Modeling right-skewed financial data streams: A likelihood inference based on the generalized Birnbaum–Saunders mixture model

Naderi, Mehrdad; Hashemi, Farzane; Bekker, Andriëtte; Jamalizadeh, Ahad

doi:10.1016/j.amc.2020.125109

Cited by 8 publications

(2 citation statements)

References 63 publications

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“…Birnbaum-Saunders (BS) regression models have proven to be good alternatives in insurance data modeling; see Leiva (2016) and Naderi et al (2020). These data show positive asymmetry and heavy tails.…”

Section: Introductionmentioning

confidence: 99%

Scale-mixture Birnbaum-Saunders quantile regression models applied to personal accident insurance data

Dasilva¹,

Saulo²

2021

Preprint

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The modeling of personal accident insurance data has been a topic of extreme relevance in the insurance literature. In general, the data often exhibit positive asymmetry and heavy tails and non-quantile Birnbaum-Saunders regression models have been used in the modeling strategy. In this work, we propose a new quantile regression model based on the scale-mixture Birnbaum-Saunders distribution, which is reparametrized by inserting a quantile parameter. The maximum likelihood estimates of the model parameters are obtained via the EM algorithm. Two Monte Carlo simulation studies were performed using the R software. The first study aims to analyze the performance of the maximum likelihood estimates, the information criteria AIC, AICc, BIC, HIC, the root of the mean square error, and the randomized quantile and generalized Cox-Snell residuals. In the second simulation study, the size and power of the the Wald, likelihood ratio, score and gradient tests are evaluated. The two simulation studies were conducted considering different quantiles of interest and sample sizes. Finally, a real insurance data set is analyzed to illustrate the proposed approach.

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Section: Introductionmentioning

confidence: 99%

Scale-mixture Birnbaum-Saunders quantile regression models applied to personal accident insurance data

Dasilva¹,

Saulo²

2021

Preprint

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“…Hashemi et al [15] proposed the normal mean-variance Lindley BS distribution. Naderi et al [24] proposed the normal mean-variance generalized BS distribution. Naderi et al [25] presented the skew-Laplace BS distribution.…”

Section: Introductionmentioning

confidence: 99%

The Weibull Birnbaum-Saunders Distribution And Its Applications

Benkhelifa¹

2020

Stat., optim. inf. comput.

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A new lifetime model, with four positive parameters, called the Weibull Birnbaum-Saunders distribution is proposed. The proposed model extends the Birnbaum-Saunders distribution and provides great flexibility in modeling data in practice. Some mathematical properties of the new distribution are obtained including expansions for the cumulative and density functions, moments, generating function, mean deviations, order statistics and reliability. Estimation of the model parameters is carried out by the maximum likelihood estimation method. A simulation study is presented to show the performance of the maximum likelihood estimates of the model parameters. The flexibility of the new model is examined by applying it to two real data sets.

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Optimal portfolio design of energy storage devices with financial and physical right market

et al. 2021

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Modeling right-skewed financial data streams: A likelihood inference based on the generalized Birnbaum–Saunders mixture model

Cited by 8 publications

References 63 publications

Scale-mixture Birnbaum-Saunders quantile regression models applied to personal accident insurance data

Scale-mixture Birnbaum-Saunders quantile regression models applied to personal accident insurance data

The Weibull Birnbaum-Saunders Distribution And Its Applications

Optimal portfolio design of energy storage devices with financial and physical right market

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