The Dynamic of Returns and Volatility of Malaysian Listed Property Companies in Asian Property Market

Razali, Muhammad Najib

doi:10.3846/1648715x.2015.1004656

Cited by 9 publications

(13 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, when assessed over different financial periods, the returns underperformed the market. While, Razali (2013) The results further showed that property assets exhibited diversification potential when included with bonds in a mixed-asset portfolio. However, across the efficient frontiers, property assets might not enhance optimal portfolio combination.…”

Section: Review Of Relevant Literaturementioning

confidence: 82%

Impact of Adding Securitised Property Into Mixed-Asset Portfolio in Emerging Markets: Evidence From Nigeria

Ayodele¹,

Olaleye²

2016

Sustainable Multi-Sectoral Real Estate Development in Emerging Economies - The 16th African Real Estate Society Conference

View full text Add to dashboard Cite

The paper examined the performance of securitised property and analysed its diversification benefits when added into domestic mixed-asset portfolios constructed using Naïve and MPT optimization techniques. The paper also tested the hypothesis that the performance of naïve portfolios with securitised properties is better than naïve portfolios without securitised property. Design/methods: The data comprised quarterly returns of securitised property, all share, Federal bonds, State bonds, Debentures and Treasury bills for years 2000 to 2013. Return-risk analysis was compared using mean return, standard deviation, Sharpe ratio and correlation coefficient. Preliminary analysis was conducted on the data sets to examine the stationarity using the Philip Perron unit root test. In assessing securitised property return enhancements and risk reduction benefits in mixed-asset portfolio, 24 naïve portfolios (18 with securitised property and 6 without securitised property) were constructed and the effectiveness of diversification was assessed for each portfolio. This is in addition to examining the impact of securitised property on optimal portfolios using Markowitz quadratic function. Findings: The results showed that securitised property did not offer superior returns and underperformed most other assets on risk adjusted basis. While the results of the naïve portfolio showed no statistically significant difference in portfolio performance when securitised property was included; the effect was however dependent on the percentage weightings of assets and the asset class being replaced. The MPT analysis showed that along the efficient frontier, securitised property has no percentage allocation in the mixed-asset portfolio. Practi al Implication The study has implications for investors interested in emerging markets like the Nigerian investment market. Originality: It is one of the few attempts within the context of Africa's emerging market and Nigeria in particular.

show abstract

Section: Review Of Relevant Literaturementioning

confidence: 82%

Impact of Adding Securitised Property Into Mixed-Asset Portfolio in Emerging Markets: Evidence From Nigeria

Ayodele¹,

Olaleye²

2016

Sustainable Multi-Sectoral Real Estate Development in Emerging Economies - The 16th African Real Estate Society Conference

View full text Add to dashboard Cite

show abstract

“…The uni-direction asset classes show that the influence of one asset class to another is only in one direction. Bi-directional asset classes show that the assets are strongly correlated and can influence each other in two directions (Razali, 2015).…”

Section: Methodsmentioning

confidence: 99%

Big data analytics for predictive maintenance in maintenance management

Razali

Jamaluddin

Jalil

et al. 2020

Self Cite

View full text Add to dashboard Cite

PurposeThis research attempts to highlight the concept of big data analytics in predictive maintenance for maintenance management of government buildings in Malaysia.Design/methodology/approachThis study uses several empirical analyses such as vector autoregression (VAR), vector error correction model (VECM), ARMA model and Granger causality to analyse predictive maintenance by using big data analytics concept.FindingsThe results indicate that there are strong correlations among these variables, which indicate reciprocal predictive maintenance of maintenance management job function. The findings also showed that there are significant needs of application of big data analytics for maintenance management in Putrajaya, Malaysia, to ensure the efficient maintenance of government buildings.Originality/valueThe conducted case study has demonstrated the empirical perspective which streamlines with the big data analytics' concept in maintenance, especially for analytics' support with appropriate empirical methodology

show abstract

“…And more recently in China (Azmi et al , 2018; Razali, 2015a, b), Indonesia (Azmi et al , 2018; Razali, 2015a, b), Vietnam (Azmi et al , 2018; Nguyen, 2010; Razali, 2015a, b), the Philippines (Nguyen, 2011a, b) and Malaysia (Lee and Ting, 2009; Ting, 2002), listed PCs were reported to underperform their country stock index. All the analysed markets probably have common features of emerging markets, which are unstable and underperformed respective assets in developed markets.…”

Section: Indonesian Listed Pcs’ Performance Analysismentioning

confidence: 99%

“…The impact of the GFC on listed PCs’ performance is evident worldwide, especially in the Asian countries. Particularly, Razali (2015a, b) reported the significant impact of the GFC volatility in 12 Asian countries, with a moderately high volatility of Malaysian listed PCs in the Asian property markets (Azmi et al , 2018; Razali, 2015a, b). Sri Lanka and the Philippines were the two countries which showed listed PCs outperforming bonds and underperforming stocks.…”

