Forecasting the Volatility of Real Residential Property Prices in Malaysia: A Comparison of Garch Models

Suleiman Ahmad Abubakar, Othman Mahmod (), Daud Hanita, Abdullah Mohd Lazim, Kadir Evizal Abdul, Kane Ibrahim Lawal and Husin Abdullah
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Suleiman Ahmad Abubakar: Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, 32610, Seri Iskandar, Perak, Malaysia
Othman Mahmod: Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, 32610, Seri Iskandar, Perak, Malaysia
Daud Hanita: Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, 32610, Seri Iskandar, Perak, Malaysia
Abdullah Mohd Lazim: Management Science Research Group, Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, Kuala Terengganu, Malaysia
Kadir Evizal Abdul: Department of Informatics Engineering, Faculty of Engineering, Universitas Islam Riau, Jl. KaharuddinNasution, No.113, Marpoyan, Pekanbaru 28284, Indonesia
Kane Ibrahim Lawal: Department of Mathematics and Computer Science, Umaru Musa Yar’adua University, 2218 Katsina, Nigeria
Husin Abdullah: Universitas Islam Indragiri, Jl. Provinsi Parit 1, Tembilahan Hulu, Kabupaten Indragiri Hili, Riau 29213, Indonesia

Real Estate Management and Valuation, 2023, vol. 31, issue 3, 20-31

Abstract: The presence of volatility in residential property market prices helps investors generate substantial profit while also causing fear among investors since high volatility implies a high return with a high risk. In a financial time series, volatility refers to the degree to which the residential property market price increases or decreases during a particular period. The present study aims to forecast the volatility returns of real residential property prices (RRPP) in Malaysia using three different families of generalized autoregressive conditional heteroskedasticity (GARCH) models. The study compared the standard GARCH, EGARCH, and GJR-GARCH models to determine which model offers a better volatility forecasting ability. The results revealed that the GJR-GARCH (1,1) model is the most suitable to forecast the volatility of the Malaysian RRPP index based on the goodness-of-fit metric. Finally, the volatility forecast using the rolling window shows that the volatility of the quarterly index decreased in the third quarter (Q3) of 2021 and stabilized at the beginning of the first quarter (Q1) of 2023. Therefore, the best time to start investing in the purchase of real residential property in Malaysia would be the first quarter of 2023. The findings of this study can help Malaysian policymakers, developers, and investors understand the high and low volatility periods in the prices of residential properties to make better investment decisions.

Keywords: residential property price; GARCH model; EGARCH model GJR-GARCH model; volatility forecasting (search for similar items in EconPapers)
JEL-codes: C53 C58 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:remava:v:31:y:2023:i:3:p:20-31:n:2

DOI: 10.2478/remav-2023-0018

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