The role of jumps and leverage in forecasting volatility in international equity markets

Andersen, 2007, Roughing it up: including jump components in the measurement, modeling and forecasting of return volatility, Rev. Econ. Stat., 89, 701, 10.1162/rest.89.4.701 Andersen, 2001, The distribution of realized stock return volatility, J. Financ. Econ., 61, 43, 10.1016/S0304-405X(01)00055-1 Andersen, 2003, Modeling and forecasting realized volatility, Econometrica, 71, 579, 10.1111/1468-0262.00418 Andrews, 1992, An improved heteroskedasticity and autocorrelation consistent covariance matrix estimator, Econometrica, 60, 953, 10.2307/2951574 Barndorff-Nielsen, 2004, Power and bipower variation with stochastic volatility and jumps, J. Financ. Economet., 2, 1, 10.1093/jjfinec/nbh001 Barndorff-Nielsen, 2005 Barndorff-Nielsen, 2006, Econometrics of testing for jumps in financial economics using bipower variation, J. Financ. Economet., 4, 1, 10.1093/jjfinec/nbi022 Bollerslev, 2008, Risk, jumps, and diversification, J. Economet., 144, 234, 10.1016/j.jeconom.2008.01.006 Bollerslev, 2006, Leverage and volatility feedback effect in high-frequency data, J. Financ. Economet., 4, 353, 10.1093/jjfinec/nbj014 Buncic, 2016, Global equity market volatility spillovers: a broader role for the United States, Int. J. Forecast., 32, 1317, 10.1016/j.ijforecast.2016.05.001 Campbell, 2008, Predicting excess stock returns out of sample: can anything beat the historical average?, Rev. Financ. Stud., 21, 1509, 10.1093/rfs/hhm055 Corsi, 2009, A simple approximate long-memory model of realized volatility, J. Financ. Economet., 7, 174, 10.1093/jjfinec/nbp001 Corsi, 2012, HAR modeling for realized volatility forecasting, 363 Corsi, 2012, Discrete-time volatility forecasting with persistent leverage effect and the link with continuous-time volatility modeling, J. Bus. Econ. Stat., 30, 368, 10.1080/07350015.2012.663261 Diebold, 1995, Comparing predictive accuracy, J. Bus. Econ. Stat., 13, 253 Figlewski, Stephen, Wang, Xiaozu, 2000. Is the ‘Leverage Effect’ a Leverage Effect? SSRN Working Paper No. 256109. Available from: <http://ssrn.com/abstract=256109>. Giacomini, 2006, Tests of conditional predictive ability, Econometrica, 74, 1545, 10.1111/j.1468-0262.2006.00718.x Heber, Gerd, Lunde, Asger, Shephard, Neil, Sheppard, Kevin, 2009. Oxford-Man Institute’s Realized Library. Oxford-Man Institute, University of Oxford. Available from: <http://realized.oxford-man.ox.ac.uk/>. Huang, 2005, The relative contribution of jumps to total price variance, J. Financ. Economet., 3, 456, 10.1093/jjfinec/nbi025 Liu, 2015, Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes, J. Economet., 187, 293, 10.1016/j.jeconom.2015.02.008 Müller, Ulrich A., Dacorogna, Michel M., Davé, Rakhal D., Olsen, Richard B., Pictet, Olivier V., Ward, John R., 1993. Fractals and intrinsic time – a challenge to econometricians. In: Invited presentation at the 39th International AEA Conference on Real Time Econometrics, 14–15 October 1993, Luxembourg. Newey, 1994, Automatic lag selection in covariance matrix estimation, Rev. Econ. Stud., 61, 631, 10.2307/2297912 Patton, 2015, Good volatility, bad volatility: signed jumps and the persistence of volatility, Rev. Econ. Stat., 97, 683, 10.1162/REST_a_00503 Prokopczuk, 2016, Do jumps matter for volatility forecasting? Evidence from energy markets, J. Fut. Markets, 36, 758, 10.1002/fut.21759 Rapach, 2013, International stock return predictability: what is the role of the United States?, J. Finan., 68, 1633, 10.1111/jofi.12041 Rigobon, 2009, Bias from censored regressors, J. Bus. Econ. Stat., 27, 340, 10.1198/jbes.2009.06119