_hours = check_if_open()
print("Getting current time")
current_time, curr_datetime = get_current_datetime()
if not open and current_time >= "09" and current_time < "16":
print("Must be weekend or holiday, waiting till tommorow...")
open = False
return open, ext_hours
def get_market_data():
if not backtesting:
#try:
# Getting time of first order
#list_orders = api.list_orders(status="closed", direction="asc", limit=1)
#first_order_fill_time = str(list_orders).split("'filled_at': '")
#first_order_fill_time = str(first_order_fill_time[1]).split("',")
#first_order_fill_time = first_order_fill_time[0]
#ticker_data = api.get_barset(ticker, timeframe="1Min", start=first_order_fill_time)
#ticker_data = ticker_data.df
#ticker_data = ticker_data.between_time(time_range_start, time_range_end)
#except:
try:
ticker_data = api.get_barset(ticker, timeframe="1Min", limit=100) #100
ticker_data = ticker_data.df
#ticker_data = ticker_data.between_time(start_time, end_time)
except Exception as e:
print(e)
else:
start = "2020-12-21" #@param {type:"date"}
# start = "2014-01-01T09:30:00-04:00"
start += "T09:30:00-04:00"
end = "2019-01-01" #@param {type:"date"}
end_today = True #@param {type:"boolean"}
if not end_today:
end += "T09:30:00-04:00"
try:
ticker_data = api.get_barset(ticker, timeframe="1Min", start=start, end=end)
except Exception as e:
print(e)
else:
try:
ticker_data = api.get_barset(ticker, timeframe="1Min", start=start)
except Exception as e:
print(e)
try:
ticker_data = ticker_data.df
ticker_data = ticker_data.between_time(start_time, end_time)
except Exception as e:
print(e)
ticker_data.columns = ticker_data.columns.droplevel(0)
ticker_data.columns
return ticker_data
def add_calculations(data, advice, margin_times=margin_times):
count = 0
stock = data
# stock = stock.between_time('9:00', '18:00')
# stock = stock.between_time(time_range_start, time_range_end)
# first_close = stock['close'][0]
# stock['close'] = stock['close'][0] * int(investment / stock['close'][0])
stock['balance'] = stock['close']
# stock['balance'][0] = investment
balance = stock['balance']
# balance[0] = investment
# advice = stock['advice']
# print(last_minute_data)
# input()
stock['price change'] = stock['close'].diff(periods=1)
price_change = stock['price change']# * (int(investment / stock['close'][0]))
#last = stock['Last']
close = stock['close']
print(count)
own_shares = 0
index = stock.index
# in tqdm(range(1, len(advice...
time_start = time.time()
for i in tqdm(range(1, len(advice)), disable=not backtesting, desc="Calculating backtest balances... [1/3]"):
if advice[i] == "SELL":
own_shares = 0
if advice[i] == "BUY":
own_shares = int(balance[i] / close[i])
# Simulate closing positions before end of day
try:
subtract = index[i+1] - index[i]
subtract = subtract.to_pytimedelta()
subtract = str(subtract).split(":")
subtract = int(subtract[1])
# If the next row is more than 30 mins away, close out of positions
if subtract > 30:
own_shares = 0
except:
own_shares = 0
if own_shares >= 1:
balance[i] = balance[i-1] + (price_change[i])#*own_shares
else:
if shorting:
balance[i] = balance[i-1] - (price_change[i])#*own_shares
else:
balance[i] = balance[i-1]
time_end = time.time()
print(f"advice took {time_end - time_start} seconds")
stock['real choice'] = advice
real_choice = stock['real choice']
time_start = time.time()
#for i in tqdm(range(1, len(price_change)-1), disable=not backtesting, desc="Calculating buy and sell signals... [2/3]"):
#if price_change[i+1] > 0:
#real_choice[i] = "BUY"
#if price_change[i+1] < 0:
#real_choice[i] = "SELL"
real_choice = np.where(price_change.shift(-1) > 0, "BUY", "SELL")
time_end = time.time()
print(f"Price_change took {time_end - time_start} seconds")
stock['correct'] = advice
correct = stock['correct']
def count_correct(advice, real_choice):
time_start = time.time()
# debugging
print("Printing real choice")
print(real_choice)
# for i in range(1, len(real_choice)):
# if advice.iloc[i] == "HOLD":
# advice.iloc[i] = advice.iloc[i-1]
# if real_choice.iloc[i] == "HOLD":
# real_choice.iloc[i] = real_choice.iloc[i-1]
'''These two above and below are seemingly interchangable, but .iloc proves to be actually slower.'''
