Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data
An accurate analysis of financial data is vital to justify sustainability for investment potential in a company. Weibull distributions can be used to examine investment behaviour due to their flexibility to be transformed into other types of distribution. However, the selection of the most suitab...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | http://eprints.usm.my/61251/1/24%20Pages%20from%20ABUBAKAR%20HAMZA.pdf http://eprints.usm.my/61251/ |
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| Summary: | An accurate analysis of financial data is vital to justify sustainability for
investment potential in a company. Weibull distributions can be used to examine
investment behaviour due to their flexibility to be transformed into other types of
distribution. However, the selection of the most suitable estimators is still a
challenging task. The present study proposes a simulated annealing algorithm (SA) in
estimating the parameters of Weibull distribution with application to modified internal
rate of return data (MIRR).The objective is to examine the investment potential of the
shari’ah compliance companies of the Malaysia property sector (MPS). The MIRR
were computed based on the data extracted from the companies’ financial reports from
2010 to 2018. The performance of the SA algorithm has been explored in terms of
accuracies and estimation errors. The finding reveals that the Weibull distribution is
well-suited to describing the investment behaviour of the MPS based on the estimates
via the SA algorithm. Therefore, purchasing shares in this sector is very attractive for
a long-term investment period, but may have a high risk of committing it as a result of
fluctuations in the mean and variance of the estimate. Additionally, the two-parameter
Weibull distribution has been extended by incorporating additional parameters to
capture the uncertainty behaviour in the financial data. |
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