TY - UNPB
T1 - Housing Market Variables and Predictability of State-level Stock Market Volatility of the United States
T2 - Evidence From a GARCH-MIDAS Approach
AU - Salisu, Afees A.
AU - Gupta, Rangan
AU - Cepni, Oguzhan
PY - 2023/10
Y1 - 2023/10
N2 - This paper utilizes the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to predict the daily volatility of state-level stock returns in the United States (US), based on the monthly state and national housing price returns. We find that housing price returns generally tend to affect state-level volatility negatively. More importantly, the GARCH-MIDAS model, supplemented by these predictors, outperforms, in a statistically significant manner over short-, medium-, and long-term forecasting horizons, the benchmark GARCH-MIDAS model with realized volatility (GARCH-MIDAS-RV) for 90% of the states, with the performance of state and national housing returns being virtually inseparable. Such superior forecasting performances continue to hold when housing price returns is replaced with housing permits and housing market media attention indexes, suggesting an overwhelming role of housing market variables: traditional and behavioural, in forecasting state-level stock returns volatility. Our findings have important implications for investors and policymakers.
AB - This paper utilizes the generalized autoregressive conditional heteroscedasticity-mixed data sampling (GARCH-MIDAS) framework to predict the daily volatility of state-level stock returns in the United States (US), based on the monthly state and national housing price returns. We find that housing price returns generally tend to affect state-level volatility negatively. More importantly, the GARCH-MIDAS model, supplemented by these predictors, outperforms, in a statistically significant manner over short-, medium-, and long-term forecasting horizons, the benchmark GARCH-MIDAS model with realized volatility (GARCH-MIDAS-RV) for 90% of the states, with the performance of state and national housing returns being virtually inseparable. Such superior forecasting performances continue to hold when housing price returns is replaced with housing permits and housing market media attention indexes, suggesting an overwhelming role of housing market variables: traditional and behavioural, in forecasting state-level stock returns volatility. Our findings have important implications for investors and policymakers.
M3 - Working paper
T3 - Working Paper Series / Department of Economics. University of Pretoria
BT - Housing Market Variables and Predictability of State-level Stock Market Volatility of the United States
PB - University of Pretoria
CY - Pretoria
ER -