7 results for “Heavy-Tailed Distribution”

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Research ArticleOpen accessIn the keywordsESTIMATING LOSS SEVERITY DISTRIBUTION: CONVOLUTION APPROACHRo J. PakFinancial loss can be classified into two types such as expected loss and unexpected loss. A current definition seeks to separate two losses from a total loss. In this article, however, we redefine a total loss as the sum of expected and unexpended losses; then the distribution of loss can be considered as the convolution of the distributions of both … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 2 May 2014 · 6,896 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAn Empirical Study of Robust Modified Recursive Fits of Moving Average ModelsMohamed Ali Ismail, Hend A. Auda, Joe W. McKean, Mahmoud Mohamed SadekThe time-series Moving Average (MA) model is a nonlinear model; see, for example. For traditional Least Squares (LS) fits, there are several algorithms to use for computing its fit. Since the model is nonlinear, Fuller discusses a Newton-type step algorithm. proposed a recursive algorithm based on a sequence of three linear LS regressions. In this study, we robustify Koreisha and … …Journal of Mathematics and Statistics, Vol. 18, Issue 1 · 28 Jul 2022 · 5,859 accessesView PDF Cite

Research ArticleOpen accessIn the abstractLog-Moment Estimators for the Generalized Linnik and Mittag-Leffler Distributions with Applications to Financial ModelingDexter O. Cahoy, Wojbor A. WoyczyńskiWe propose formal estimation procedures for the parameters of the generalized, heavy-tailed three-parameter Linnik gL(α, µ, δ) and Mittag-Leffler gML(α, µ, δ) distributions. The paper also aims to provide guidance about the different inference procedures for the different two-parameter Linnik and Mittag-Leffler distributions in the current literature. The estimators are derived from the moments of the log-transformed random variables and … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 1 Aug 2018 · 7,355 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Study on the Behavior of Volatility in Saudi Arabia Stock Market Using Symmetric and Asymmetric GARCH ModelsAjab Al Freedi, Ahmed Shamiri, Zaidi IsaProblem statement: This study examines several stylized facts (heavy-tailedness, leverage effect and persistence) in volatility of stock price returns exploiting symmetric and asymmetric GARCH family models for Saudi Arabia. Approach: This study is carried out using closing stock market prices over 15 years covering the period 1 January 1994 to 31 March 2009. The sample period is divided into three … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 7 Feb 2012 · 7,577 accessesView PDF Cite

Research ArticleOpen accessIn the abstractModeling and Forecasting Volatility of the Malaysian Stock MarketsAhmed Shamiri, Zaidi IsaProblem statement: One of the main purposes of modeling variance is forecasting, which is crucial in many areas of finance. Despite the burgeoning interest in and evaluation of volatility forecasts, a clear consensus on witch volatility model/or distribution specification to use has not yet been reached. Therefore, the out of-sample forecasting ability should be a natural model selection criterion for … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 7,900 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Simple Robust Control Chart Based on MADMoustafa Omar Ahmed Abu-ShawieshControl charts are one of the most powerful tools used to detect aberrant behavior in industrial processes. The Shewhart S-control chart is one of the most widely used statistical process control techniques developed to control the process variability based on the fundamental assumption that the underlying distribution of the quality characteristic is normal. When the underlying normality assumption is not … …Journal of Mathematics and Statistics, Vol. 4, Issue 2 · 30 Jun 2008 · 14,254 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Generalized Discrete-Time Long Memory Volatility Model for Financial Stock ExchangeChin Wen CheongWe proposed a simple way to combine a few long memory models in financial market volatility modeling using daily, range and high frequency data. This model was able to fit the return, range of daily return or realized volatility under a parametric heavy-tailed distribution. Model was flexible to include additional volatility information as the contemporaneous variables. Empirical results found that … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 6,869 accessesView PDF Cite