Struct Inputs

Source

pub struct Inputs {
    pub option_type: OptionType,
    pub s: f64,
    pub k: f64,
    pub p: Option<f64>,
    pub r: f64,
    pub q: f64,
    pub t: f64,
    pub sigma: Option<f64>,
}

Expand description

The inputs to the Black-Scholes-Merton model.

Fields§

§option_type: OptionType

The type of the option (call or put)

§s: f64

Stock price

§k: f64

Strike price

§p: Option<f64>

Option price

§r: f64

Risk-free rate

§q: f64

Dividend yield

§t: f64

Time to maturity in years

§sigma: Option<f64>

Volatility

Implementations§

Source §

impl Inputs

Methods for calculating the price, greeks, and implied volatility of an option.

Source

pub fn new( option_type: OptionType, s: f64, k: f64, p: Option<f64>, r: f64, q: f64, t: f64, sigma: Option<f64>, ) -> Self

Creates instance ot the Inputs struct.

§Arguments

option_type - The type of option to be priced.
s - The current price of the underlying asset.
k - The strike price of the option.
p - The dividend yield of the underlying asset.
r - The risk-free interest rate.
q - The dividend yield of the underlying asset.
t - The time to maturity of the option in years.
sigma - The volatility of the underlying asset.

§Example

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, None, 0.05, 0.2, 20/365.25, Some(0.2));

§Returns

An instance of the Inputs struct.

Source

pub fn str(&self) -> String

§Returns

string representation of the Inputs struct.

Source

pub fn calc_price(&self) -> PyResult<f64>

Calculates the price of the option.

§Requires

s, k, r, q, t, sigma.

§Returns

f64 of the price of the option.

§Example

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, None, 0.05, 0.2, 20/365.25, Some(0.2));
let price = inputs.calc_price();

Source

pub fn calc_delta(&self) -> PyResult<f64>

Calculates the delta of the option.

§Requires

s, k, r, q, t, sigma

§Returns

f64 of the delta of the option.

§Example

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, None, 0.05, 0.2, 20/365.25, Some(0.2));
let delta = inputs.calc_delta();

Source

pub fn calc_gamma(&self) -> PyResult<f64>

Calculates the gamma of the option.

§Requires

s, k, r, q, t, sigma

§Returns

f64 of the gamma of the option.

§Example

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, None, 0.05, 0.2, 20/365.25, Some(0.2));
let gamma = inputs.calc_gamma();

Source

pub fn calc_theta(&self) -> PyResult<f64>

Calculates the theta of the option. Uses 365.25 days in a year for calculations.

§Requires

s, k, r, q, t, sigma

§Returns

f64 of theta per day (not per year).

§Example

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, None, 0.05, 0.2, 20/365.25, Some(0.2));
let theta = inputs.calc_theta();

Source

pub fn calc_vega(&self) -> PyResult<f64>

Calculates the vega of the option.

§Requires

s, k, r, q, t, sigma

§Returns

f64 of the vega of the option.

§Example

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, None, 0.05, 0.2, 20/365.25, Some(0.2));
let vega = inputs.calc_vega();

Source

pub fn calc_rho(&self) -> PyResult<f64>

Calculates the rho of the option.

§Requires

s, k, r, q, t, sigma

§Returns

f64 of the rho of the option.

§Example

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, None, 0.05, 0.2, 20/365.25, Some(0.2));
let rho = inputs.calc_rho();

Source

pub fn calc_iv(&self, tolerance: f64) -> PyResult<f64>

Calculates the implied volatility of the option. Tolerance is the max error allowed for the implied volatility, the lower the tolerance the more iterations will be required. Recommended to be a value between 0.001 - 0.0001 for highest efficiency/accuracy. Initializes estimation of sigma using Brenn and Subrahmanyam (1998) method of calculating initial iv estimation. Uses Newton Raphson algorithm to calculate implied volatility.

§Requires

s, k, r, q, t, p

§Returns

f64 of the implied volatility of the option.

§Example:

use blackscholes::Inputs;
let inputs = Inputs::new(OptionType::Call, 100.0, 100.0, Some(10), 0.05, 0.02, 20.0 / 365.25, None);
let iv = inputs.calc_iv(0.0001);