Abstract
This study introduces an approach to fitting a copula based seemingly unrelated regression to an interval-valued data set. This approach consists of fitting a model on the appropriate point of the interval values assumed by the variables in the learning set. To find the appropriate point of the interval values, we assign weights in calculating the appropriate value between intervals by using convex combination method. We apply this methodology to quantify the risk and dependence of Real Estate Investment Trust (REITs) in Asia. Our results suggest that Hong Kong and Japan markets have a positive sign of the beta and both markets have less volatility than the global REITs market. On the other hand, we find that the estimated beta for Singapore market shows a negative relationship with global REITs market. We conclude that Singapore market can be viewed as a hedge against higher risk in Asian REITs.
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Phadkantha, R., Yamaka, W., Tansuchat, R. (2018). Analysis of Risk, Rate of Return and Dependency of REITs in ASIA with Capital Asset Pricing Model. In: Kreinovich, V., Sriboonchitta, S., Chakpitak, N. (eds) Predictive Econometrics and Big Data. TES 2018. Studies in Computational Intelligence, vol 753. Springer, Cham. https://doi.org/10.1007/978-3-319-70942-0_38
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DOI: https://doi.org/10.1007/978-3-319-70942-0_38
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