Asymptotic inference about predictive accuracy using high frequency data

Aït-Sahalia, 2009, Testing for jumps in a discretely observed process, Ann. Statist., 37, 184, 10.1214/07-AOS568 Aït-Sahalia, 2005, How often to sample a continuous-time process in the presence of market microstructure noise, Rev. Financ. Stud., 18, 351, 10.1093/rfs/hhi016 Amaya, 2015, Does realized skewness predict the cross-section of equity returns?, J. Financ. Econom., 118, 135, 10.1016/j.jfineco.2015.02.009 Andersen, 1998, Answering the skeptics: Yes, standard volatility models do provide accurate forecasts, Internat. Econom. Rev., 39, 885, 10.2307/2527343 Andersen, 2006, Volatility and correlation forecasting, 10.1016/S1574-0706(05)01015-3 Andersen, 2003, Modeling and forecasting realized volatility, Econometrica, 71, 579, 10.1111/1468-0262.00418 Andersen, 2005, Correcting the errors: Volatility forecast evaluation using high-frequency data and realized volatilities, Econometrica, 73, 279, 10.1111/j.1468-0262.2005.00572.x Andrews, 1991, Heteroskedasticity and autocorrelation consistent covariance matrix estimation, Econometrica, 59, 817, 10.2307/2938229 Bandi, 2016, Price and volatility co-jumps, J. Financ. Econom., 119, 107, 10.1016/j.jfineco.2015.05.007 Bandi, 2008, Microstructure noise, realized volatility and optimal sampling, Rev. Econom. Stud., 75, 339, 10.1111/j.1467-937X.2008.00474.x Barndorff-Nielsen, 2008, Designing realized kernels to measure the ex post variation of equity prices in the presence of noise, Econometrica, 76, 1481, 10.3982/ECTA6495 Barndorff-Nielsen, 2010, Measuring downside risk: realised semivariance, 117 Barndorff-Nielsen, 2004, Econometric analysis of realized covariation: High frequency based covariance, regression, and correlation in financial economics, Econometrica, 72, 885, 10.1111/j.1468-0262.2004.00515.x Barndorff-Nielsen, 2004, Power and bipower variation with stochastic volatility and jumps (with discussion), J. Financ. Econom., 2, 1 Bollerslev, 1986, Generalized autoregressive conditional heteroskedasticity, J. Econometrics, 31, 307, 10.1016/0304-4076(86)90063-1 Bollerslev, 2002, Estimating stochastic volatility diffusions using conditional moments of integrated volatility, J. Econometrics, 109, 33, 10.1016/S0304-4076(01)00141-5 Cappiello, 2006, Asymmetric dynamics in the correlations of global equity and bond returns, J. Financ. Econom., 4, 537 Clark, 2005, Evaluating direct multistep forecasts, Econometric Rev., 24, 369, 10.1080/07474930500405683 Comte, 1998, Long memory in continuous-time stochastic volatility models, Math. Finance, 8, 291, 10.1111/1467-9965.00057 Corradi, 2006, Semi-parametric comparison of stochastic volatility models using realized measures, Rev. Econom. Stud., 73, 635, 10.1111/j.1467-937X.2006.00390.x Corradi, 2009, Predictive density estimators for daily volatility based on the use of realized measures, J. Econometrics, 150, 119, 10.1016/j.jeconom.2008.12.015 Corradi, 2011, Predictive inference for integrated volatility, J. Amer. Statist. Assoc., 106, 1496, 10.1198/jasa.2011.tm10012 Corradi, 2007, Nonparametric bootstrap procedures for predictive inference based on recursive estimation schemes, Internat. Econom. Rev., 48, 67, 10.1111/j.1468-2354.2007.00418.x Corsi, 2009, A simple approximate long memory model of realized volatility, J. Financ. Econom., 7, 174 Davidson, 1994 Diebold, 1995, Comparing predictive accuracy, J. Bus. Econom. Statist., 253 Duffie, 2001 Engle, 1982, Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation, Econometrica, 50, 987, 10.2307/1912773 Engle, 2002, Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models, J. Bus. Econom. Statist., 20, 339, 10.1198/073500102288618487 Engle, 2008 Foster, 1996, Continuous record asymptotics for rolling sample variance estimators, Econometrica, 64, 139, 10.2307/2171927 Giacomini, 2009, Detecting and predicting forecast breakdowns, Rev. Econom. Stud., 76, 669, 10.1111/j.1467-937X.2009.00545.x Giacomini, 2006, Tests of conditional predictive ability, Econometrica, 74, 1545, 10.1111/j.1468-0262.2006.00718.x Glosten, 1993, On the relation between the expected value and the volatility of the nominal excess return on stocks, J. Financ., 48, 1779, 10.1111/j.1540-6261.1993.tb05128.x Gonçalves, 2003, Consistency of the stationary bootstrap under weak moment conditions, Econom. Lett., 81, 273, 10.1016/S0165-1765(03)00192-7 Gonçalves, 2002, The bootstrap of the mean for dependent heterogeneous arrays, Econom. Theory, 18, 1367, 10.1017/S0266466602186051 Granger, 1999, Outline of forecast theory using generalized