compute_ekop_orig_lik: Computes the original likelihood of the EKOP model

Description Usage Arguments Value References See Also

Description

Calling compute_ekop_orig_lik() computes the likelihood from the original likelihood function of the model of Easley et al. (1996). This likelihood function can become unstable in settings with high trading volumes. For this case the bayespin-package provides a modified version of the likelihood function, compute_ekop_lik(), first proposed in the paper by Easley et al. (2002) that is often more stable during optimizaton.

Optimization is performed over the logit transformation of the ratios alpha and delta and therefore these parameter logits get transformed in the likelihood function via the logistic transformation exp()/(1+exp()).

Usage

1
compute_ekop_orig_lik(data, par, T, methodLik = c("precise", "approx"))

Arguments

data

A data.frame containing the trades data in the following order: mis-specified buys, mis-specified sells, buyer-initiated trades, seller-initiated trades and finally the total number of trades on a specific trading day.

par

A vector specifying the parameter values at which the function should be evaluated. The parameter order is alpha, epsilon, delta, and mu.

T

A double indicating the length of a trading day in minutes.

methodLik

A character specifying, if undefined function values in optimization should be approximated by large defined values (1e+6). This can help to make maximum likelihood estimation more stable.

Value

A double holding the likelihood value of the data and parameter values passed in.

References

See Also


simonsays1980/bayespin documentation built on Dec. 23, 2021, 2:25 a.m.