Results 11 to 20 of about 15,002 (270)
Bayesian QTL mapping using skewed Student-t distributions [PDF]
Genetics Selection Evolution, 2002 In most QTL mapping studies, phenotypes are assumed to follow normal distributions. Deviations from this assumption may lead to detection of false positive QTL. To improve the robustness of Bayesian QTL mapping methods, the normal distribution for residuals is replaced with a skewed Student-t distribution. The latter distribution is able to account for
von Rohr, Peter, Hoeschele, Ina
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East Asian Economic Review, 2007 This paper investigates the relevance of skewed Student-t distributions in capturing long memory volatility properties in the daily return series of Japanese financial data (Nikkei 225 Index and JPY-USD exchange rate).
Seong¡-Min Yoon , Sang-Hoon Kang
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Objective Bayesian modelling of insurance risks with the skewed Student‐t distribution [PDF]
Applied Stochastic Models in Business and Industry, 2017 Insurance risks data typically exhibit skewed behaviour. In this paper, we propose a Bayesian approach to capture the main features of these data sets. This work extends a methodology recently introduced in the literature by considering an extra parameter that captures the skewness of the data.
Leisen F., Marin J. M., Villa C.
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MODEL VOLATILITAS ARCH(1) DENGAN RETURN ERROR BERDISTRIBUSI SKEWED STUDENT-T [PDF]
Jurnal MIPA, 2016 Model volatilitas Autoregressive Conditional Heteroscedasticity (ARCH)lag 1, dimana return error berdistribusi skewed Student-t, diaplikasikan untuk runtun waktu return kurs beli harian Euro (EUR) dan Japanese Yen (JPY) terhadap Indonesian Rupiah (IDR ...
E. D. Saputri +2 more
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SKEW NORMAL AND SKEW STUDENT-T DISTRIBUTIONS ON GARCH(1,1) MODEL
MEDIA STATISTIKA, 2021 The Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) type models have become important tools in financial application since their ability to estimate the volatility of financial time series data. In the empirical financial literature, the presence of skewness and heavy-tails have impacts on how well the GARCH-type models able to ...
Didit Budi Nugroho +2 more
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The multivariate slash and skew-slash student t distributions [PDF]
Journal of Statistical Distributions and Applications, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tan, Fei, Tang, Yuanyuan, Peng, Hanxiang
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A Jump Diffusion Model with Fast Mean-Reverting Stochastic Volatility for Pricing Vulnerable Options
Discrete Dynamics in Nature and Society, 2023 The Black–Scholes–Merton option pricing model is a classical approach that assumes that the underlying asset prices follow a normal distribution with constant volatility.
Joy K. Nthiwa +2 more
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COVID-19 Pandemic and Volatility Persistence of the Nigerian Crude Oil Price
Journal of Applied Sciences and Environmental Management, 2022 Impacts of COVID-19 pandemic on the global economy cannot be overemphasized, especially with Nigeria, which largely depends on crude oil as a major source of her revenue.
T. K. Samson, M. A. Raheem
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Scientific African, 2023 This study introduces a new conditional innovation density called the generalized odd generalized exponentiated skew-t (GOGEST) distribution for the generalized autoregressive conditional heteroscedasticity (GARCH) volatility models.
O.D. Adubisi, A. Abdulkadir, D.J. Adashu
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Copernican Journal of Finance & Accounting, 2015 The modelling of market returns can be especially problematical in emerging and frontier financial markets given the propensity of their returns to exhibit significant non-normality and volatility asymmetries.
Heitham Al-Hajieh +3 more
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