for i in trange(1, len(real_choice), disable=not backtesting, desc="Converting HOLDs and calculating backtest correct/incorrect... [3/3]"):
if (advice[i] == "HOLD"):
advice[i] = advice[i-1]
if (real_choice[i] == "HOLD"):
real_choice[i] = real_choice[i-1]
if advice[i] == real_choice[i]:
correct[i] = "CORRECT"
else:
correct[i] = "INCORRECT"
time_end = time.time()
print(f"count_correct took {time_end - time_start} seconds")
# for i in trange(1, len(real_choice), disable=not backtesting, desc="Converting HOLDs and calculating backtest correct/incorrect... [3/3]"):
# advice = [advice[i-1] for i in advice if advice[i] == "HOLD"]
# real_choice = [real_choice[i-1] for i in real_choice if real_choice[i] == "HOLD"]
# correct = correct[i]
def percent_right():
# did this cuz counting the number of 'correct' includes the incorrect
num_incorrect = correct.str.count("INCORRECT").sum()
total_choices = len(correct)
num_correct = total_choices - num_incorrect
print(f"""
num correct: {num_correct}
total_choices: {total_choices}
""")
return (num_correct / total_choices) * 100
count_correct(advice, real_choice)
print("Percent right: {}%".format(round(percent_right(), 3)))
initial = balance.iloc[1]
end_price = balance.iloc[-1]
def calc_percent_return(initial, end_price):
calc = (end_price-initial)/initial
calc = calc*100
return calc
percent_return = calc_percent_return(initial, end_price)
percent_return = round(percent_return, 3)
print(f"Percent return: {percent_return}%")
# stock.index.values[-1] <-- tried this, but gave a really big number idk if its seconds or what
start_date = stock.index[1]
end_date = stock.index[-1]
def calculate_days(start_date, end_date):
return end_date - start_date
days = calculate_days(start_date, end_date)
days = str(days).split()
days = days[0]
days = int(days)
print(f"Time for return: {days} days")
def extrapolate_returns(percent_return, days):
# seconds = days.total_seconds()
# hours = seconds / 60
# days = hours / 24
# print(days)
return_per_day = percent_return / days #6?
return_per_year = return_per_day * 365 #252 trading days
return_per_year = round(return_per_year, 3)
return return_per_year
print("Return per year: {}%".format(extrapolate_returns(percent_return, days)))
print()
def baseline_return():
initial_baseline = close.iloc[1]
end_price_baseline = close.iloc[-1]
baseline_return = calc_percent_return(initial_baseline, end_price_baseline)
baseline_return = round(baseline_return, 3)
return baseline_return
baseline_return = baseline_return()
print(f"Baseline return: {baseline_return}%")
baseline_advantage = percent_return - baseline_return
baseline_advantage = round(baseline_advantage, 3)
print(f"Percent better than baseline: {baseline_advantage}%")
print()
def plot(data, type="pyplot"):
if type == "pyplot":
import matplotlib.pyplot as plt
balance.plot()
close.plot()
plt.ylabel('price')
plt.show()
list_orders = api.list_orders(status="closed", direction="asc", limit=1)
first_order_fill_time = str(list_orders).split("'filled_at': '")
first_order_fill_time = str(first_order_fill_time[1]).split("',")
first_order_fill_time = first_order_fill_time[0]
first_order_fill_time = first_order_fill_time[:10]
# portfolio_history = api.get_portfolio_history(timeframe="1Min", date_start=first_order_fill_time)
current_time, curr_datetime = get_current_datetime()
# global curr_datetime
print(curr_datetime[:10])
import numpy as np
portfolio_history = api.get_portfolio_history(timeframe="1Min", date_start=str(curr_datetime[:10]).replace("/", "-"), date_end=str(curr_datetime[:10]).replace("/", "-"))
profit_loss = portfolio_history.profit_loss
profit_loss = pd.DataFrame(np.array(profit_loss).reshape(len(profit_loss),1), columns = list("p"))
# print(profit_loss)
profit_loss.plot()
plt.ylabel('profit')
plt.xlabel('arbitrary time')
plt.show()
if type == "interactive":
import plotly.offline as pyo
import plotly.graph_objs as go
from plotly.offline import iplot
import cufflinks as cf
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
cf.go_offline()
#%matplotlib inline
init_notebook_mode(connected=False)
def configure_plotly_browser_state():
import IPython
display(IPython.core.display.HTML('''
<script src="/static/components/requirejs/require.js"></script>
<script>
requirejs.config({
paths: {
base: '/static/base',
plotly: 'https://cdn.plot.ly/plotly-1.5.1.min.js?noext',
},
});
</script>
'''))
configure_plotly_browser_state()
stock.iplot(kind='line',x='',y=['close', 'balance'], color=['orange', 'blue'],
theme='solar', mode='markers+lines',title='Trading bot')
if backtesting:
plot_type = "pyplot" #@param ["interactive", "pyplot"]
else:
plot_type = "pyplot"
plot(data, type=plot_type)
def get_advice(data, strategy="default"):
if strategy == "default":
#your strat here
return advice, last_advice
def cancel_all_orders(verbose=True):
if verbose:
print("Cancelling all orders...")
