Flury, T. and N. Shephard (2011). Bayesian inference based only on a simulated likelihood, Econometric Theory, forthcoming

Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde, and N. Shephard (2011). Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading, Journal of Econometrics, forthcoming

Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde, and N. Shephard (2011). Subsampling realised kernels. Journal of Econometrics, 160, 204-219[ bib | .pdf ]

Pakel, C., N. Shephard and K.K. Shephard (2011). Nuisance parameters, composite likelihoods and a panel of GARCH models, Statistica Sinica, , 2011, 21, 307-329

Sheppard, K. K. and N. Shephard (2010) Realising the future: forecasting with high frequency based volatility (HEAVY) models, Journal of Applied Econometrics, 25, 197-231.

Shephard, N. (2010) Deferred fees for universities, Economic Affairs, 2010, 30, 2, 40-44.

Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde, and N. Shephard (2009). Realised kernels in practice: trades and quotes. Econometrics Journal, 12, C1-C32 [ bib | .pdf ]

Koopman, S. J., D. Creal, and N. Shephard (2009). Testing the assumptions behind importance sampling. Journal of Econometrics, 149, 2-11 [ bib | .pdf ]

Barndorff-Nielsen, O. E., P. R. Hansen, A. Lunde, and N. Shephard (2008). Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise. Econometrica 76, 1481-1536. [ bib | .pdf ]

Bec, F., A. Rahbek, and N. Shephard (2008). The ACR model: a multivariate dynamic mixture autoregression. Oxford Bulletin of Economics and Statistics 70, 583-618. [ bib | .pdf ]

Omori, Y., S. Chib, N. Shephard, and J. Nakajima (2007). Stochastic volatility with leverage: fast and efficient likelihood inference. Journal of Econometrics 140, 425-449. [ bib | .pdf ]

Barndorff-Nielsen, O. E. and N. Shephard (2006b). Impact of jumps on returns and realised variances: econometric analysis of time-deformed Lévy processes. Journal of Econometrics 131, 217-252. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2006a). Econometrics of testing for jumps in financial economics using bipower variation. Journal of Financial Econometrics 4, 1-30. [ bib ]

Barndorff-Nielsen, O. E., S. E. Graversen, J. Jacod, and N. Shephard (2006). Limit theorems for realised bipower variation in econometrics. Econometric Theory 22, 677-719. [ bib ]

Barndorff-Nielsen, O. E., N. Shephard, and M. Winkel (2006). Limit theorems for multipower variation in the presence of jumps. Stochastic Processes and Their Applications 116, 796-806. [ bib ]

Bos, C. and N. Shephard (2006). Inference for adaptive time series models: stochastic volatility and conditionally Gaussian state space form. Econometric Reviews 25, 219-244. [ bib ]

Chib, S., F. Nardari, and N. Shephard (2006). Analysis of high dimensional multivariate stochastic volatility models. Journal of Econometrics 134, 341-371. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2005). Power variation and time change. Theory of Probability and Its Applications 50, 1-15. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2004b). Power and bipower variation with stochastic volatility and jumps (with discussion). Journal of Financial Econometrics 2, 1-48. [ bib ]

Barndorff-Nielsen, O. E., S. E. Graversen, and N. Shephard (2004). Power variation and stochastic volatility: a review and some new results. Journal of Applied Probability 41A, 133-143. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2004a). Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics. Econometrica 72, 885-925. [ bib ]

Fiorentini, G., E. Sentana, and N. Shephard (2004). Likelihood-based estimation of latent generalised ARCH structures. Econometrica 72, 1481-1517. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2003a). Integrated OU processes and non-Gaussian OU-based stochastic volatility. Scandinavian Journal of Statistics 30, 277-295. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2003b). Realised power variation and stochastic volatility. Bernoulli 9, 243-265. Correction published in pages 1109-1111. [ bib ]

Nielsen, B. and N. Shephard (2003). Likelihood analysis of a first order autoregressive model with exponential innovations. Journal of Time Series Analysis 24, 337-344. [ bib ]

Rydberg, T. H. and N. Shephard (2003). Dynamics of trade-by-trade price movements: decomposition and models. Journal of Financial Econometrics 1, 2-25. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2002a). Econometric analysis of realised volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society, Series B 64, 253-280. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2002b). Estimating quadratic variation using realised variance. Journal of Applied Econometrics 17, 457-477. [ bib ]

Barndorff-Nielsen, O. E., E. Nicolato, and N. Shephard (2002). Some recent developments in stochastic volatility modelling. Quantitative Finance 2, 11-23. [ bib ]

Chib, S., F. Nardari, and N. Shephard (2002). Markov chain Monte Carlo methods for generalized stochastic volatility models. Journal of Econometrics 108, 281-316. [ bib ]

Doornik, J. A., D. F. Hendry, and N. Shephard (2002). Computationally-intensive econometrics using a distributed matrix-programming language. Philosophical Transactions of the Royal Society of London, Series A 360, 1245-1266. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2001a). Non-Gaussian Ornstein-Uhlenbeck-based models and some of their uses in financial economics (with discussion). Journal of the Royal Statistical Society, Series B 63, 167-241. [ bib | .pdf ]