cost functions, Spanish Econom. Rev., 1, 161, 10.1007/s101080050007 Hansen, 1982, Large sample properties of generalized method of moments estimators, Econometrica, 50, 1029, 10.2307/1912775 Hansen, 2005, A test for superior predictive ability, J. Bus. Econom. Statist., 23, 365, 10.1198/073500105000000063 Hansen, 2006, Consistent ranking of volatility models, J. Econometrics, 131, 97, 10.1016/j.jeconom.2005.01.005 Hansen, 2011, The model confidence set, Econometrica, 79, 453, 10.3982/ECTA5771 Hansen, 2012, Choice of Sample Split in Out-of-Sample Forecast Evaluation Huang, 2005, The relative contribution of jumps to total price variance, J. Financ. Econom., 4, 456 Inoue, 2004, In-sample or out-of-sample tests of predictability: Which one should we use?, Econometric Rev., 23, 371, 10.1081/ETC-200040785 Jacod, 2008, Asymptotic properties of realized power variations and related functionals of semimartingales, Stochastic Process. Appl., 118, 517, 10.1016/j.spa.2007.05.005 Jacod, 2012 Jacod, 2013, Quarticity and other functionals of volatility: Efficient estimation, Ann. Statist., 118, 1462 Kanaya, 2016, Estimation of stochastic volatility models by nonparametric filtering, Econom. Theory, 32, 861, 10.1017/S0266466615000079 Kiefer, 2005, A new asymptotic theory for heteroskedasticity-autocorrelation robust tests, Econom. Theory, 21, 1130, 10.1017/S0266466605050565 Kristensen, 2010, Nonparametric filtering of the realized spot volatility: A kernel-based approach, Econom. Theory, 26, 60, 10.1017/S0266466609090616 Lepingle, 1976, La variation d’ordre p des semi-martingales, Z. Wahrscheinlichkeitstheor. Verwandte Geb., 36, 295, 10.1007/BF00532696 Mancini, 2001, Disentangling the jumps of the diffusion in a geometric jumping Brownian motion, Giornale dell’Istituto Italiano degli Attuari, LXIV, 19 McCracken, 2000, Robust out-of-sample inference, J. Econometrics, 99, 195, 10.1016/S0304-4076(00)00022-1 McCracken, 2007, Asymptotics for out of sample tests of granger Causality, J. Econometrics, 140, 719, 10.1016/j.jeconom.2006.07.020 Müller, 2014, HAC corrections for strongly autocorrelated time series, J. Bus. Econom. Statist., 32, 311, 10.1080/07350015.2014.931238 Newey, 1987, A simple, positive semidefinite, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica, 55, 703, 10.2307/1913610 Noureldin, 2012, Multivariate high-frequency-based volatility (HEAVY) models, J. Appl. Econometrics, 27, 907, 10.1002/jae.1260 Patton, 2011, Volatility forecast comparison using imperfect volatility proxies, J. Econometrics, 160, 246, 10.1016/j.jeconom.2010.03.034 Patton, 2015, Good volatility, bad volatility: Signed jumps and the persistence of volatility, Rev. Econom. Statist., 97, 683, 10.1162/REST_a_00503 Patton, 2010, Generalized forecast errors, a change of measure, and forecast optimality conditions Politis, 1994, The stationary bootstrap, J. Amer. Statist. Assoc., 1303, 10.1080/01621459.1994.10476870 Renò, 2006, Nonparametric estimation of stochastic volatility models, Econom. Lett., 90, 390, 10.1016/j.econlet.2005.09.009 Romano, 2005, Stepwise multiple testing as formalized data snooping, Econometrica, 73, 1237, 10.1111/j.1468-0262.2005.00615.x Singleton, 2006 Tauchen, 2011, Realized jumps on financial markets and predicting credit spreads, J. Econometrics, 160, 102, 10.1016/j.jeconom.2010.03.023 Todorov, 2009, Estimation of continuous-time stochastic volatility models with jumps using high-frequency data, J. Econometrics, 148, 131, 10.1016/j.jeconom.2008.10.005 Todorov, 2012, The realized Laplace transform of volatility, Econometrica, 80, 1105, 10.3982/ECTA9133 Todorov, 2011, Realized Laplace transforms for estimation of jump diffusive volatility models, J. Econometrics, 164, 367, 10.1016/j.jeconom.2011.06.016 Vetter, 2010, Limit theorems for bipower variation of semimartingales, Stochastic Process. Appl., 120, 22, 10.1016/j.spa.2009.10.005 West, 1996, Asymptotic inference about predictive ability, Econometrica, 64, 1067, 10.2307/2171956 West, 2006, Forecast evaluation, 10.1016/S1574-0706(05)01003-7 White, 1982, Maximum likelihood estimation of misspecified models, Econometrica, 50, 1, 10.2307/1912526 White, 2000, A reality check for data snooping, Econometrica, 68, 1097, 10.1111/1468-0262.00152 White, 2001 Zhang, 2006, Efficient estimation of stochastic volatility using noisy observations: A multi-scale approach, Bernoulli, 12, 1019, 10.3150/bj/1165269149 Zhang, 2005, A tale of two time scales: Determining integrated volatility with noisy high-frequency data, J. Amer. Statist. Assoc., 100, 1394, 10.1198/016214505000000169