This document has not been cited yet.

1. Adrian, T., Boyarchenko, N., and Giannone, D. (2019). Vulnerable growth. American Economic Review, 109:1263–89.
   Paper not yet in RePEc: Add citation now
   

2. Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., and Shephard, N. (2008). Designing realized kernels to measure the ex post variation of equity prices in the presence of noise. Econometrica, 76:1481–1536.

3. Barndorff-Nielsen, O. E., Hansen, P. R., Lunde, A., and Shephard, N. (2009). Realized kernels in practice: Trades and quotes. Econometrics Journal, 12:C1–C32.

4. Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. The Review of Economics and Statistics, 72:498–505.

5. Box, G. E. P. (1980). Sampling and Bayes’ inference in scientific modelling and robustness. Journal of the Royal Statistical Society: Series A (General), 143:383–430.
   Paper not yet in RePEc: Add citation now
   
6. Carriero, A., Clark, T., Marcellino, M., and Mertens, E. (2022). Addressing COVID-19 outliers in BVARs with stochastic volatility. Review of Economics and Statistics. forthcoming.
   Paper not yet in RePEc: Add citation now
   

7. Catania, L., Grassi, S., and Ravazzolo, F. (2019). Forecasting cryptocurrencies under model and parameter instability. International Journal of Forecasting, 35:485–501.

8. Chan, J. C. C. (2020). Large Bayesian VARs: A flexible Kronecker error covariance structure. Journal of Business & Economic Statistics, 38:68–79.

9. Chen, Y.-T. (2011). Moment tests for density forecast evaluation in the presence of parameter estimation uncertainty. Journal of Forecasting, 30:409–450.

10. Chernozhukov, V., Fernández-Val, I., and Galichon, A. (2010). Quantile and probability curves without crossing. Econometrica, 78:1093–1125.

11. Clark, M., Gangopadhyay, S., Hay, L., Rajagopalan, B., and Wilby, R. (2004). The Schaake shuffle: A method for reconstructing space–time variability in forecasted precipitation and temperature fields. Journal of Hydrometeorology, 5:243–262.
    Paper not yet in RePEc: Add citation now
    

12. Clark, T. E. (2011). Real-time density forecasts from Bayesian vector autoregressions with stochastic volatility. Journal of Business & Economic Statistics, 29:327–341.

13. Clements, M. P. (2014). Forecast uncertainty–ex ante and ex post: US inflation and output growth. Journal of Business & Economic Statistics, 32:206–216.

14. Clements, M. P. and Smith, J. (2002). Evaluating multivariate forecast densities: a comparison of two approaches. International Journal of Forecasting, 18:397 – 407.

15. Cockayne, J., Graham, M. M., Oates, C. J., Sullivan, T., and Teymur, O. (2022). Testing whether a learning procedure is calibrated. Journal of Machine Learning Research, 23:1–36.
    Paper not yet in RePEc: Add citation now
    

16. Corsi, F. (2009). A simple approximate long-memory model of realized volatility. Journal of Financial Econometrics, 7:174–196.

17. Craiu, R. V. and Rosenthal, J. S. (2014). Bayesian computation via Markov chain Monte Carlo. Annual Review of Statistics and Its Application, 1:179–201.
    Paper not yet in RePEc: Add citation now
    
18. Dawid, A. P. (1984). Present position and potential developments: Some personal views: Statistical theory: The prequential approach. Journal of the Royal Statistical Society: Series A (General), 147:278–290.
    Paper not yet in RePEc: Add citation now
    
19. Dawid, A. P. and Sebastiani, P. (1999). Coherent dispersion criteria for optimal experimental design. The Annals of Statistics, 27:65 – 81.
    Paper not yet in RePEc: Add citation now
    

20. Del Negro, M. and Primiceri, G. E. (2015). Time varying structural vector autoregressions and monetary policy: a corrigendum. The Review of Economic Studies, 82:1342–1345.

21. Diebold, F. X. and Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13:253–263.

22. Diebold, F. X., Gunther, T. A., and Tay, A. S. (1998). Evaluating density forecasts with applications to financial risk management. International Economic Review, 39:863–883.

