Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data - Hamza, Abubakar (2023)
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.