Struct VolatilityKernel 

pub struct VolatilityKernel<State = Untrained> { /* private fields */ }

Kernel method for volatility modeling and forecasting

This kernel focuses on volatility features using various volatility models.

References

• Bollerslev (1986): “Generalized Autoregressive Conditional Heteroskedasticity”

Implementations

impl VolatilityKernel<Untrained>

pub fn new(n_components: usize, model: VolatilityModel) -> Self

Create a new volatility kernel

pub fn decay_factor(self, decay_factor: Float) -> Self

Set the decay factor for EWMA

Trait Implementations

impl Default for VolatilityKernel<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ()> for VolatilityKernel<Untrained>

type Fitted = VolatilityKernel<Trained>

The fitted model type

fn fit(self, x: &Array2<Float>, _y: &()) -> Result<Self::Fitted>

Fit the model to the provided data with validation

fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>

where Self: Sized,

Fit with custom validation and early stopping

impl Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for VolatilityKernel<Trained>

fn transform(&self, x: &Array2<Float>) -> Result<Array2<Float>>

Transform the input data