23. Diebold, F. X., Hahn, J., and Tay, A. S. (1999). Multivariate density forecast evaluation and calibration in financial risk management: High-frequency returns on foreign exchange. The Review of Economics and Statistics, 81:661–673.

24. Diks, C., Panchenko, V., Sokolinskiy, O., and van Dijk, D. (2014). Comparing the accuracy of multivariate density forecasts in selected regions of the copula support. Journal of Economic Dynamics and Control, 48:79–94.

25. Dimitriadis, T., Gneiting, T., and Jordan, A. I. (2021). Stable reliability diagrams for probabilistic classifiers. Proceedings of the National Academy of Sciences, 118:e2016191118.
    Paper not yet in RePEc: Add citation now
    

26. Dovern, J. and Manner, H. (2020). Order-invariant tests for proper calibration of multivariate density forecasts. Journal of Applied Econometrics, 35:440–456.

27. Gabry, J., Simpson, D., Vehtari, A., Betancourt, M., and Gelman, A. (2019). Visualization in Bayesian workflow. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182:389–402.

28. Galvão, A. and Mitchell, J. (2019). Measuring data uncertainty: An application using the Bank of England’s fan charts for historical GDP growth. WBS EMF Working Paper Series no., 24.
    Paper not yet in RePEc: Add citation now
    
29. Genest, C. and Rivest, L.-P. (2001). On the multivariate probability integral transformation. Statistics & Probability Letters, 53:391–399.
    Paper not yet in RePEc: Add citation now
    

30. Giacomini, R. and Rossi, B. (2010). Forecast comparisons in unstable environments. Journal of Applied Econometrics, 25:595–620.

31. Giacomini, R. and White, H. (2006). Tests of conditional predictive ability. Econometrica, 74:1545– 1578.

32. Gneiting, T. (2008). Editorial: Probabilistic forecasting. Journal of the Royal Statistical Society: Series A (Statistics in Society), 171:319–321.

33. Gneiting, T. and Katzfuss, M. (2014). Probabilistic forecasting. Annual Review of Statistics and Its Application, 1:125–151.
    Paper not yet in RePEc: Add citation now
    

34. Gneiting, T. and Raftery, A. E. (2007). Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association, 102:359–378.

35. Gneiting, T. and Ranjan, R. (2013). Combining predictive distributions. Electronic Journal of Statistics, 7:1747–1782.
    Paper not yet in RePEc: Add citation now
    
36. Gneiting, T. and Resin, J. (2022). Regression diagnostics meets forecast evaluation: Conditional calibration, reliability diagrams, and coefficient of determination. Preprint, arXiv:2108.03210.
    Paper not yet in RePEc: Add citation now
    

37. Gneiting, T., Balabdaoui, F., and Raftery, A. E. (2007). Probabilistic forecasts, calibration and sharpness. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 69:243– 268.

38. Gneiting, T., Stanberry, L. I., Grimit, E. P., Held, L., and Johnson, N. A. (2008). Assessing probabilistic forecasts of multivariate quantities, with an application to ensemble predictions of surface winds. Test, 17:211.

39. González-Rivera, G. and Yoldas, E. (2012). Autocontour-based evaluation of multivariate predictive densities. International Journal of Forecasting, 28:328 – 342.

40. Grothe, O., Kächele, F., and Krüger, F. (2022). From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price foreasting. Preprint, arxiv:2204.10154.

41. Guler, K., Ng, P. T., and Xiao, Z. (2017). Mincer–Zarnowitz quantile and expectile regressions for forecast evaluations under aysmmetric loss functions. Journal of Forecasting, 36:651–679.

42. Gupta, R., Huber, F., and Piribauer, P. (2020). Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models. International Review of Financial Analysis, 68:101456.

43. Heinrich, C., Hellton, K. H., Lenkoski, A., and Thorarinsdottir, T. L. (2021). Multivariate postprocessing methods for high-dimensional seasonal weather forecasts. Journal of the American Statistical Association, 116:1048–1059.

44. Held, L., Rufibach, K., and Balabdaoui, F. (2010). A score regression approach to assess calibration of continuous probabilistic predictions. Biometrics, 66:1295–1305.

