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arch 6.3.0

arch.univariate.LS.x

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arch 6.3.0

Univariate Volatility Models
Univariate Volatility Models
- Introduction
- Examples
- Forecasting
- Volatility Forecasting
- Value-at-Risk Forecasting
- Forecasting Scenarios
- Forecasting with Exogenous Variables
- Mean Models
  Mean Models
  - arch.univariate.ZeroMean
  - arch.univariate.ConstantMean
  - arch.univariate.ARX
  - arch.univariate.HARX
  - arch.univariate.LS
    
    arch.univariate.LS
    
    Carch.univariate.LS
    
    Carch.univariate.LS
    
    arch.univariate.LS.bounds
    
    arch.univariate.LS.compute_param_cov
    
    arch.univariate.LS.constraints
    
    arch.univariate.LS.fit
    
    arch.univariate.LS.fix
    
    arch.univariate.LS.forecast
    
    arch.univariate.LS.parameter_names
    
    arch.univariate.LS.resids
    
    arch.univariate.LS.simulate
    
    arch.univariate.LS.starting_values
    
    arch.univariate.LS.distribution
    
    arch.univariate.LS.name
    
    arch.univariate.LS.num_params
    
    arch.univariate.LS.volatility
    
    arch.univariate.LS.x arch.univariate.LS.x
    Contents
    
    PLS.x
    
    arch.univariate.LS.y
  - (G)ARCH-in-mean Models
  - Writing New Mean Models
- Volatility Processes
- Using the Fixed Variance Process
- Distributions
- Results
- Utilities
- Background and References
Bootstrapping
Multiple Comparison Problems
Unit Root Testing
Cointegration Analysis
Long-run Covariance Estimation
API Reference
Change Log

Contents

PLS.x

arch.univariate.LS.x¶

property LS.x : ndarray | DataFrame | None¶: Gets the value of the exogenous regressors in the model

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© Copyright 2021, Kevin Sheppard.

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