RustQuant 0.0.4

#![deny(missing_docs)]

use crate::stochastics::*;

/// Struct containing the Ornstein-Uhlenbeck process parameters.
#[derive(Debug)]
pub struct CoxIngersollRoss {
    /// The long-run mean ($\mu$).
    pub mu: f64,

    /// The diffusion, or instantaneous volatility ($\sigma$).
    pub sigma: f64,

    /// Mean reversion parameter ($\theta$).
    /// Defines the speed at which the process reverts to the long-run mean.
    pub theta: f64,
}

impl CoxIngersollRoss {
    /// Create a new Cox-Ingersoll-Ross process.
    pub fn new(mu: f64, sigma: f64, theta: f64) -> Self {
        assert!(sigma >= 0.0);
        Self { mu, sigma, theta }
    }
}

impl StochasticProcess for CoxIngersollRoss {
    fn drift(&self, x: f64) -> f64 {
        self.theta * (self.mu - x)
    }

    fn diffusion(&self, x: f64) -> f64 {
        self.sigma * x.sqrt()
    }
}

// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
// TESTS
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

#[cfg(test)]
mod tests {
    use super::*;
    use crate::helpers::*;

    #[test]
    fn test_cox_ingersoll_ross() -> Result<(), Box<dyn std::error::Error>> {
        let cir = CoxIngersollRoss::new(0.15, 0.45, 0.01);

        let output = cir.euler_maruyama(10.0, 0.0, 0.5, 1000, 2, false);

        let file1 = "./Images/CIR1.png";
        plot_vector((&output.trajectories[0]).clone(), file1).unwrap();

        let file2 = "./Images/CIR2.png";
        plot_vector((&output.trajectories[1]).clone(), file2)
    }
}