45. Knüppel, M. (2015). Evaluating the calibration of multi-step-ahead density forecasts using raw moments. Journal of Business & Economic Statistics, 33:270–281.
    Paper not yet in RePEc: Add citation now
    

46. Ko, S. I. and Park, S. Y. (2013). Multivariate density forecast evaluation: A modified approach. International Journal of Forecasting, 29:431 – 441.

47. Koenker, R. (2021). quantreg: Quantile Regression. R package version 5.83.
    Paper not yet in RePEc: Add citation now
    

48. Koop, G. M. (2013). Forecasting with medium and large Bayesian VARS. Journal of Applied Econometrics, 28:177–203.

49. Krüger, F. (2015). bvarsv: Bayesian analysis of a vector autoregressive model with stochastic volatility and time-varying parameters.
    Paper not yet in RePEc: Add citation now
    
50. Krüger, F. and Pavlova, L. (2022). Quantifying subjective uncertainty in survey expectations. Preprint, available at https://ewifo.econ.kit.edu/downloads/KruegerPavlova2022.pdf.
    Paper not yet in RePEc: Add citation now
    

51. Krüger, F., Lerch, S., Thorarinsdottir, T. L., and Gneiting, T. (2021). Predictive inference based on Markov chain Monte Carlo output. International Statistical Review, 89:274–301.

52. Lerch, S., Thorarinsdottir, T. L., Ravazzolo, F., and Gneiting, T. (2017). Forecaster’s dilemma: extreme events and forecast evaluation. Statistical Science, 32:106–127.
    Paper not yet in RePEc: Add citation now
    

53. McAlinn, K., Aastveit, K. A., Nakajima, J., and West, M. (2020). Multivariate Bayesian predictive synthesis in macroeconomic forecasting. Journal of the American Statistical Association, 115:1092–1110.

54. Mincer, J. A. and Zarnowitz, V. (1969). The evaluation of economic forecasts. In Mincer, J. A., editor, Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3–46. Columbia University Press, New York.

55. Mosler, K. and Mozharovskyi, P. (2022). Choosing among notions of multivariate depth statistics. Statistical Science, 37:348–368.
    Paper not yet in RePEc: Add citation now
    
56. Neyman, J. (1937). ‘Smooth test’ for goodness of fit. Scandinavian Actuarial Journal, 20:150–199.
    Paper not yet in RePEc: Add citation now
    

57. Pohle, M.-O. (2020). The Murphy decomposition and the calibration-resolution principle: A new perspective on forecast evaluation. Preprint, arxiv:2005.01835.

58. Primiceri, G. E. (2005). Time varying structural vector autoregressions and monetary policy. The Review of Economic Studies, 72:821–852.

59. Rosenblatt, M. (1952). Remarks on a multivariate transformation. Annals of Mathematical Statistics, 23:470–472.
    Paper not yet in RePEc: Add citation now
    

60. Rossi, B. and Sekhposyan, T. (2019). Alternative tests for correct specification of conditional predictive densities. Journal of Econometrics, 208:638–657.

61. Rüschendorf, L. (2009). On the distributional transform, Sklar’s theorem, and the empirical copula process. Journal of Statistical Planning and Inference, 139:3921–3927.
    Paper not yet in RePEc: Add citation now
    
62. Schefzik, R., Thorarinsdottir, T. L., and Gneiting, T. (2013). Uncertainty quantification in complex simulation models using ensemble copula coupling. Statistical Science, 28:616–640.
    Paper not yet in RePEc: Add citation now
    
63. Smith, J. Q. (1985). Diagnostic checks of non-standard time series models. Journal of Forecasting, 4:283–291.
    Paper not yet in RePEc: Add citation now
    

64. Székely, G. J. and Rizzo, M. L. (2005). A new test for multivariate normality. Journal of Multivariate Analysis, 93:58–80.

