Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data

vii,64p

Zapisane w:
Opis bibliograficzny
1. autor: Ojemola, Oladipupo Ibukun
Format: Praca dyplomowa
Język:angielski
Wydane: Mathematics,Obafemi Awolowo University. 2023
Hasła przedmiotowe:
Dostęp online:https://ir.oauife.edu.ng/123456789/5407
Etykiety: Dodaj etykietę
Nie ma etykietki, Dołącz pierwszą etykiete!
_version_ 1810764575745769472
author Ojemola, Oladipupo Ibukun
author_facet Ojemola, Oladipupo Ibukun
author_sort Ojemola, Oladipupo Ibukun
collection DSpace
description vii,64p
format Thesis
id oai:ir.oauife.edu.ng:123456789-5407
institution My University
language English
publishDate 2023
publisher Mathematics,Obafemi Awolowo University.
record_format dspace
spelling oai:ir.oauife.edu.ng:123456789-54072023-05-13T18:12:25Z Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data Ojemola, Oladipupo Ibukun Exponential power Multivariate exponential Stock exchange Algorithm vii,64p This study obtained the parameter estimates of the multivariate exponential power distribution and fitted the model on stock returns data of three stocks on the Nigerian Stock Exchange market and compared the Value at Risk forecasts when multivariate exponential power mixture distribution was the underlying distribution of the data with the multivariate normal mixture Value at Risk. This was with a view to reducing possible loss on financial assets. The parameters of the multivariate normal mixture and multivariate exponential power mixture model were obtained by Expectation Maximization algorithm. The method of probability fitting was used to fit three company shares quoted on the Nigerian Stock Exchange market and the best fit model was determined using Pearson Chi-Square approach. Value-at-Risk (VaR) forecasts were obtained using the fitted model parameter estimates of the multivariate power mixture model and compared with the multivariate normal mixture model. After 25 iterations, the parameter estimates and the log-likelihood of the multivariate exponential power mixture model were obtained. Also, at both 95% and 99% confidence levels, it was discovered that the estimates for the VaR were lower when the multivariate mixture normal model was assumed than when the multivariate exponential power mixture model was assumed. The study concluded that Value at Risk forecast of a portfolio of asset returns would be more reliable if exponential power distribution was modelled on such data. 2023-05-13T16:55:55Z 2023-05-13T16:55:55Z 2015 Thesis Ojemola,O.I(2015).Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data. Obafemi Awolowo University. https://ir.oauife.edu.ng/123456789/5407 en application/pdf Mathematics,Obafemi Awolowo University.
spellingShingle Exponential power
Multivariate exponential
Stock exchange
Algorithm
Ojemola, Oladipupo Ibukun
Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data
title Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data
title_full Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data
title_fullStr Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data
title_full_unstemmed Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data
title_short Expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data
title_sort expectation maximization algorithm for multivariate exponential power mixture model with applications to financial data
topic Exponential power
Multivariate exponential
Stock exchange
Algorithm
url https://ir.oauife.edu.ng/123456789/5407
work_keys_str_mv AT ojemolaoladipupoibukun expectationmaximizationalgorithmformultivariateexponentialpowermixturemodelwithapplicationstofinancialdata