Name
Abstract | ||
|---|---|---|
This study investigates how specification of return distribution for REIT influences the performance of volatility forecasting using three GARCH models (GARCH-N, GARCH-ST and GARCH-SGED). Daily prices on the REIT provide an empirical sample for discussing and comparing relative ability to accurately out-of-sample volatility, given the growth potential of REIT markets in the United State from the perspective of global investors. Empirical results indicate that the GARCH-SGED model is superior to the GARCH-N and GARCH-ST model in forecasting REIT volatility in the United State, for all forecast horizons in which model selection is based on MSE or MAE. Meanwhile, the DM-tests further confirm that volatility forecasts using the GARCH-SGED model are more accurate than those generated using the GARCH-N and GARCH-ST model in all cases. These findings demonstrate the significant influences of both skewness and tail-thickness on the conditional distribution of returns. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.eswa.2009.11.044 | Expert Syst. Appl. |
Keywords | Field | DocType |
garch,united state,skew-ged distribution,garch-st model,out-of-sample volatility,garch model,reit volatility prediction,fat tails,skewness,model selection,reit volatility,volatility forecasting,garch-sged model,volatility forecast,sged,reit market,conditional distribution,fat tail | Econometrics,Financial models with long-tailed distributions and volatility clustering,Real estate investment trust,Implied volatility,Volatility swap,Computer science,Volatility smile,Forward volatility,Autoregressive conditional heteroskedasticity,Volatility (finance) | Journal |
Volume | Issue | ISSN |
37 | 7 | Expert Systems With Applications |
Citations | PageRank | References |
1 | 0.36 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yen-hsien Lee | 1 | 118 | 16.64 |
| Tung-Yueh Pai | 2 | 1 | 0.36 |