65. Theil, H. (1961). Economic Forecasts and Policy. Contributions to economic analysis; 15. NorthHolland Publ. Co., Amsterdam, 2. rev. edition.
    Paper not yet in RePEc: Add citation now
    
66. Thorarinsdottir, T. L. and Schuhen, N. (2018). Verification: Assessment of calibration and accuracy. In Vannitsem, S., Wilks, D. S., and Messner, J., editors, Statistical postprocessing of ensemble forecasts, pages 155–186. Elsevier.
    Paper not yet in RePEc: Add citation now
    
67. Thorarinsdottir, T. L., Scheuerer, M., and Heinz, C. (2016). Assessing the calibration of highdimensional ensemble forecasts using rank histograms. Journal of Computational and Graphical Statistics, 25:105–122.
    Paper not yet in RePEc: Add citation now
    

68. Tsyplakov, A. (2011). Evaluating density forecasts: A comment. Preprint, available at https: //mpra.ub.uni-muenchen.de/32728/1/MPRA_paper_32728.pdf.

69. Tsyplakov, A. (2014). Theoretical guidelines for a partially informed forecast examiner. Preprint, available at https://mpra.ub.uni-muenchen.de/67333/.

70. Vannitsem, S., Wilks, D. S. H., and Messner, J. W., editors (2018). Statistical Postprocessing of Ensemble Forecasts. Elsevier, Amsterdam, Netherlands.
    Paper not yet in RePEc: Add citation now
    

71. Wei, W., Balabdaoui, F., and Held, L. (2017). Calibration tests for multivariate Gaussian forecasts. Journal of Multivariate Analysis, 154:216–233.

72. West, K. D. (1996). Asymptotic inference about predictive ability. Econometrica, 64:1067–1084.

73. Wilks, D. S. (2017). On assessing calibration of multivariate ensemble forecasts. Quarterly Journal of the Royal Meteorological Society, 143:164–172.
    Paper not yet in RePEc: Add citation now
    
74. Ziegel, J. F. (2015). Copula calibration. Oberwolfach Reports, 12:1091–1094.
    Paper not yet in RePEc: Add citation now
    
75. Ziegel, J. F. and Gneiting, T. (2014). Copula calibration. Electronic Journal of Statistics, 8:2619– 2638.
    Paper not yet in RePEc: Add citation now
    

76. Ziel, F. and Berk, K. (2019). Multivariate forecasting evaluation: On sensitive and strictly proper scoring rules. Preprint, arxiv:1910.07325.pdf.

77. Žikeš, F. and Barunı́k, J. (2015). Semi-parametric conditional quantile models for financial returns and realized volatility. Journal of Financial Econometrics, 14:185–226.

78. Zuo, Y. and Serfling, R. (2000). General notions of statistical depth function. Annals of Statistics, 28:461–482. A Additional simulations A.1 Size Here we explore the size of our proposed methods in two setups that are potentially more challenging than the one in Section 4: First, a setup involving time series dependence in forecasts and realizations. Second, a setup in which the true model follows a multivariate t (rather than normal) distribution.
    Paper not yet in RePEc: Add citation now
    

1. A realized EGARCH-MIDAS model with higher moments. (2021). Wu, Xinyu ; Xie, Haibin.
   In: Finance Research Letters.
   RePEc:eee:finlet:v:38:y:2021:i:c:s1544612319308505.

   Full description at Econpapers || Download paper

2. Risk of Bitcoin Market: Volatility, Jumps, and Forecasts. (2021). Hu, Junjie ; Hardle, Wolfgang Karl ; Kuo, Weiyu.
   In: Papers.
   RePEc:arx:papers:1912.05228.

   Full description at Econpapers || Download paper

3. Inference for Volatility Functionals of Multivariate It\^o Semimartingales Observed with Jump and Noise. (2019). Chen, Richard Y.
   In: Papers.
   RePEc:arx:papers:1810.04725.

   Full description at Econpapers || Download paper

4. Gold Futures Returns and Realized Moments: A Forecasting Experiment Using a Quantile-Boosting Approach. (2016). Pierdzioch, Christian ; GUPTA, RANGAN ; Demirer, Riza ; Bonato, Matteo.
   In: Working Papers.
   RePEc:pre:wpaper:201645.

