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

Suleiman, A.A. and Othman, M. and Daud, H. and Abdullah, M.L. and Kadir, E.A. and Kane, I.L. and Husin, A. (2023) Forecasting the Volatility of Real Residential Property Prices in Malaysia: A Comparison of Garch Models. Real Estate Management and Valuation, 31 (3). pp. 20-31. ISSN 23005289

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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. © 2023 Ahmad Abubakar Suleiman et al., published by Sciendo.

Item Type: Article
Impact Factor: cited By 0
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 04 Oct 2023 08:42
Last Modified: 04 Oct 2023 08:42

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