We automatically trade options via some simple algorithms and it's only applicable for Charles Schwab Accounts. The author is Lin with MathPhdTrading and she explains her algorithms more in details in her Youtube Channel: https://youtube.com/@mathphdtrading-sv2024?si=3MZf12bxZ4E5TL3x.
*** I just added The Wheel Strategy, please try it out!!! ***
First we only sell puts and/or calls since I am a big believer of Theta trading. So if you are an option buyers, you can stop here.
The new put trade has the expiration date 4 weeks out, the delta between [-0.24, -0.16] and the premium > 0.01 x strike price;
If an existing trade has a gain > 50% and abs(delta) <= 0.14. We close this existing trade and open a new trade based on above.
if an existing trade has the external value < 0.005 x strike price and expires in two weeks. We close this existing trade, and STO a new trade that has at least 2% lower strike price and $0.30 higher premium.
If you choose THE_WHEEL in ACCOUNT_TRADING_STRATEGY_MAP of configs/config.py, then we sell cash secured puts and covered calls for this account. The new puts/calls settings are the same as the above STO a new put/call, so is the definition of a winning trade. However in The Wheel strategy there is no losing trade any more. We will just let it be assigned and then sell the trading of the other direction.
Step 2: Scan through high IV stocks and sell options if the day, week, or month change is larger than x percent;
We do this based on two benefits:
- when a stock moves down significantly, the implied volatility (IV) of the stock increases, therefore a good candidate to sell puts;
- when a stock moves down significantly, we assume it won't go down too much, kinda like conditional probability. But don't trust this fully because some stocks go down for a reason (bad earning result, bad news and so on). If that's the case, don't sell puts. The new put trade has the expiration date 4 weeks out, the delta between [-0.24, -0.16] and the premium > 0.01 x strike price;
Step 3: Get earning tickers for a specific date and sell options for the earning tickers that are in the current positions;
IV of the stock is large, therefore a good candidate to sell puts. The new put trade has the expiration date that Friday of the earnings week, the delta between [-0.24, -0.14] and the premium > 0.005 x strike price;
The whole point of selling option trades is due to theta decay. A reasonable target is to have a theta decay of 0.1% of the account value per day. Since there are 250 trading days in a year, you are expected to gain 25% of annual return even if the stock doesn't change. Try uncomment the code in main.py and test it out yourself. You will get a "bold" prediction and a scatter plot.
Before you follow the instruction below, you need to apply for a developer account from Schwab, apply for an App inside the developer account, enable ThinkOrSwim from your account and etc. (Basically to follow the instruction from Tyler Bowers's github code). Tyler Bower is the author of schwabdev, the Schwab API. The code link is: https://github.com/tylerebowers/Schwab-API-Python After you get your connection to Schwab account working, you should also put your APP key and APP secret to the Config class in configs/config.py.
If you want to do earnings trade, you should apply for an account from apicalls.io and then subscribe to the cheapest plan (currently is $0 per month). You can get 500 calls per month that include only stocks, not option data. But earning calendars are covered. The good news is you are covered for 2024 Q3 since I have all the earning tickers in data/earnings_calendar.json.
Note: Always work under SchwabAutoTrading/, or the same level as README.md. Use the package manager pip to install.
You need to be in virtual environment to use pip. The following command creates a virtual environment .myenv in the current directory. You only run this when it is the first time to create a virtual environment.
python3 -m venv .myenvAnd then activate it:
source .myenv/bin/activateYou may wish to deactivate it later by simply typing
deactivatein your shell. When it is your first time to create a virtual environment, you need to install the necessary libraries before running the main file, you run:
pip3 install -r requirements.txtLast, don't forget to add your python path in your .bashrc.
Except test/ and data/, there are main.py plus 3 folders: configs, options and trading_algorithms.
configs: stores all the constants and enum classes. This is where you should change your app
key, app secret and account numbers. If you have different likings of expiration date and delta, you can
change your STO_TRADING_SETTINGS. Ideally, after you modify all the necessary variables in configs.py,
you can just run python3 main.py every day to trade.
options: composed of basic classes like stocks, options and option_chains.
trading: all the trading algorithm code is here. it deals with trading current positions of all accounts in trade_options.py; and in stock_screener.py it scan through a list of stocks and trade it if there are significant price changes, if so, STO put/call trades; in earnings_calendar.py, it check whether there is earnings next day, if so, STO a put that expires the Friday of the same week. and theta_analyzer.py gives you a portfolio theta decay rate and a nice scatter plot of all positions theta decay rate and expiration date.
main.py: Run this every day to trade!!!!
If you have any questions about the code, please email me at [email protected].