   Full description at Econpapers || Download paper

5. Volume, Volatility and Public News Announcements. (2016). Bollerslev, Tim ; Xue, Yuan ; Li, Jia.
   In: CREATES Research Papers.
   RePEc:aah:create:2016-19.

   Full description at Econpapers || Download paper

6. Functional stable limit theorems for quasi-efficient spectral covolatility estimators. (2015). Altmeyer, Randolf ; Bibinger, Markus.
   In: Stochastic Processes and their Applications.
   RePEc:eee:spapps:v:125:y:2015:i:12:p:4556-4600.

   Full description at Econpapers || Download paper

7. Exploiting the Errors: A Simple Approach for Improved Volatility Forecasting. (2015). Quaedvlieg, Rogier ; Patton, Andrew ; Bollerslev, Tim.
   In: CREATES Research Papers.
   RePEc:aah:create:2015-14.

   Full description at Econpapers || Download paper

8. Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes. (2013). Patton, Andrew ; Liu, Lily ; Sheppard, Kevin.
   In: Economics Series Working Papers.
   RePEc:oxf:wpaper:645.

   Full description at Econpapers || Download paper

9. Martingale unobserved component models. (2013). Shephard, Neil.
   In: Economics Series Working Papers.
   RePEc:oxf:wpaper:644.

   Full description at Econpapers || Download paper

10. Martingale unobserved component models. (2013). Shephard, Neil.
    In: Economics Papers.
    RePEc:nuf:econwp:1301.

    Full description at Econpapers || Download paper

11. A Note on the Mixingale Limit Theorem by McLeish (1977). (2013). Ikeda, Shin.
    In: GRIPS Discussion Papers.
    RePEc:ngi:dpaper:13-11.

    Full description at Econpapers || Download paper

12. Estimating the quadratic covariation of an asynchronously observed semimartingale with jumps. (2013). Vetter, Mathias ; Bibinger, Markus.
    In: SFB 649 Discussion Papers.
    RePEc:hum:wpaper:sfb649dp2013-029.

    Full description at Econpapers || Download paper

13. Econometrics of co-jumps in high-frequency data with noise. (2013). Bibinger, Markus ; Winkelmann, Lars.
    In: SFB 649 Discussion Papers.
    RePEc:hum:wpaper:sfb649dp2013-021.

    Full description at Econpapers || Download paper

14. Inference for Multi-Dimensional High-Frequency Data: Equivalence of Methods, Central Limit Theorems, and an Application to Conditional Independence Testing. (2013). Mykland, Per A. ; Bibinger, Markus.
    In: SFB 649 Discussion Papers.
    RePEc:hum:wpaper:sfb649dp2013-006.

    Full description at Econpapers || Download paper

15. Pricing Nikkei 225 Options Using Realized Volatility. (2013). Watanabe, Toshiaki ; Ubukata, Masato.
    In: Global COE Hi-Stat Discussion Paper Series.
    RePEc:hst:ghsdps:gd12-273.

    Full description at Econpapers || Download paper

16. On covariation estimation for multivariate continuous Itô semimartingales with noise in non-synchronous observation schemes. (2013). Christensen, Kim ; Vetter, Mathias ; Podolskij, Mark.
    In: Journal of Multivariate Analysis.
    RePEc:eee:jmvana:v:120:y:2013:i:c:p:59-84.

    Full description at Econpapers || Download paper

17. Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction. (2013). Olmo, Jose ; Fuertes, Ana-Maria.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:29:y:2013:i:1:p:28-42.

    Full description at Econpapers || Download paper

18. Long memory and tail dependence in trading volume and volatility. (2013). Santucci de Magistris, Paolo ; Rossi, Eduardo.
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:22:y:2013:i:c:p:94-112.

    Full description at Econpapers || Download paper

19. Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach. (2013). SONG, ZHAOGANG ; Chen, Bin.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:173:y:2013:i:1:p:83-107.

    Full description at Econpapers || Download paper

20. On loss functions and ranking forecasting performances of multivariate volatility models. (2013). Violante, Francesco ; Rombouts, Jeroen ; Laurent, Sébastien ; Rombouts, Jeroen V. K., .
    In: Journal of Econometrics.
    RePEc:eee:econom:v:173:y:2013:i:1:p:1-10.

