Purpose: The study examined the volatility of daily market price of listed property stocks on Johannesburg Stock Exchange (JSE) for 10year period (2008-2017). The primary aim of the study is to investigate the volatility pattern of the daily market price; in an attempt to document and model the nature of volatility characterised with the daily price of the listed property stock market for informed investment decision making.

Design/Methodology/Approach- The study used daily price from January 2, 2008 to December 29, 2017 of twelve (12) quoted property companies out of the twenty seven (27) listed on Johannesburg Stock Exchange (SA REIT Association, 2020). The property stocks were selected based on the quoted property companies that have sufficient published data on daily price for the period under review. The data were obtained from the JSE published statistical bulletin. The study computed the average daily price of the selected (12) property stocks and was used as proxy for daily market price for property stock market in the analysis. The study deployed mean, standard deviation, maximum and minimum analytical tools for descriptive statistics, Augmented Dickey-Fuller (ADF) and Kwiatkowski-Phillips-Schmidt- Shin (KPSS); Jarque-Bera, Breusch-Godfrey LM and Heteroskedasticity tests for unit root, normal distribution, autocorrelation and ARCH effect tests respectively. The diversification benefits and modelling of SA-REIT market price volatility were analysed using correlation matrix and generalised autoregressive conditional heteroskedasticity (GARCH 1, 1)

Finding: The daily price of the selected property stocks were stationary at 1st difference I(1) as indicated by results of ADF and KPSS unit root tests (p<.05); the p-value for LM autocorrelation and heteroskedasticity tests were significant (p<.05) indicating that the series is characterised with autocorrelation and ARCH effect; and exhibited non- normal distribution pattern as reported by Jarque-Bera statistics (p<.05). The correlation matrix showed strong diversification benefits between EQUP and INTU (-0.809) property stocks. Analysis of residual estimate of the series documents the evidence of volatility characterised with prolong high and low clustering pattern. The GARCH model reported that, the previous days information of both the daily market price (ARCH term) and the volatility (GARCH term) have positive and significant (p<.05) effect on current day's market price volatility in the property stock market. The result of the model implies that investment in property stock market is strongly driven by positive news on daily price than negative shock; meaning that South Afric ponse to good news on daily market price than bad news when thinking of investing in listed property company shares on Johannesburg Stock Exchange.

Practical implications: The study documents and models the statistical significant influence of conditional variance (volatility) of daily price of South Africa property stock market.

Originality/Value: The study added to the exiting body of knowledge by documenting the volatility pattern and model structure of SA-property stock markets for informed investment decision making.