Journal article Open Access

# New Log Likelihood Estimation Function

Louangrath, P.

### Citation Style Language JSON Export

{
"publisher": "Zenodo",
"DOI": "10.5281/zenodo.1320774",
"container_title": "Inter. J. Res. Methodol. Soc. Sci",
"language": "eng",
"title": "New Log Likelihood Estimation Function",
"issued": {
"date-parts": [
[
2015,
6,
30
]
]
},
"abstract": "<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 <em>X</em>, 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.</p>",
"author": [
{
"family": "Louangrath, P."
}
],
"page": "36-47",
"volume": "1",
"version": "1A",
"type": "article-journal",
"issue": "2",
"id": "1320774"
}
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