<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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.</p>
</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.

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

Department of Fundamental and Applied Science

Aliko Dangote University of Science and Technology

Department of Informatics Engineering, Faculty of Engineering

Department of Mathematics and Computer Science

Real Estate Management and Valuation

This work is licensed under the Creative Commons Attribution 4.0 International License.

The presence of volatility in residential property market prices helps investors generate substantial profit while also causing fear among investors since high...

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

Published Online: Sep 07, 2023

Page range: 20 - 31

DOI: https://doi.org/10.2478/remav-2023-0018

Keywords
residential property price, GARCH model, EGARCH model GJR-GARCH model, volatility forecasting

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

This work is licensed under the Creative Commons Attribution 4.0 International License.

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

Published Online: Sep 07, 2023

Page range: 20 - 31

DOI: https://doi.org/10.2478/remav-2023-0018

Keywordsresidential property price, GARCH model, EGARCH model GJR-GARCH model, volatility forecasting

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

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
residential property price, GARCH model, EGARCH model GJR-GARCH model, volatility forecasting