Estimating parameters in autoregressive models in non-normal situations: symmetric innovations

Tiku, M. L.; Wong, Wing-Keung; Bian, Guorui

doi:10.1080/03610929908832300

Cited by 56 publications

(27 citation statements)

References 39 publications

(38 reference statements)

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“…Using the US data, Tsuji (2012b) quantitatively investigated the relations of the industry portfolio returns and Fama and French's (1993) three factor returns; however, the study did not employ non-linear estimations of asset pricing models. In addition, there are such related interesting studies as Tiku et al (1999) and Bai et al (2010Bai et al ( , 2011; however, based on this recent literature review, we consider that a non-linear CAPM estimation conducted as in our present study is rare and much precious.…”

Section: Introductionmentioning

confidence: 90%

A Robust Estimation of the CAPM with a Heavy-tailed Distribution

Tsuji¹

2017

IJSSS

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This study quantitatively explores the linear standard capital asset pricing model (CAPM) and a non-linear CAPM by using ten US representative firms' monthly stock returns. By the maximum likelihood estimation, we derive the following useful findings. (1) First, when the stock return distribution is fat-tailed, our non-linear CAPM application is highly effective. Because our non-linear CAPM parameters very well capture the behavior of fat-tailed returns, the non-linear CAPM estimation derives more reliable beta value estimates than the standard linear CAPM. (2) Second, conducting the Wald tests based on both the standard linear CAPM and non-linear CAPM estimators, we clarify that when the stock return distribution is fat-tailed, the Wald test result based on the non-linear CAPM estimators is more reliable than that based on the standard linear CAPM estimators.

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Section: Introductionmentioning

confidence: 90%

A Robust Estimation of the CAPM with a Heavy-tailed Distribution

Tsuji¹

2017

IJSSS

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“…On the other hand, Tiku, Wong and Bian, (1999a) derive the estimator for coefficients in a simple regression model with autocorrelated errors in which the underlying distribution is assumed to be symmetric, one of Student's t family for illustration. Wong and Bian (2005) extend the theory by considering the underlying distribution is a generalized logistic distribution.…”

Section: Robust Estimationmentioning

confidence: 99%

Moment Generating Function, Expectation and Variance of Ubiquitous Distributions with Applications in Decision Sciences: A Review

Pho

Tran

et al. 2019

SSRN Journal

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“…Their efficiency relative to the proposed MML estimators is very low. Tiku, Wong, and Bian (1999b) estimate coefficients in a simple regression model with autocorrelated errors. The underlying distribution is assumed to be symmetric, one of the Student t family for illustration.…”

Section: Other Econometric Models/testsmentioning

confidence: 99%

Management Information, Decision Sciences, and Financial Economics: A Connection

2018

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The paper provides a brief review of the connecting literature in management information, decision sciences, and financial economics, and discusses some research that is related to the three cognate disciplines. Academics could develop theoretical models and subsequent econometric models to estimate the parameters in the associated models, and analyze some interesting issues in the three related disciplines.

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Estimating parameters in autoregressive models in non-normal situations: symmetric innovations

Cited by 56 publications

References 39 publications

A Robust Estimation of the CAPM with a Heavy-tailed Distribution

A Robust Estimation of the CAPM with a Heavy-tailed Distribution

Moment Generating Function, Expectation and Variance of Ubiquitous Distributions with Applications in Decision Sciences: A Review

Management Information, Decision Sciences, and Financial Economics: A Connection

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