    Full description at Econpapers || Download paper

21. Bootstrapping realized multivariate volatility measures. (2013). Meddahi, Nour ; Goncalves, Silvia ; Dovonon, Prosper ; Gonalves, Silvia.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:172:y:2013:i:1:p:49-65.

    Full description at Econpapers || Download paper

22. Herding and Speculation in the Crude Oil Market. (2013). Harris, Jeffrey ; Buyuksahin, Bahattin ; Brunetti, Celso ; Celso Brunetti, Bahattin Buyuksahin,, .
    In: The Energy Journal.
    RePEc:aen:journl:ej34-3-04.

    Full description at Econpapers || Download paper

23. Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns. (2013). Meddahi, Nour ; Goncalves, Silvia ; Hounyo, Ulrich ; Gonalves, Silvia.
    In: CREATES Research Papers.
    RePEc:aah:create:2013-07.

    Full description at Econpapers || Download paper

24. Forecasting Covariance Matrices: A Mixed Frequency Approach. (2012). Voev, Valeri ; Halbleib, Roxana.
    In: Working Paper Series of the Department of Economics, University of Konstanz.
    RePEc:knz:dpteco:1230.

    Full description at Econpapers || Download paper

25. Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and Covolatility. (2012). Voev, Valeri ; Lunde, Asger ; Hansen, Peter.
    In: Global COE Hi-Stat Discussion Paper Series.
    RePEc:hst:ghsdps:gd12-269.

    Full description at Econpapers || Download paper

26. Spot Volatility Estimation Using Delta Sequences. (2012). Renò, Roberto ; Mattiussi, Vanessa ; Reno, Roberto ; Mancini, Cecilia.
    In: Working Papers - Mathematical Economics.
    RePEc:flo:wpaper:2012-10.

    Full description at Econpapers || Download paper

27. Realized Beta GARCH: Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility. (2012). Voev, Valeri ; Lunde, Asger ; Hansen, Peter.
    In: Economics Working Papers.
    RePEc:eui:euiwps:eco2012/28.

    Full description at Econpapers || Download paper

28. Exponential GARCH Modeling with Realized Measures of Volatility. (2012). Huang, Zhuo ; Hansen, Peter.
    In: Economics Working Papers.
    RePEc:eui:euiwps:eco2012/26.

    Full description at Econpapers || Download paper

29. An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory. (2012). Bibinger, Markus.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:122:y:2012:i:6:p:2411-2453.

    Full description at Econpapers || Download paper

30. Large deviations of realized volatility. (2012). Otsu, Taisuke ; Kanaya, Shin.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:122:y:2012:i:2:p:546-581.

    Full description at Econpapers || Download paper

31. Price jumps in Visegrad-country stock markets: An empirical analysis. (2012). Novotny, Jan ; Hanousek, Jan.
    In: Emerging Markets Review.
    RePEc:eee:ememar:v:13:y:2012:i:2:p:184-201.

    Full description at Econpapers || Download paper

32. Testing for jumps in noisy high frequency data. (2012). Ait-Sahalia, Yacine ; At-Sahalia, Yacine ; Jacod, Jean.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:168:y:2012:i:2:p:207-222.

    Full description at Econpapers || Download paper

33. Volatility forecasts evaluation and comparison. (2012). Violante, Francesco ; Laurent, Sébastien.
    In: LIDAM Reprints CORE.
    RePEc:cor:louvrp:2414.

    Full description at Econpapers || Download paper

34. A model for vast panels of volatilities. (2012). Veredas, David ; Luciani, Matteo.
    In: Working Papers.
    RePEc:bde:wpaper:1230.

    Full description at Econpapers || Download paper

35. Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data. (2012). Ait-Sahalia, Yacine ; Yacine Aït-Sahalia, ; Jacod, Jean.
    In: Journal of Economic Literature.
    RePEc:aea:jeclit:v:50:y:2012:i:4:p:1007-50.

