Journal article Open Access

New Log Likelihood Estimation Function

Louangrath, P.

This paper provides a New Log-Likelihood Estimator (NLLE) function as a tool for value approximation. We improved the accuracy of the log MLE in two steps (i) determine the log likelihood of a random variable X, and (ii) adjust the estimate by a factor of . In-Sample testing was accomplished by using daily SET100 indices over a period of 60 days. Out-of-sample data were used for confirmatory verification; out-of-sample data came from 5 major stock markets: NASDAQ, DOW, SP500, DAX, and CAC40. Relevant tests used to compare the results of the proposed NLLE include Cramer-Rao Lower Bound (CRLB), Likelihood Ratio Test, Wald statistic, and Lagrange Multiplier (Score Statistic). It was found that NLLE is more efficient than the conventional MLE. It gives practitioners a better tool for value estimation in many fields of natural and social sciences.

Files (133.6 kB)
Name Size
ARTICLE 3, Vol 1, No 2, New Log Likelihood Estimation Function.pdf
133.6 kB Download
All versions This version
Views 2520
Downloads 3327
Data volume 4.0 MB3.6 MB
Unique views 2219
Unique downloads 2725


Cite as