The Alpha Power Transformed Logistic Distribution: Properties, application and VaR Estimation
نویسندگان
چکیده
AbstractIn this paper, a new three-parameter distribution, which is member of the Alpha Power Transformed Family distributions, introduced. The distribution generalization logistic model called alpha power transformed (APTL) distribution. Some mathematical properties like moments, quantile function, median, skewness, kurtosis, Rényi entropy, and order statistics are discussed. parameters estimated using maximum likelihood estimation method simulation study performed to investigate effectiveness estimates. usefulness flexibility APTL in modelling financial data investigated two portfolio stock indices, namely NASDAQ New York both from United States market. Based on selection criteria, we able establish empirically that best for sets, among various distributions compared study. For each data, value-at-risk estimates give smaller expected loss at high confidence levels comparison those other distributions.Keywords: family distributions; distribution; estimation; investments; value-at-risk. AbstrakPada artikel ini, diperkenalkan distribusi baru dengan tiga parameter yang merupakan anggota dari keluarga Transformed. Distribusi ini generalisasi logistik disebut Transform Logistics (APTL). Selain itu, dibahas pula beberapa sifat matematika tersebut yaitu momen, fungsi kuantil, kemiringan, entropi Rényi, dan statistik terurut. Parameter diestimasi menggunakan metode studi simulasi dilakukan untuk menyelidiki keefektifan estimasi. Kegunaan fleksibilitas dalam pemodelan keuangan diselidiki dua indeks saham portofolio pasar Amerika Serikat York. Berdasarkan kriteria pemilihan model, secara empiris, dihasilkan bahwa adalah terbaik memodelkan set di antara berbagai dibandingkan pada penelitian ini. Untuk setiap estimasi kuantil memberikan kerugian diharapkan lebih kecil tingkat kepercayaan tinggi lainnya.Kata Kunci: transformed; logistik; investasi portofolio; 2020MSC: 62E10.
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ژورنال
عنوان ژورنال: InPrime Journal
سال: 2023
ISSN: ['2716-2478']
DOI: https://doi.org/10.15408/inprime.v5i1.31035