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utils.py
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utils.py
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import math
import os
import time
from datetime import datetime, timedelta
from decimal import Decimal
from typing import Any, Optional
import pyotp
import robin_stocks.robinhood as r
from dotenv import load_dotenv
from loguru import logger
from exceptions import NoStrikePriceError
from models import Bounds, Interval, OptionType, Span
def closest_friday() -> str:
"""Returns the nearest Friday as a string in YYYY-MM-DD format"""
today = datetime.today()
return (today + timedelta((4 - today.weekday()) % 7)).strftime("%Y-%m-%d")
# Function to fetch the nearest expiration date and most profitable strike
# ~14sec slower on avg than `get_closest_strike_price()`
def find_best_strikes(ticker, exp_date) -> tuple[dict, dict]:
stock_price = Decimal(r.stocks.get_latest_price(ticker)[0])
# Fetch call and put options for the nearest expiration date
call_options = r.options.find_options_by_expiration(
ticker, expirationDate=exp_date, optionType=OptionType.call
)
put_options = r.options.find_options_by_expiration(
ticker, expirationDate=exp_date, optionType=OptionType.put
)
# Find the strike prices closest to the current stock price
best_call_option = min(
call_options, key=lambda x: abs(Decimal(x["strike_price"]) - stock_price)
)
best_put_option = min(
put_options, key=lambda x: abs(Decimal(x["strike_price"]) - stock_price)
)
return best_call_option, best_put_option
def ensure_orders_are_filled(func):
def wrapper(*args, **kwargs):
all_filled = None
filled_orders = 0
while not all_filled:
time.sleep(2)
orders = func(*args, **kwargs)
for order in orders:
if is_option_position_bought(order["id"]):
filled_orders += 1
if filled_orders == len(orders):
all_filled = True
logger.info("Success - Orders filled")
logger.info("Failure - Orders not filled. Trying again...")
return orders
return wrapper
def round_to_nearest_half_dollar(
price: float | Decimal, option_type: OptionType
) -> Decimal:
if option_type == OptionType.call:
return Decimal(math.ceil(price * 2) / 2)
if option_type == OptionType.put:
return Decimal(math.floor(price * 2) / 2)
def calculate_mean(list) -> Decimal:
return Decimal(sum(list) / len(list))
def calculate_std_dev(list, mean: Decimal) -> Decimal:
variance = sum((x - mean) ** 2 for x in list) / len(list)
return Decimal(math.sqrt(variance))
def log_in() -> dict | None:
load_dotenv()
totp = pyotp.TOTP(os.getenv("MFA_CODE")).now()
return r.login(os.getenv("EMAIL"), os.getenv("PASSWORD"), mfa_code=totp)
def current_stock_price(ticker: str | list[str]) -> dict | list[dict]:
price_list = r.stocks.get_latest_price(ticker)
if len(price_list) == 1:
return Decimal(price_list[0])
return [Decimal(price) for price in price_list]
def get_stock_basic_info(ticker: str | list[str]) -> dict | list[dict]:
"""
- A dict is returned per ticker symbol provided
- A single ticker symbol i.e. "aapl" returns a dict of basic info
- A list of ticket symbols i.e ["aapl", "tsla"] returns a list[dict] of basic info
"""
res = r.stocks.get_fundamentals(ticker)
curated_info = [
{
"open": r["open"],
"high": r["high"],
"low": r["low"],
"high_52_weeks": r["high_52_weeks"],
"low_52_weeks": r["low_52_weeks"],
}
for r in res
]
if len(curated_info) == 1:
return curated_info[0]
return curated_info
def at_stop_loss(
position: dict, current_price: Decimal, stop_loss_percentage: Decimal
) -> bool:
entry_price = position["entry_price"] # Get this somehow
loss = (entry_price - current_price) / entry_price
logger.info(f"Current loss: {loss}")
return loss >= stop_loss_percentage
# Note: Extended and Trading hours FORCE you to use a 'day' time window - whatever
# Note: Default args for the daily pre-market prep - shift args for subsequent calls as needed
def get_stock_historical_price_deltas(
ticker: str | list[str],
candle_interval: Optional[Interval] = Interval.ten_min,
time_window: Optional[Span] = Span.day,
trading_hours: Optional[Bounds] = Bounds.extended,
) -> list[dict]:
curated_data = []
raw_data = r.stocks.get_stock_historicals(
ticker, candle_interval, time_window, trading_hours
)
for entry in raw_data:
curated_data.append(
{
# Time is UTC so market hours are 14:30 to 21:00
"datetime": entry["begins_at"],
"open_to_close_price_delta": (
str(Decimal(entry["close_price"]) - Decimal(entry["open_price"]))
),
}
)
return curated_data
def get_closest_strike_price(ticker: str, option_type: OptionType) -> Decimal:
# TODO: Performance can be improved by getting a list of all strike prices
# for that ticker, sort that array and grab the closest one above the current price.
# It'll be 1 API call + static array sorting and indexing vs a max of 5 API calls
price = Decimal(r.stocks.get_latest_price(ticker)[0])
nearest_half_dollar_increment = round_to_nearest_half_dollar(price, option_type)
logger.info(
f"Current Stock price: {price} \nFinding closest out-of-the-money strike price..."