Section: Property Investment Implications and Conclusionmentioning

confidence: 99%

“…In terms of property research, there have been an abundance of studies on property research on the various aspects of property performance as well as its features as an investment asset class in Asia (Addae-Dapaah and Loh, 2005; Azmi et al , 2017; Bond et al , 2003; Gerlach et al , 2006; Jin et al , 2007; Liow, 2007, 2008; Liow and Adair, 2009; Liow and Sim, 2006; Mei and Hu, 2000; Nguyen, 2011a, b; Ooi and Liow, 2004; Razali, 2015a, b; Wilson et al , 2007; Wilson and Zurbruegg, 2004). Research has also been conducted for specific Asian countries such as Singapore (Liow, 2000, 2001a, b; Ong and Ng, 2009; Sing and Low, 2000), Hong Kong (Chau et al , 2001, 2003; Newell and Chau, 1996; Newell et al , 2004, 2007; Schwann and Chau, 2003), Malaysia (Azmi et al , 2018; Lee and Ting, 2009; Razali, 2015a, b; Ting, 2002), India (Newell and Kamineni, 2007), China (Newell et al , 2005), Vietnam (Nguyen, 2010) and the Philippines (Nguyen, 2011a, b). This does not only provide investors and academics an indication of the awareness and understanding of a specific property market with its significance in the mentioned context, it also provides a comprehensive overall picture of regional property investment in Asia compared to the remaining world.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The dynamics of listed property companies in Indonesia

Nguyen

Razali

2020

JPIF

Self Cite

View full text Add to dashboard Cite

Purpose As an asset class, listed property companies (PCs) in the emerging Asian markets have taken on increased significance in recent years. Investors have seen Indonesian real estate investment trusts (REITs) being regulated to become a property investment vehicle in 2007. This sees macro-environment investment in the Indonesian property market taking off to a higher level regionally. In the background, Indonesian listed PCs maintain as one of the major investment vehicles for local and international investors. It has also been the subject of investment for REITs and property investment funds in Indonesia. The purpose of this paper is to assess the dynamics of risk-adjusted performances and portfolio diversification benefits of listed PCs in a mixed-asset portfolio context in Indonesia, from July 2006 to December 2018. The sub-periods of pre-global financial crisis (GFC), GFC and post-GFC of listed PCs is also assessed. Design/methodology/approach Using monthly total returns, the risk-adjusted performance and portfolio diversification benefits of listed PCs from July 2006 to December 2018 are assessed, with extended efficient frontiers and asset allocation diagrams used to assess the role of listed PCs in a mixed-asset portfolio. Sub-period analyses are conducted to assess the post-GFC recovery of listed PCs. Findings Listed PCs delivered higher returns but carried higher risks compared to stocks before the GFC, with bonds having both the lowest returns and risks. The impact of the GFC was highest for Indonesian PCs compared to stocks, where properties did not deliver strong risk-adjusted returns. Notwithstanding the poor risk-adjusted performance, Indonesian PCs had low correlations with stocks and bonds, suggesting some level of diversification potential for stock and bond investors. Stocks outperformed listed PCs across the sub-periods and the full period. Over the post-GFC period, both stocks and listed PCs recovered from the crisis, with stocks turning around stronger. This analysis shows a prolonged recovering and slow bouncing adjustment of listed PCs from the economic changes. This research suggests selected listed PCs may be the outperformers, and, a future contract as a hedge form for listed PC to be implemented. Research limitations/implications The use of the indices of Standard & Poor’s Indonesian property total return (for listed PCs) are as follows: MSCI Indonesia total return (for stocks), Indonesia’s ten-year bond’s total return (for bonds) and Indonesia’s three-month bill total return (for cash). This is used to study the Indonesian listed PCs and may have aggregation effects in its underperformance and therefore drawing a negative outcome. The results may reflect the common fact that the majority of listed PCs in Indonesia are property developers, which also sees underperformances in other emerging country markets. Practical implications Listed PCs have been under increasingly adjusted and positively adapted regulations from the Indonesian Government over the post-GFC period. Therefore, in order to attract interest from international investors in property investment in Indonesia, listed PCs need stronger and more efficiently adapted regulations to a competitive level of respective regulations in the region and globally. Notwithstanding the poor performance in the transitional stage, Indonesian listed PCs bring some diversification benefits to local investors who are able to pick the outperformed invested PCs at the right time. Of the on-going concerns, international investors have no restrictions on holding listed PCs in the Indonesian stock market. This provides room for improvement in business performance in listed PCs as a result of regional/global competition and international management being involved. The present study delivers awareness to investors, researchers as well as policymakers on the Indonesian property market. Originality/value This paper is the first published to present a country profile of significant property vehicles (commercial property, listed PCs and REITs). It also presents empirical research analysis of the risk-adjusted performance of listed PCs and its dynamic role in a local investors’ perspective across the pre-GFC, GFC, post-GFC periods. Given the significance of listed PCs in Asia, this research highlights more information for opportunities and on-going property investment issues in Indonesia.

show abstract

The Dynamic of Returns and Volatility of Malaysian Listed Property Companies in Asian Property Market

Cited by 9 publications

References 47 publications

Impact of Adding Securitised Property Into Mixed-Asset Portfolio in Emerging Markets: Evidence From Nigeria

Impact of Adding Securitised Property Into Mixed-Asset Portfolio in Emerging Markets: Evidence From Nigeria

Big data analytics for predictive maintenance in maintenance management

The dynamics of listed property companies in Indonesia

Contact Info

Product

Resources

About