Research Article

Incorporating simulated annealing algorithm in the Weibull distribution for valuation of investment return of Malaysian property development sector

¹ School of Mathematical Sciences, Universiti sains Malaysia, Penang, Malaysia
² Department of Mathematics, Isa Kaita College of Education, Dutsin-Ma, Nigeria

^* e-mail: zeeham4u2c@yahoo.com

Received: 6 June 2021
Accepted: 28 September 2021

Abstract

In this study, a simulated annealing algorithm(SAA) has been incorporated in the Weibull Distribution (WD) for Valuation of Investment Return. The purpose is to examine the behaviour of investment's attractiveness in the Malaysian property development sector (MPDS) for a long-term investment period. The research intends is to produce parameters estimates of the WD using MIRR data extracted from the financial report of MPDS for 5 years investment period. The shape parameter of the WD reflects the effectiveness in maximizing the investment performance on MPDS with lower returns and is represented as the slope of the fitted line on a Weibull probability plot. The estimated results obtained using the Simulated annealing algorithm (SAA) has been compared with Differential Evolution (DE) and other existing estimation methods in terms of root mean square error (R-MSE) and coefficient of determination (R-Square). The findings revealed that Weibull distribution parameters estimated via Simulated annealing algorithm have good agreement with parameters estimated via Differential Evolution (DE) and other existing methods based on the transformed MIRR data from the MPDS. The study is expected to provide an overview of the investment behaviour for the long-term investment return in the MPDS. Therefore, SAA in estimating the WD parameters can serve as a good alternative approach for the assessment of the investment potential using MIRR data. The study will be extended to accommodate the growth rate arising from the financial data such as investment growth and insurance claim data.