api.cancel_all_orders()
def get_positions(verbose=True):
#wait(1)
cancel_all_orders(verbose=verbose)
try: positions = api.get_position(ticker)
except Exception as e:
print(e)
if "Too many" in str(e):
wait(1)
get_positions()
if "does not exist" in str(e):
positions = None
qty = 0
market_value = 0
side = None
print(e)
return positions, qty, market_value, side
try:
qty = int(positions.qty)
market_value = float(positions.market_value)
side = positions.side
if side == "short":
side = "sell"
else:
side = "buy"
except Exception as e:
positions = None
qty = 0
market_value = 0
side = None
print(e)
return positions, qty, market_value, side
account = api.get_account()
def truncate(n, decimals=0):
multiplier = 10 ** decimals
return int(n * multiplier) / multiplier
def order(last_advice, e=""):
current_time, curr_datetime = get_current_datetime()
if (current_time > "15:58") and not trade_ext_hours:
close_margin(last_advice)
print("Setting open to false because it is almost market close and we're not trading extended hours.")
open = False
open, ext_hours = wait_for_open()
if (current_time > "15:58") and not overnight_positions:
last_advice = None
open = False
open, ext_hours = wait_for_open()
filled = False
while not filled:
current_positions, current_qty, current_market_value, current_side = get_positions()
print(f"Current quantity: {current_qty}")
print(f"Current side: {current_side}")
print(f"Current market value: ${current_market_value}")
def define_order(e=""):
if verbose:
print("Defining order")
close_prices = market_data['close']
last_close = close_prices[-1]
limit_price = last_close
account = api.get_account()
last_equity = float(account.last_equity)
if e == "insufficient buying power":
buying_power = float(account.regt_buying_power)
else:
buying_power = float(account.buying_power)
buying_power = buying_power / 4
global ext_hours
if not ext_hours:
buying_power = buying_power * margin_times
buying_power = buying_power - current_market_value
portfolio_value = float(account.portfolio_value)
total_profit = portfolio_value - investment
total_profit_perc = (total_profit / investment) * 100
todays_profit = portfolio_value - last_equity
todays_profit_perc = (todays_profit / last_equity) * 100
list_orders = api.list_orders(status="closed", direction="asc", limit=1)
try:
first_order_fill_price = str(list_orders).split("'filled_at': '")
first_order_fill_price = str(first_order_fill_price[1]).split("',")[1]
first_order_fill_price = str(first_order_fill_price).split(": '")[1]
print(f"First order fill price: {first_order_fill_price}")
buy_and_hold = float(limit_price) - float(first_order_fill_price)
vs_hold = float(total_profit) - float(buy_and_hold)
print(f"Buy and hold: {buy_and_hold:.2f}")
print(f"vs_hold: {vs_hold:.2f}")
except: pass
try:
share_adj_perc = todays_profit_perc*(last_equity/abs(current_market_value))
#share_adj_perc = ((abs(current_market_value) - (abs(current_market_value)+todays_profit))/(abs(current_market_value)+todays_profit))*100
#share_adj_perc = (((abs(current_market_value)+todays_profit) - abs(current_market_value))/abs(current_market_value))*100
except Exception as e:
print(e)
share_adj_perc = 0
useable_cash = truncate(((last_equity - keep_as_cash)*margin_times), 2) # Using last_equity instead of portfolio_value because funds aren't settled until the end of day
target_qty = int(useable_cash / limit_price)
global stop_loss1
global stop_loss2
# if share_adj_perc >= stop_loss1 or share_adj_perc <= stop_loss2:
# print(f"Today's profit: {todays_profit}")
# send_email("Stop loss")
# raise Exception("Stop loss")
global stop_loss_tripped
try: stop_loss_tripped
except: stop_loss_tripped = False
print(f"Tripped: {stop_loss_tripped}")
if not stop_loss_tripped:
if truncate(share_adj_perc, decimals=2) >= stop_loss1:
stop_loss_tripped = True
print("Positive stop loss closing all positions")
