Determinants of trading volume in real estate investment trusts / Hairulnizam Hashim
Real estate investment trusts (REITs) show lower average volumes than similar non REITs. Lower average volume is among the main reason of institutional investors' disinterest to invest in REITs. Consequently, the lower participation of institutional investors causes the lower return performa...
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| Format: | Thesis |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/12990/2/12990.pdf |
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| Summary: | Real estate investment trusts (REITs) show lower average volumes than similar non REITs.
Lower average volume is among the main reason of institutional investors'
disinterest to invest in REITs. Consequently, the lower participation of institutional
investors causes the lower return performance of REITs. There are very limited studies
on trading volume in REITs. Most of the studies focus on examining the level of
trading volume. In reviewing past studies which regard to variables that have significant
relationship with trading volume of non-REITs, only proxies for stock market
data have been used. This indicate the need to examine other important variables such
as macro-economic data, type of returns, firm size, market structure and period eflect
in modelling determinants that affect trading volume of REITs. In filling the gap of
the previous works, this study had also tested whether variables that have significant
relationship and significantly related to trading volume in non-REITs market, will also
affect significantly the trading volume of REITs. The variables identified are price
return, absolute price return, volatility, dividend yield, percentage change of long-term
interest rate, absolute percentage change of long-term interest rate, fum size, year of
trading, type of return, trading volume (lag one) and trading volume (lag two). This
study examines weekly data of 288 individual REITs from January 2006 to December
2007 across 10 countries, which involve 12 REITs markets and 29,664 firm-weekly
observations. This study employs the panel ordinary least square (OLS), fixed etlects
model, random effects model, and panel equation testing to identify the best estimation
model The cross section fixed effects model (CSFEM) is the best estimation
model in explaining 11 out of 12 REITs markets. There are different detem1inants of
trading volume in REITs for different market. However, this study discovers similar
main determinants for the same region of REITs markets. Trading volume (lag one) revealed
as the main determinant on trading volume as evident in the II REITs markets.
Since trading volume is a proxy of information rate, the REITs managers should improve
dissemination of information to the existing and potential investors. |
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