Hitting the jackpot: what drives casino hotel stock returns' predictability?

被引:0
|
作者
Pham, Thach [1 ]
Bannigidadmath, Deepa [1 ]
Goh, Edmund [2 ,4 ]
Golab, Anna [3 ]
机构
[1] Edith Cowan Univ, Sch Business & Law, Churchlands, WA, Australia
[2] Bond Univ, Bond Business Sch, Gold Coast, Australia
[3] Edith Cowan Univ, Sch Business & Law, Joondalup, Australia
[4] Bond Univ, Bond Business Sch, 14 Univ Dr, Gold Coast, Qld 4226, Australia
关键词
Casinos; hospitality; predictability; predictive regression model; firm-specific variables; macroeconomic variables; RESIDENTS PERCEPTIONS; MONETARY-POLICY; HOSPITALITY; TOURISM; PERFORMANCE; CONFIDENCE; SENTIMENT; REVENUE; ECONOMY;
D O I
10.1080/02508281.2024.2327258
中图分类号
F [经济];
学科分类号
02 ;
摘要
Forecasting casino hotel stock prices are strategically important to key stakeholders making investment decisions. However, there is a paucity of studies that have examined the impact of macro-economic variables, sector-specific variables and firm-specific variables on casino stock returns. This research fills a research gap by examining the predictability of Australian casino hotel stock returns. The forecasting of casino hotel stock prices was modelled using econometric panel predictive regression analysis through the efficacy of 26 predictors comprising macroeconomic variables, sector-specific variables, and firm-specific variables as predictors. All eight casinos listed on the Australia Stock Exchange (ASX) were included in our sample. Our econometric panel predictive regression model found macro-economic variables with the strongest return predictability relative to the sector-specific and firm-specific variables. Our study contributes to the theoretical advancement of forecasting methodology through panel predictive regression modelling by addressing the endogeneity, persistency and heteroskedasticity of stock predictors by considering a large set of macro-economic variables, sector-specific and firm-specific variables as predictors to develop an econometric framework that suits the features of hotel financial data.
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页数:15
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