print(f"Today's profit: {todays_profit}")
print(f"Today's profit % (share adjusted): {share_adj_perc:.2f}%")
close_all_positions()
send_email("Stop loss")
del stop_loss_tripped
raise Exception("Stop loss")
# if not stop_loss_tripped:
# if todays_profit >= useable_cash * (stop_loss1/100):
# stop_loss_tripped = True
# print("Positive stop loss closing all positions")
# close_all_positions()
# print(f"Today's profit: {todays_profit}")
# print(f"Today's profit % (share adjusted): {share_adj_perc:.2f}%")
# send_email("Stop loss")
# raise Exception("Stop loss")
if not stop_loss_tripped:
global start_time
current_time, curr_datetime = get_current_datetime()
if current_time > start_time:# and start_time_minute > 10:
if truncate(share_adj_perc, decimals=2) <= stop_loss2:
stop_loss_tripped = True
print("Negative stop loss closing all positions")
print(f"Today's profit: {todays_profit}")
print(f"Today's profit % (share adjusted): {share_adj_perc:.2f}%")
close_all_positions()
send_email("Stop loss")
del stop_loss_tripped
raise Exception("Stop loss")
if verbose:
print(f"Last equity: ${last_equity}")
print(f"Buying power: ${buying_power:.2f}")
print(f"Keep as cash: ${keep_as_cash}")
print(f"Portfolio value: ${portfolio_value}")
print(f"Total profit: ${total_profit:.2f}")
print(f"Total profit %: {total_profit_perc:.2f}%")
print(f"Today's profit: ${todays_profit:.2f}")
print(f"Today's profit %: {todays_profit_perc:.2f}%")
print(f"Today's profit % (share adjusted): {share_adj_perc:.2f}%")
print(f"Useable cash: ${useable_cash}")
print(f"Limit price: ${limit_price}")
print(f"Target Qty: {target_qty}")
return limit_price, target_qty, buying_power, useable_cash
limit_price, target_qty, buying_power, useable_cash = define_order(e)
quantity = target_qty
if last_advice == None:
to_close = True
if current_side == "sell":
side = "buy"
last_advice = "buy"
else:
side = "sell"
last_advice = "sell"
target_qty = 0
print(f"Setting target qty to {target_qty}")
else: to_close = False
future_buying_power = useable_cash - (limit_price * quantity)
if future_buying_power < 0:
print(f"Skipping because future buying power == {future_buying_power}")
return
if buying_power == 0:
print(f"Skipping because buying power is {buying_power}")
return
if quantity < 1 and last_advice == "buy":
print(f"Setting quantity = current_qty because quantity {quantity} < 1 and last_advice is {last_advice}")
quantity = current_qty
i = 1
while last_advice == "hold":
i += 1
last_advice = advice[-i]
last_advice = last_advice.lower()
try:
if (current_side == last_advice) and (abs(target_qty) == abs(current_qty)):
print(f"Skipping order because we are holding positions")
return
except Exception as e: print(e)
# input(f"quantity = {quantity}, last advice = {last_advice}")
# if (quantity < 1) and (last_advice == current_side):
# print(f"Skipping order because quantity {quantity} < 1 and we're on same side")
# return
try:
print(f"Current side: {current_side}, last advice: {last_advice}")
print(f"current qty: {current_qty}, Quantity: {quantity}")
if current_side != None:
if (current_side != last_advice) and (quantity > current_qty):
print("Setting quantity == current_qty because we're trying to switch sides")
quantity = current_qty
print(f"Quantity: {quantity}")
except Exception as e:
print(e)
# input("5")
#if trade_ext_hours == False:
#if debug:
#print("Setting ext_hours to false")
#ext_hours = False
# Debugging
# last_advice = "sell"
# quantity = 56
# send_order(limit_price, quantity, last_advice)
if abs(current_qty) > target_qty+1:
send_email("Using too many shares")
def send_order(limit_price, quantity, side, ext_hours, type="limit"):
if side == "no data":
wait_for_new_data()
cancel_all_orders()
current_positions, current_qty, current_market_value, current_side = get_positions()
if abs(quantity) > target_qty:
quantity = current_qty