Barndorff-Nielsen, O. E. and N. Shephard (2001b). Normal modified stable processes. Theory of Probability and Mathematical Statistics 65, 1-19. [ bib ]

Elerian, O., S. Chib, and N. Shephard (2001). Likelihood inference for discretely observed non-linear diffusions. Econometrica 69, 959-993. [ bib | .pdf ]

Koopman, S. J., N. Shephard, and J. A. Doornik (1999). Statistical algorithms for models in state space using SsfPack 2.2. The Econometrics Journal 2, 107-166. [ bib ]

Pitt, M. K. and N. Shephard (1999a). Analytic convergence rates and parameterisation issues for the Gibbs sampler applied to state space models. Journal of Time Series Analysis 21, 63-85. [ bib ]

Pitt, M. K. and N. Shephard (1999b). Filtering via simulation: auxiliary particle filter. Journal of the American Statistical Association 94, 590-599. [ bib | .pdf ]

Kim, S., N. Shephard, and S. Chib (1998). Stochastic volatility: likelihood inference and comparison with ARCH models. Review of Economic Studies 65, 361-393. [ bib ]

Manrique, A. and N. Shephard (1998). Simulation based likelihood inference for Gaussian limited dependent processes. The Econometrics Journal 1, C174-C202. [ bib ]

Atkinson, A. C., S. J. Koopman, and N. Shephard (1997). Detecting shocks: outliers and breaks in time series. Journal of Econometrics 80, 387-422. [ bib ]

Shephard, N. and M. K. Pitt (1997). Likelihood analysis of non-Gaussian measurement time series. Biometrika 84, 653-667. [ bib ]

Atkinson, A. C. and N. Shephard (1996). Deletion diagnostics and transformations for time series. Journal of Forecasting 15, 1-17. [ bib ]

Harvey, A. C. and N. Shephard (1996). The estimation of an asymmetric stochastic volatility model for asset returns. Journal of Business and Economic Statistics 14, 429-434. [ bib ]

de Jong, P. and N. Shephard (1995). The simulation smoother for time series models. Biometrika 82, 339-350. [ bib | .pdf ]

Harvey, A. C., E. Ruiz, and N. Shephard (1994). Multivariate stochastic variance models. Review of Economic Studies 61, 247-264. [ bib | .pdf ]

Shephard, N. (1994a). Local scale model: state space alternative to integrated GARCH processes. Journal of Econometrics 60, 181-202. [ bib ]

Shephard, N. (1994b). Partial non-Gaussian state space. Biometrika 81, 115-131. [ bib ]

Shephard, N. (1993b). Fitting non-linear time series models, with applications to stochastic variance models. Journal of Applied Econometrics 8, S135-52. [ bib ]

Shephard, N. (1993c). Maximum likelihood estimation of regression models wit stochastic trend components. Journal of the American Statistical Association 88, 590-595. [ bib ]

Shephard, N. (1993a). Distribution of the ML estimator of an MA(1) and a local level model. Econometric Theory 9, 377-401. [ bib ]

Koopman, S. J. and N. Shephard (1992). Exact score for time series models in state space form. Biometrika 79, 823-6. [ bib ]

Shephard, N. (1991b). Numerical integration rules for multivariate inversions. Journal of Statistical Computation and Simulation 39, 37-46. [ bib ]

Shephard, N. (1991a). From characteristic function to distribution function: a simple framework for the theory. Econometric Theory 7, 519-529. [ bib ]

Harvey, A. C. and N. Shephard (1990). On the probability of estimating a deterministic component in the local level model. Journal of Time Series Analysis 11, 339-347. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2009). Financial Volatility in Continuous Time. Cambridge: Cambridge University Press. Forthcoming. [ bib ]

Castle, J. L. and N. Shephard (Eds.) (2009). The Methodology and Practice of Econometrics: papers in honour of David F. Hendry. Oxford: Oxford University Press. [ bib ]

Koopman, S. J., J. A. Doornik, and N. Shephard (2008). Statistical Algorithms for Models in State Space Form: SsfPack 3.0. London: Timberlake Consultants Press. [ bib | http ]

Koopman, S. J., A. C. Harvey, J. A. Doornik, and N. Shephard (2007). STAMP 8.0: Structural Time Series Analyser, Modeller and Predictor. London: Chapman & Hall. [ bib | http ]

Shephard, N. (Ed.) (2005). Stochastic Volatility: Selected Readings. Oxford: Oxford University Press. [ bib | http ]

Harvey, A. C., S. J. Koopman, and N. Shephard (Eds.) (2004). State Space and Unobserved Component Models: Theory and Applications. Proceedings of a Conference in Honour of James Durbin. Cambridge: Cambridge University Press. [ bib | http ]

Barndorff-Nielsen, O. E., S. Kinnebrouck, and N. Shephard (2009). Measuring downside risk: realised semivariance. In T. Bollerslev, J. Russell, and M. Watson (Eds.), Volatility and Time Series Econometrics: Essays in Honor of Robert F. Engle. Oxford University Press. Forthcoming. [ bib ]