)
if r.options.find_options_by_strike(
ticker, nearest_half_dollar_increment, option_type, info="expiration_date"
):
logger.info(f"Closest strike price: {nearest_half_dollar_increment}")
return nearest_half_dollar_increment
for i in range(4):
if option_type == OptionType.call:
nearest_half_dollar_increment = nearest_half_dollar_increment + Decimal(0.5)
if option_type == OptionType.put:
nearest_half_dollar_increment = nearest_half_dollar_increment - Decimal(0.5)
if r.options.find_options_by_strike(
ticker, nearest_half_dollar_increment, option_type, info="expiration_date"
):
logger.info(f"Closest strike price: {nearest_half_dollar_increment}")
return nearest_half_dollar_increment
raise NoStrikePriceError(
f"No strike price found for {ticker} within 2.5 dollars of the current stock price"
)
def get_nearest_out_of_the_money_option_contract_details(
ticker: str, call_or_put: OptionType, exp_date: Optional[str] = None
) -> dict | None:
"""
- This will find find the closest out-of-the-money option contract for the ticker and option type requested.
- The expiration date, unless specified, will default to the closest Friday
- The strike price is set by looking .5 to 1 dollar above the current stock price
Arguments:
ticker: The stock ticker
call_or_put: The option type -> 'call' or 'put'
exp_date (optional): Option exp date in YYYY-MM-DD format
- Default -> Nearest Friday
"""
if not exp_date:
next_friday = closest_friday()
if details := r.options.find_options_by_expiration_and_strike(
inputSymbols=ticker,
optionType=call_or_put,
expirationDate=exp_date if exp_date else next_friday,
strikePrice=get_closest_strike_price(ticker, call_or_put),
):
details = details[0]
if details["state"] == "active" and details["tradability"] == "tradable":
return {
"symbol": details["chain_symbol"],
"expiration_date": details["expiration_date"],
"strike_price": details["strike_price"],
"last_trade_price": details["last_trade_price"],
"fair_midpoint_price": details["mark_price"],
"buying_details": {
"high_fill_rate_price": details["high_fill_rate_buy_price"],
"low_fill_rate_price": details["low_fill_rate_buy_price"],
},
"selling_details": {
"high_fill_rate_price": details["high_fill_rate_sell_price"],
"low_fill_rate_price": details["low_fill_rate_sell_price"],
},
"ask_price": details["ask_price"],
"ask_size": details["ask_size"],
"bid_price": details["bid_price"],
"bid_size": details["bid_size"],
"greeks": {
"delta": details["delta"],
"gamma": details["gamma"],
"rho": details["rho"],
"theta": details["theta"],
"vega": details["vega"],
},
}
logger.warning(
"Requested stock has no active or tradable options contract. Try a different stock, option type, etc"
)
def is_option_position_bought(option_id) -> bool:
open_positions = r.options.get_open_option_positions()
for position in open_positions:
if option_id == position["id"]:
return True # position is open/bought
return False # order is not open/not bought
@ensure_orders_are_filled
def monitor_trade_and_sell(
option, take_profit: Decimal = 0.05, stop_loss: Decimal = 0.02, positions=1
) -> None:
initial_total_value = Decimal(option["fair_midpoint_price"] or option["mark_price"])
# Refresh option data
refreshed_option_info = r.options.get_option_market_data_by_id(option["id"])[0]
current_total_value = (
Decimal(refreshed_option_info["adjusted_mark_price"])
+ Decimal(refreshed_option_info["ask_price"])
) / 2
profit_pct = (current_total_value - initial_total_value) / initial_total_value
logger.info(f"Current Profit: {profit_pct*100:.2f}%")
if profit_pct >= take_profit:
logger.info("Take-profit triggered, closing positions.")
sold_option = sell_option_limit_order(
option["chain_symbol"],
OptionType.call,
option["strike_price"],
option["expiration_date"],
positions,
current_total_value,
)
return [sold_option]
elif profit_pct <= -stop_loss:
logger.info("Stop-loss triggered, closing positions.")
sold_option = sell_option_limit_order(
option["chain_symbol"],
OptionType.call,
option["strike_price"],
option["expiration_date"],
positions,
current_total_value,
)
return [sold_option]
def buy_option_limit_order(
ticker: str,
call_or_put: OptionType,
strike_price: float | Decimal,
exp_date: str,
quantity: int,
option_price: float | Decimal,
time_in_force: str = "ioc",
) -> dict | Any:
raise Exception("Don't want to buy options right now")
return r.orders.order_buy_option_limit(
positionEffect="open",
creditOrDebit="debit",
price=option_price,
symbol=ticker,
quantity=quantity,
expirationDate=exp_date,
strike=strike_price,
optionType=call_or_put,
timeInForce=time_in_force, # Defaulting to 'immediate or cancel'
)
def sell_option_limit_order(
ticker: str,
call_or_put: OptionType,
strike_price: float | Decimal,
exp_date: str,
quantity: int,
option_price: float | Decimal,
time_in_force: str = "ioc",
) -> dict | Any:
raise Exception("Don't want to sell options right now")
# TODO: We need to monitor if we've actually sold the contracts. Putting them up for sale doesn't mean they've been sold.
return r.orders.order_sell_option_limit(
positionEffect="close",
creditOrDebit="credit",
price=option_price,
symbol=ticker,
quantity=quantity,
expirationDate=exp_date,
strike=strike_price,
optionType=call_or_put,
timeInForce=time_in_force, # Defaulting to 'immediate or cancel'
)