    Full description at Econpapers || Download paper

36. Exponential GARCH Modeling with Realized Measures of Volatility. (2012). Huang, Zhuo ; Hansen, Peter.
    In: CREATES Research Papers.
    RePEc:aah:create:2012-44.

    Full description at Econpapers || Download paper

37. How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?. (2011). Veraart, Almut.
    In: AStA Advances in Statistical Analysis.
    RePEc:spr:alstar:v:95:y:2011:i:3:p:253-291.

    Full description at Econpapers || Download paper

38. The role of high frequency intra-daily data, daily range and implied volatility in multi-period Value-at-Risk forecasting. (2011). Louzis, Dimitrios ; Xanthopoulos-Sisinis, Spyros ; Refenes, Apostolos P..
    In: MPRA Paper.
    RePEc:pra:mprapa:35252.

    Full description at Econpapers || Download paper

39. Spectral estimation of covolatility from noisy observations using local weights. (2011). Rei, Markus ; Bibinger, Markus.
    In: SFB 649 Discussion Papers.
    RePEc:hum:wpaper:sfb649dp2011-086.

    Full description at Econpapers || Download paper

40. Multivariate realised kernels: Consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading. (2011). Hansen, Peter Reinhard ; Barndorff-Nielsen, Ole E. ; Shephard, Neil ; Lunde, Asger.
    In: Post-Print.
    RePEc:hal:journl:peer-00815564.

    Full description at Econpapers || Download paper

41. Asymptotic results for time-changed Lévy processes sampled at hitting times. (2011). TANKOV, PETER ; Rosenbaum, Mathieu.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:121:y:2011:i:7:p:1607-1632.

    Full description at Econpapers || Download paper

42. Variance dynamics: Joint evidence from options and high-frequency returns. (2011). Wu, Liuren.
    In: Journal of Econometrics.
    RePEc:eee:econom:v:160:y:2011:i:1:p:280-287.

    Full description at Econpapers || Download paper

43. Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices. (2011). Varneskov, Rasmus Tangsgaard.
    In: CREATES Research Papers.
    RePEc:aah:create:2011-35.

    Full description at Econpapers || Download paper

44. Pre-averaging based estimation of quadratic variation in the presence of noise and jumps: Theory, implementation, and empirical evidence. (2010). Hautsch, Nikolaus ; Podolskij, Mark.
    In: CFS Working Paper Series.
    RePEc:zbw:cfswop:201017.

    Full description at Econpapers || Download paper

45. Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets. (2010). Veredas, David ; Gallo, Giampiero ; Brownlees, Christian ; Barigozzi, Matteo.
    In: Econometrics Working Papers Archive.
    RePEc:fir:econom:wp2010_06.

    Full description at Econpapers || Download paper

46. Bipower-type estimation in a noisy diffusion setting. (2009). Podolskij, Mark ; Vetter, Mathias.
    In: Stochastic Processes and their Applications.
    RePEc:eee:spapps:v:119:y:2009:i:9:p:2803-2831.

    Full description at Econpapers || Download paper

47. The relationship between the volatility of returns and the number of jumps in financial markets. (2009). Cartea, Álvaro ; Karyampas, Dimitrios.
    In: DEE - Working Papers. Business Economics. WB.
    RePEc:cte:wbrepe:wb097508.

    Full description at Econpapers || Download paper

48. The Relationship Between the Volatility of Returns and the Number of Jumps in Financial Markets. (2009). Cartea, Álvaro ; Karyampas, Dimitrios.
    In: Birkbeck Working Papers in Economics and Finance.
    RePEc:bbk:bbkefp:0914.

    Full description at Econpapers || Download paper

49. On the correlation structure of microstructure noise in theory and practice. (2008). Strasser, Georg ; Diebold, Francis.
    In: CFS Working Paper Series.
    RePEc:zbw:cfswop:200832.

    Full description at Econpapers || Download paper

50. Does the open limit order book matter in explaining long run volatility ?. (2006). Veredas, David ; PASCUAL, ROBERTO.
    In: LIDAM Discussion Papers CORE.
    RePEc:cor:louvco:2006110.

    Full description at Econpapers || Download paper

Report date: 2025-10-06 15:59:45 || Missing content? Let us know