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Publikācija: Approximation of Distribution of Log-Returns with Normal Inverse Gaussian Process

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Nosaukums oriģinālvalodā Approximation of Distribution of Log-Returns with Normal Inverse Gaussian Process
Pētniecības nozare 1. Dabaszinātnes
Pētniecības apakšnozare 1.1. Matemātika
Autori Oskars Rubenis
Andrejs Matvejevs
Atslēgas vārdi Normal Inverse Gaussian distribution, Normal Inverse Gaussian process, log-returns, maximum likelihood estimation
Anotācija Normal inverse Gaussian (NIG) distribution is a quit a new distribution introduced in 1997. This is distribution, which describes evolution of NIG process. It appears that in many cases NIG distribution describes log-returns of stock prices with a high accuracy. Unlike normal distribution, it has higher kurtosis, which is necessary to fit many historical returns. This gives the opportunity to construct precise algorithms for hedging risks of options. The aim of this work is to evaluate how good NIG distribution can reproduce stock price dynamics and to illuminate future fields of applications.
DOI: 10.1109/ITMS.2018.8552949
Hipersaite: https://ieeexplore.ieee.org/document/8552949 
Atsauce Rubenis, O., Matvejevs, A. Approximation of Distribution of Log-Returns with Normal Inverse Gaussian Process. No: 2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2018), Latvija, Riga, 9.-14. oktobris, 2018. Piscataway: IEEE, 2018, 63.-65.lpp. ISBN 978-1-7281-0099-9. e-ISBN 978-1-7281-0098-2. Pieejams: doi:10.1109/ITMS.2018.8552949
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ID 28901