Macroeconomic risk factors in Australian commercial real estate, listed property trust and property sector stock returns

Rehman

Economic Research-Ekonomska Istraživanja

et al. 2016

This study analyses risk-return trade-off and behaviour of various volatility dynamics including: volatility, its persistence, mean reversion and speed of mean reversion along with asymmetry and leverage effect on the Pakistani stock market by employing aggregate (aggregate market level) and disaggregate (sectoral level) monthly data for the period from 1998 to 2012. Three generalised autoregressive conditional heteroscedasticity models were applied: GARCH (1,1) for various volatility dynamics; EGARCH for asymmetric and leverage effect and GARCH-M for pricing of risk. The outcomes of the study are as follows: first, the volatility shocks are quite persistent but with varying degrees across the sectors. Both the ARCH effect (short-term effect) and GARCH effect (long-term effect) play their role in generating conditional future stock returns volatility. Further, overall the volatility process is mean reverting; however, the speed of mean reversion varies across the sectors. Secondly, the current study finds little evidence of asymmetry and leverage effect at both aggregate and disaggregates data. Thirdly, the pricing of risk (positive risk premium) is also evident, particularly at the disaggregate data in the Pakistani stock market. Finally, this research study sets the implications for both the policy makers and investors.

Section: Data and Descriptive Statisticsmentioning

confidence: 99%

Pricing of risk and volatility dynamics on an emerging stock market: evidence from both aggregate and disaggregate data

Rehman

Economic Research-Ekonomska Istraživanja

et al. 2016

Investment Management and Financial Innovations

“…West and Worthington (2006) use the GARCH-M approach to empiri-cally demonstrate that the macro-economy exhibits a significantly positive relationship with the return of REITs and that certain variables, such as the long-run interest rate, the short-run interest rate, unexpected inflation and the construction index, demonstrate particularly high correlations with commercial real estate returns. Hoesli and Reka (2015) empirically show that there exists the risk of contagion between REITs and stocks in the United States.…”

mentioning

confidence: 99%

The impact of macroeconomic factors on the real estate investment trust index return on Japan, Singapore and China

Fang

Chang

Lee

et al. 2016

The impact of macroeconomic factors on the real estate investment trust index return on Japan, Singapore and China AbstractThis study contributes to the existing literature by combining the multiple methods to clarify the influence of the macroeconomic factors on the real estate investment trust (REIT) index in three Asian countries. The authors, first, use an autoregressive distributed lag (ARDL) bounds test to find that a long-run equilibrium exists between the REIT index and the interest rate, inflation rate, and stock index for China and Singapore. The authors, then, analyze the long-and short-run elasticity of the macroeconomic variables on the REIT index. Finally, using the Granger non-causality test, the authors demonstrate that a unidirectional relationship, in which inflation-rate shifts cause REIT index changes, exists in Japan and Singapore and that a wealth effect, in which stock index movements cause REIT index changes, exists in Singapore. The findings have economic implications for investors seeking to gain from REITs using macroeconomic factors.

“…In contrast, it was positively impacted by the 10-year bond value. West and Worthington (2006) also used the GARCH–M Method to study the impact of macro-economic factors on commercial real estate, property trust and property sector stock returns. They proved that the persistence of volatility shocks varies across the different markets.…”

Section: Literature Reviewmentioning

confidence: 99%

Sub-prime Crisis or COVID-19: A Comparative Analysis of Volatility in Indian Banking Sectoral Indices

Bhatia

Gupta²

2020

FIIB Business Review

Stock market volatility may be a function of company, industry, or world over information made public. The present study has investigated the volatility of Indian banking sectoral indices with the general banking index for two shocking events: the Sub-prime crisis and COVID-19. A comparative analysis of both the shocks leading to these indices’ volatility has been conducted using symmetric and asymmetric models. This study’s findings show that these indices’ volatile behaviour has been strong enough to persist in the market with the leverage effect present during the sub-prime crisis. This effect disappeared for Nifty Bank Indices and Private Sector Bank Indices as compared to Public Sector Undertaking Bank Indices during COVID-19 (probably because the pandemic is not over yet). With GARCH and EGARCH models, the study suggests that the investors may use the diversification approach, in the long run, to safeguard their portfolio values to survive from global shocks.