if current_side == side:
if (quantity + current_qty) > target_qty:
print(f"Trade quantity {quantity} + current_qty: {current_qty} would exceed target_qty: {target_qty}")
#send_email("Trade quantity {quantity} + current_qty: {current_qty} would exceed target_qty: {target_qty}")
#if target_qty - current_qty > current_qty:
quantity = target_qty - current_qty
quantity = abs(quantity)
print(f"Quantity: {quantity}")
print(f"Side: {side}, Last advice: {last_advice}")
if quantity < 1:
filled = True
return filled
if debug:
print("Sending order")
try:
if ext_hours:
print(f"Extended limit order: {side} {quantity} shares of {ticker} for ~${limit_price}. Total: ~${limit_price*quantity:.2f}")
api.submit_order(symbol=ticker,
qty=abs(quantity),
side=side,
time_in_force='day',
extended_hours= ext_hours,
type='limit',
limit_price=limit_price)
# client_order_id=order_id)
else:
print(f"{type} order: {side} {quantity} shares of {ticker} for ~${limit_price}. Total: ~${(limit_price*quantity):.2f}")
api.submit_order(symbol=ticker,
qty=abs(quantity),
side=side,
time_in_force='day',
type='limit',
limit_price=limit_price)
# limit_price=400.00,
# client_order_id=order_id)
except Exception as e:
print(e)
e = str(e)
if "insufficient buying power" in e:
order(last_advice, e="insufficient buying power")
wait(quantity*0.01)
current_positions, current_qty, current_market_value, current_side = get_positions()
def qty_delta(current_qty, quantity, current_side, last_advice, limit_price, side, ext_hours):
print("In qty_delta")
#elif current_qty != quantity:
## input("3")
#print("Getting quantity delta")
## if (current_side == "sell" and current_qty < 0) and
#quantity_delta = current_qty - quantity
#print(f"Quantity detla: {quantity_delta}")
#if quantity_delta
#send_order(limit_price, quantity=quantity_delta, last_advice)
#if abs(current_qty) != abs(quantity):
#if (current_qty > quantity) or (current_qty < quantity):
#print("Getting quantity delta")
#quantity_delta = current_qty - (quantity)
#if quantity_delta > 0:
#side = "sell"
#if quantity_delta < 0:
#side = "buy"
#send_order(limit_price, quantity=quantity_delta, side=side)
current_positions, current_qty, current_market_value, current_side = get_positions()
if current_qty == 0:
if quantity != 0:
quantity_delta = quantity
else: quantity_delta = target_qty
side = last_advice
return side, quantity_delta
quantity = target_qty
if abs(current_qty) != abs(quantity):
if (abs(current_qty) > abs(quantity)) or (abs(current_qty) < abs(quantity)):
if current_side == last_advice:
print("Setting quantity delta to quantity - current qty because we're on the right side")
quantity_delta = abs(quantity) - abs(current_qty)
if quantity_delta > 0:
side = current_side
elif quantity_delta < 0:
if current_side == "sell":
side = "buy"
else: side = "sell"
else:
side = last_advice
print(f"I think we want to switch sides here, setting qty_delta to current_qty")
quantity_delta = current_qty
#quantity_delta = abs(quantity) - abs(current_qty)
#if quantity_delta > 0:
#side = "buy"
#elif quantity_delta < 0:
#side = "sell"
print("Sending order to fix quantity delta")
if current_qty == 0:
side = last_advice
#if current_side == last_advice:
#side = last_advice
#else:
#side = current_side
if quantity_delta == 0 or (quantity_delta == quantity):
print(f"Quantity delta is {quantity_delta}, so setting quantity delta to quantity {quantity}")
quantity_delta = quantity
if (quantity_delta > current_qty) and (current_side != last_advice):
print(f"Setting quantity delta to quantity because we're trying to switch sides")
quantity_delta = current_qty
print(f"Quantity delta: {quantity_delta}")
print(f"Last advice: {last_advice}")
print(f"Side: {side}")
send_order(limit_price, quantity=quantity_delta, side=side, ext_hours=ext_hours)
else:
side = last_advice
quantity_delta = quantity
return side, quantity_delta
try:
