feat: 2F CIR

Author: dancixx

README.md

@@ -25,7 +25,6 @@ The library is organized into several modules, each targeting specific areas of
 
 Planned features and models under development:
 - **Barndorff-Nielsen & Shephard Model**: A stochastic volatility model with non-Gaussian Ornstein-Uhlenbeck processes.
-- **Multi-factor CIR Model**: Extends the CIR model to multiple factors, providing greater flexibility in interest rate modeling.
 - **Brace-Gatarek-Musiela (BGM) Model**: A market model for interest rates, modeling the evolution of forward rates.
 - **Wu-Zhang Model**: A stochastic volatility model with jumps in returns and volatility.
 - **Affine Models**: A class of models where yields are affine functions of factors, facilitating analytical solutions.

src/stochastic/interest/cir_2f.rs

@@ -0,0 +1,33 @@
+use impl_new_derive::ImplNew;
+use ndarray::Array1;
+
+use crate::stochastic::Sampling;
+
+use super::cir::CIR;
+
+#[derive(ImplNew)]
+pub struct CIR2F {
+  pub x: CIR,
+  pub y: CIR,
+  pub phi: fn(f64) -> f64,
+}
+
+impl Sampling<f64> for CIR2F {
+  fn sample(&self) -> Array1<f64> {
+    let x = self.x.sample();
+    let y = self.y.sample();
+
+    let dt = self.x.t.unwrap_or(1.0) / (self.n() - 1) as f64;
+    let phi = Array1::<f64>::from_shape_fn(self.n(), |i| (self.phi)(i as f64 * dt));
+
+    x + y * phi
+  }
+
+  fn n(&self) -> usize {
+    self.x.n()
+  }
+
+  fn m(&self) -> Option<usize> {
+    self.x.m()
+  }
+}