FinanceToolkit v1.8.3

[JerBouma]

This release includes the Binomial Model, a mathematical model for pricing both American as well as European options. The Binomial Model is a discrete-time model that calculates the price of an option by creating a riskless hedge portfolio that replicates the payoff of the option. The model is based on the assumption that the price of the underlying asset follows a binomial distribution. The Binomial Model is a simple and intuitive model that is widely used in practice. It is also the basis for more complex models. See for an elaborate explanation the documentation as found here.

For example, when using the following code:

from financetoolkit import Toolkit

companies = Toolkit(["AAPL", "MSFT"], api_key="FINANCIAL_MODELING_PREP_KEY")

companies.options.get_binomial_model(show_input_info=True)

It returns a large DataFrame with the binomial tree for each company and each strike price around the current price (as defined by the start_date parameter).

The resulting output is a DataFrame containing the tickers, strike prices and movements as the index and the time to expiration as the columns. The movements index contains the number of up movements and the number of down movements. The output is the binomial tree displayed in a table. E.g. when using 10 time steps, the table for each strike price from each company will contain the actual binomial tree as also depicted in the image as seen below. Find the documentation here.

When selecting for example Apple at a Strike Price of 140 you will get the actual Binomial Tree depicted as a table, this represents the tree you see in the image at the top.

Movement	2024-02-02	2024-03-09	2024-04-15	2024-05-21	2024-06-27	2024-08-02	2024-09-08	2024-10-14	2024-11-20	2024-12-26	2025-02-01
UUUUUUUUUU	54.7747	69.9327	87.4757	107.31	129.344	153.573	180.122	209.208	241.069	275.965	314.18
UUUUUUUUUD	nan	39.9569	52.8423	68.2288	86.0206	106.037	128.14	152.365	178.911	207.994	239.852
UUUUUUUUDD	nan	nan	27.3011	37.7763	50.8718	66.5774	84.6651	104.825	126.925	151.146	177.689
UUUUUUUDDD	nan	nan	nan	16.9659	24.8886	35.4656	48.9066	65.0645	83.4462	103.602	125.698
UUUUUUDDDD	nan	nan	nan	nan	9.1158	14.4288	22.208	33.0259	47.083	63.8384	82.2161
UUUUUDDDDD	nan	nan	nan	nan	nan	3.8311	6.7007	11.4806	19.124	30.5822	45.85
UUUUDDDDDD	nan	nan	nan	nan	nan	nan	0.9669	1.9327	3.8631	7.722	15.4353
UUUDDDDDDD	nan	nan	nan	nan	nan	nan	nan	0	0	0	0
UUDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	0	0	0
UDDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	nan	0	0
DDDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0

The model contains parameters to lengthen the time steps, change the risk-free rate and the dividend yield but more importantly, make it possible to calculate the price of both American and European options as well as Call and Put options. For example, let's calculate the price of a American Put option with a strike price of 140 for Apple again:

from financetoolkit import Toolkit

companies = Toolkit(["AAPL", "MSFT"], api_key="FINANCIAL_MODELING_PREP_KEY")

companies.options.get_binomial_model(
    show_input_info=True,
    put_option=True,
    american_option=True,
    timesteps=12,
    risk_free_rate=0.01)

Which returns the Option valuations for an American Put Option.

Movement	2024-02-02	2024-03-03	2024-04-02	2024-05-03	2024-06-02	2024-07-03	2024-08-02	2024-09-01	2024-10-02	2024-11-01	2024-12-02	2025-01-01	2025-02-01
UUUUUUUUUUUU	2.3581	1.1115	0.4236	0.116	0.0171	0	0	0	0	0	0	0	0
UUUUUUUUUUUD	nan	3.7011	1.8524	0.7546	0.2225	0.0355	0	0	0	0	0	0	0
UUUUUUUUUUDD	nan	nan	5.6933	3.0346	1.3274	0.4238	0.0736	0	0	0	0	0	0
UUUUUUUUUDDD	nan	nan	nan	8.5588	4.8737	2.3002	0.8005	0.1529	0	0	0	0	0
UUUUUUUUDDDD	nan	nan	nan	nan	12.5322	7.6463	3.9148	1.4975	0.3173	0	0	0	0
UUUUUUUDDDDD	nan	nan	nan	nan	nan	17.8023	11.6676	6.518	2.7676	0.6586	0	0	0
UUUUUUDDDDDD	nan	nan	nan	nan	nan	nan	24.4233	17.2193	10.5575	5.0375	1.3671	0	0
UUUUUDDDDDDD	nan	nan	nan	nan	nan	nan	nan	32.2051	24.4052	16.5049	8.9884	2.8376	0
UUUUDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	40.6414	32.9347	24.6074	15.6102	5.89
UUUDDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	nan	48.9936	41.9389	34.3151	26.0772
UUDDDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	56.6615	50.2044	43.2257
UDDDDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	63.702	57.7929
DDDDDDDDDDDD	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	70.1673

Under the hood of this model the stock prices are simulated based on up and down movements. These can be graphically depicted as a binomial tree and help in understanding the calculated option prices for each node in. More information about these stock price simulations can be found in the documentation here and as follows:

from financetoolkit import Toolkit

companies = Toolkit(["AAPL", "MSFT"], api_key="FINANCIAL_MODELING_PREP_KEY")

companies.options.get_stock_price_simulations(show_input_info=True, timesteps=10)

Which would return for Apple the following graph when plotted:

Given that the Finance Toolkit is modular, you do not have to use the Toolkit functionality directly and can also call each functionality of the model separately. For example, this shows the output of using the model directly, specifying each parameter yourself.