# input("1")
if (current_side == last_advice) and (current_qty == quantity):
# input("2")
print(f"Skipping order because current_positions.side and current_qty are the same")
return
except Exception as e:
print(e)
pass
try: side
except: side = last_advice
try: quantity_delta
except:
print(f"Setting quantity = quantity_delta")
quantity_delta = quantity
print(f"Quantity: {quantity}, qty delta: {quantity_delta}")
#global ext_hours
ext_hours = False
if current_qty != target_qty:
side, quantity = qty_delta(current_qty, quantity, current_side, last_advice, limit_price, side, ext_hours)
#if abs(current_qty) != abs(quantity):
#print("Sending regular order")
#send_order(limit_price, quantity, side=last_advice)
def check_fill(current_positions, current_qty, current_side, side, quantity, target_qty, to_close=to_close):
print("In check_fill")
#open_orders_list = api.list_orders(status='open')
# Check if there are no open orders
#if not open_orders_list:
#print("No open orders")
#filled = True
#return filled
try:
old_positions = current_positions
old_qty = current_qty
#old_market_value = current_market_value
old_side = current_side
#wait(5)
current_positions, current_qty, current_market_value, current_side = get_positions()
print(f"Current qty: {current_qty}, quantity: {quantity}")
print(f"Current side: {current_side}, last advice: {last_advice}")
if old_qty == current_qty and old_side == current_side:
filled = False
if abs(target_qty) == abs(current_qty) and last_advice == current_side:
filled = True
else:
filled = False
if to_close:
if current_qty == 0 and current_side != "sell" and current_side != "buy" and current_side != "hold":
filled = True
try: side
except: side = last_advice
if current_qty != target_qty:
side, quantity = qty_delta(current_qty, quantity, current_side, last_advice, limit_price, side, ext_hours)
except Exception as e:
print(e)
filled = False
return filled
print(f"Target qty: {target_qty}")
filled = check_fill(current_positions, current_qty, current_side, side, quantity, target_qty)
if filled:
play_sound("filled")
print(f"Filled: {filled}")
# input("6")
def get_filled(filled, limit_price, quantity, side):
i = 0
while not filled:
if current_qty != target_qty:
side, quantity = qty_delta(current_qty, quantity, current_side, last_advice, limit_price, side, ext_hours)
if side == "sell":
limit_price = limit_price - 0.01
else:
limit_price = limit_price + 0.01
print(f"Iterations: {i}")
if i >= 4:
if side == "sell":
limit_price = limit_price - 1
else: limit_price = limit_price + 1
print(f"Limit price: {limit_price}")
print("Sending order to get filled")
filled = check_fill(current_positions, current_qty, current_side, side, quantity, target_qty)
send_order(limit_price, quantity, side, ext_hours)
i += 1
#wait(5)
filled = check_fill(current_positions, current_qty, current_side, side, quantity, target_qty)
print(f"Filled: {filled}")
else:
print(f"Filled: {filled}")
play_sound("filled")
# input("7")
if not filled:
# input("8")
print(f"Quantity: {quantity}")
get_filled(filled, limit_price, quantity, side)
def close_margin(last_advice):
print("Closing margin")
global trade_ext_hours
if trade_ext_hours == False:
set_trade_ext_hours = False
else: set_trade_ext_hours = True
trade_ext_hours = True
current_positions, current_qty, current_market_value, current_side = get_positions()
if current_qty == 0 and current_side != "sell" and current_side != "buy" and current_side != "hold":
print("No current positions")
else:
print("Closing out of margin...")
global margin_times
margin_times = 1
if current_qty == 0 and current_side != "sell" and current_side != "buy":
print("No current positions")
market_data = get_market_data()
order(last_advice, e=e)
trade_ext_hours = set_trade_ext_hours
#send_order(limit_price, quantity=current_qty, side=side, ext_hours=ext_hours)
def close_all_positions():
global trade_ext_hours