ou_fit: Estimate parameters of an Ornstein-Uhlenbeck process.

In mlysy/svcommon: Fast Inference for Common-Factor Stochastic Volatility Models

Estimate parameters of an Ornstein-Uhlenbeck process.

Description

Calculate the MLE using least-squares on the one-step Euler approximation.

Usage

ou_fit(Xt, dt)

Arguments

Xt	Vector of log-prices.
dt	Interobservation time.

Details

The Ornstein-Uhlenbeck process is described by the stochastic differential equation

dXt = - gamma (Xt - mu) dt + sigma dBt.

Here, the MLE is computed analytically from the Euler approximation

X_{t+1} | X_t ~ N(X_t - gamma (X_t - mu) dt, sigma^2 dt).

Value

A named vector containing the maximum likelihood estimate of the OU parameters.

mlysy/svcommon documentation built on Sept. 15, 2024, 1:15 a.m.