Abstract
This paper investigates the impacts of macroeconomic variables, namely consumer price index, exchange rate, minimum loan rate and oil price movement, on the financials and the property & construction stock index return in the Stock Exchange of Thailand (SET). The monthly data is collected from January 2004 to November 2016, covering 155 observations. We employ a copula based SUR regression as a tool for this study. Ten copula functions are considered in this regression and the best copula function is selected based on Akaike’s Information Criterion (AIC) and Bayesian Information Criterion (BIC). The estimated results show that Gumbel 270 copula is the most appropriate function for being the linkage between the marginal distributions of residuals of financials sector and property & construction sector equations. In addition, the marginal distribution is also tested, and the result shows that normal distribution is the best fit for the marginal distribution for both financials and property & construction equations. Our results suggest that the exchange rate can exert significant impact on both sectors. The dependency parameter also suggests that dependency between financials sector and property & construction sector is negative, and very low dependency, meaning when the impact of macroeconomic variables in one of these two sectors, it just has a little effect to another one sector.
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Srichaikul, W., Yamaka, W., Tansuchat, R. (2018). The Impacts of Macroeconomic Variables on Financials Sector and Property and Construction Sector Index Returns in Stock Exchange of Thailand Under Interdependence Scheme. 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_42
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DOI: https://doi.org/10.1007/978-3-319-70942-0_42
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