pypomp.models.spx¶
- pypomp.models.spx()[source]¶
Creates a POMP model for the S&P 500 stock index data.
This function constructs a Partially Observed Markov Process (POMP) model for analyzing the S&P 500 stock index data. The model uses a stochastic volatility framework where the volatility follows a mean-reverting process and the log returns follow a normal random walk with time-varying variance.
- Returns:
A POMP model object containing, among other things:
ys: S&P 500 log returns data.
theta: Model parameters including mu, kappa, theta, xi, rho, and V_0.
covars: Covariates used in the model. In this case, the log returns of the S&P 500 stock index at the previous time step.
- Return type: