RT Report
T1 Asymmetry and Long Memory in Volatility Modelling
A1 Asai, Manabu
A1 McAleer, Michael
A1 Medeiros, Marcelo C.
AB A wide variety of conditional and stochastic variance models has been used to estimate latent volatility (or risk). In this paper, we propose a new long memory asymmetric volatility model which captures more flexible asymmetric patterns as compared with several existing models. We extend the new specification to realized volatility by taking account of measurement errors, and use the Efficient Importance Sampling technique to estimate the model. As an empirical example, we apply the new model to the realized volatility of S&P500 to show that the new specification of asymmetry significantly improves the goodness of fit, and that the out-of-sample forecasts and Value-at-Risk (VaR) thresholds are satisfactory. Overall, the results of the out-of-sample forecasts show the adequacy of the new asymmetric and long memory volatility model for the period including the global financial crisis.
YR 2011
FD 2011-08
LK https://hdl.handle.net/20.500.14352/49024
UL https://hdl.handle.net/20.500.14352/49024
LA eng
NO The authors are most grateful to a Co-Editor, Associate Editor and two referees for very helpful comments and suggestions, and Marcel Scharth for efficient research assistance.
NO Japan Society for the Promotion of Science
NO Japan Ministry of Education Culture, Sports, Science and Technology
NO Australian Academy of Science
NO Australian Research Council,
NO National Science Council
NO Taiwan, and Japan Society for the Promotion of Science
NO CNPq, Brazil
DS Docta Complutense
RD 11 abr 2025