Shephard, N. and T. G. Andersen (2009). Stochastic volatility: Origins and overview. In T. G. Andersen, R. Davis, J.-P. Kreiss, and T. Mikosch (Eds.), Handbook of Financial Time Series. Forthcoming. [ bib ]

Shephard, N. (2008). Stochastic volatility. In S. Durlauf and L. Blume (Eds.), New Palgrave Dictionary of Economics (2 ed.). Palgrave Macmillan. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2007). Variation, jumps and high frequency data in financial econometrics. In R. Blundell, T. Persson, and W. K. Newey (Eds.), Advances in Economics and Econometrics. Theory and Applications, Ninth World Congress, Econometric Society Monographs, pp. 328-372. Cambridge University Press. [ bib ]

Barndorff-Nielsen, O. E., S. E. Graversen, J. Jacod, M. Podolskij, and N. Shephard (2006). A central limit theorem for realised power and bipower variations of continuous semimartingales. In Y. Kabanov, R. Lipster, and J. Stoyanov (Eds.), From Stochastic Analysis to Mathematical Finance, Festschrift for Albert Shiryaev, pp. 33-68. Springer. [ bib ]

Doornik, J. A., D. F. Hendry, and N. Shephard (2006). Parallel computation in econometrics: A simplified approach. In J. Kontoghiorghes (Ed.), Handbook of Parallel Computing and Statistics, pp. 449-476. Chapman and Hall. [ bib ]

Shephard, N. (2006). Introduction. In N. Shephard (Ed.), Stochastic Volatility: Selected Readings, pp. 1-33. Oxford University Press. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2005a). How accurate is the asymptotic approximation to the distribution of realised volatility? In D. W. K. Andrews and J. H. Stock (Eds.), Identification and Inference for Econometric Models. A Festschrift in Honour of T.J. Rothenberg, pp. 306-331. Cambridge: Cambridge University Press. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2005b). Multipower variation and stochastic volatility. In A. Shiryaev, M. Grossinho, P. Oliveira, and M. Esquivel (Eds.), Stochastic Finance, pp. 73-82. Springer. [ bib ]

Shephard, N. (2005). Are there discontinuities in financial prices? In A. Davison, Y. Dodge, and N. Wermuth (Eds.), Celebrating Statistics: Papers in Honour of Sir David Cox on his 80th Birthday, pp. 213-231. Oxford University Press. [ bib ]

Barndorff-Nielsen, O. E., B. Nielsen, N. Shephard, and C. Ysusi (2004). Measuring and forecasting financial variability using realised variance with and without a model. In A. C. Harvey, S. J. Koopman, and N. Shephard (Eds.), State Space and Unobserved Component Models: Theory and Applications. Proceedings of a Conference in Honour of James Durbin, pp. 205-235. Cambridge: Cambridge University Press. [ bib ]

Barndorff-Nielsen, O. E. and N. Shephard (2001). Modelling by Lévy processes for financial econometrics. In O. E. Barndorff-Nielsen, T. Mikosch, and S. Resnick (Eds.), Lévy Processes - Theory and Applications, pp. 283-318. Boston: Birkhäuser. [ bib ]

Pitt, M. K. and N. Shephard (2001). Auxiliary variable based particle filters. In N. de Freitas, A. Doucet, and N. J. Gordon (Eds.), Sequential Monte Carlo Methods in Practice, pp. 273-293. New York: Springer-Verlag. [ bib ]

Rydberg, T. H. and N. Shephard (2000). A modelling framework for the prices and times of trades made on the NYSE. In W. J. Fitzgerald, R. L. Smith, A. T. Walden, and P. C. Young (Eds.), Nonlinear and Nonstationary Signal Processing, pp. 217-246. Cambridge: Isaac Newton Institute and Cambridge University Press. [ bib ]

Pitt, M. K. and N. Shephard (1999). Time varying covariances: a factor stochastic volatility approach (with discussion). In J. M. Bernardo, J. O. Berger, A. P. Dawid, and A. F. M. Smith (Eds.), Bayesian Statistics 6, pp. 547-570. Oxford: Oxford University Press. [ bib ]

Shephard, N. (1996). Statistical aspects of ARCH and stochastic volatility. In D. R. Cox, D. V. Hinkley, and O. E. Barndorff-Nielsen (Eds.), Time Series Models in Econometrics, Finance and Other Fields, pp. 1-67. London: Chapman & Hall. [ bib ]

Atkinson, A. C., S. J. Koopman, and N. Shephard (1994). Outliers and switches in time series. In P. Mandl and M. Huskova (Eds.), Asymptotic Statistics, pp. 35-48. Heidelberg: Physica-Verlag. [ bib ]

Harvey, A. C. and N. Shephard (1993). Structural time series models. In G. S. Maddala, C. R. Rao, and H. D. Vinod (Eds.), Handbook of Statistics, Volume 11. Amsterdam: Elsevier Science Publishers B V. [ bib ]