@workingpaper {693643, title = {Some properties of the sample median of an in-fill sequence of events with an application to high frequency financial econometrics}, year = {Working Paper}, abstract = {Using an in-fill argument, the properties of the sample median of a sequence of events are established both for the case of a fixed period of time and for a period which shrinks as the sample size grows. \ The results are used to study the properties of the sample median of absolute returns under stochastic volatility. \ This estimator is invariant, asymptotically pivotal and a 1/2 breakdown estimator. \ In practice it has deep robustness to jump processes even when there are jumps of α-stable type. \ }, author = {Neil Shephard} } @unpublished {661582, title = {An estimator for predictive regression: reliable inference for financial economics}, year = {Working Paper}, abstract = {Estimating linear regression using least squares and reporting robuststandard errors is very common in financial economics, and indeed, much ofthe social sciences and elsewhere.\  \ For thick tailed predictors underheteroskedasticity this recipe for inference performs poorly, sometimesdramatically so. Here, we develop an alternative approach which delivers anunbiased, consistent and asymptotically normal estimator so long as themeans of the outcome and predictors are finite.\  The new method hasstandard errors under heteroskedasticity which are easy to reliably estimateand tests which are close to their nominal size. The procedure works wellin simulations and in an empirical exercise.\  An extension is given toquantile regression.}, author = {Neil Shephard} } @workingpaper {632883, title = {When do common time series estimands have nonparametric causal meaning?}, year = {Working Paper}, author = {Ashesh Rambachan and Neil Shephard} } @article {702001, title = {Inference and forecasting for continuous-time integer-valued trawl processes}, journal = {Journal of Econometrics}, volume = {236}, number = {2}, year = {2023}, month = {2023}, pages = {105476}, abstract = {This paper develops likelihood-based methods for estimation, inference, model selection, and forecasting of continuous-time integer-valued trawl processes. The full likelihood of integer-valued trawl processes is, in general, highly intractable, motivating the use of composite likelihood methods, where we consider the pairwise likelihood in lieu of the full likelihood. Maximizing the pairwise likelihood of the data yields an estimator of the parameter vector of the model, and we prove consistency and, in the short memory case, asymptotic normality of this estimator. When the underlying trawl process has long memory, the asymptotic behaviour of the estimator is more involved; we present some partial results for this case. The pairwise approach further allows us to develop probabilistic forecasting methods, which can be used to construct the predictive distribution of integer-valued time series. In a simulation study, we document the good finite sample performance of the likelihood-based estimator and the associated model selection procedure. Lastly, the methods are illustrated in an application to modelling and forecasting financial bid-ask spread data, where we find that it is beneficial to carefully model both the marginal distribution and the autocorrelation structure of the data.}, url = {https://www.sciencedirect.com/science/article/pii/S0304407623001926}, author = {Mikkel Bennedsen and Lunde, Asger and Neil Shephard and Almut E.D. Veraart} } @article {697425, title = {Interactions with Sir David R. Cox}, journal = {Harvard Data Science Review}, volume = {5}, number = {2}, year = {2023}, month = {2023}, url = {https://hdsr.mitpress.mit.edu/pub/qpgr28nf/release/1?readingCollection=d6860ef9}, author = {Neil Shephard} } @article {661879, title = {Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective}, journal = {Quantitative Economics}, volume = {12}, year = {2021}, month = {2021}, pages = {1171-1196}, abstract = {In panel experiments, we randomly expose multiple units to different interventions and measure their subsequent outcomes, sequentially repeating the procedure numerous times. Using the potential outcomes framework, we define finite population dynamic causal effects that capture the relative effectiveness of alternative treatment paths. For the leading example, known as the lag-p dynamic causal effects, we provide a nonparametric estimator that is unbiased over the randomization distribution. We then derive the finite population limiting distribution of our estimators as either the sample size or the duration of the experiment increases. Our approach provides a new technique for deriving finite population central limit theorems that exploits the underlying Martingale property of unbiased estimators. We further describe two methods for conducting inference on dynamic causal effects: a conservative test for weak null hypotheses of zero average causal effects using the limiting distribution and an exact randomization-based test for sharp null hypotheses. We also derive the finite population limiting distribution of commonly-used linear fixed effects estimators, showing that these estimators perform poorly in the presence of dynamic causal effects. We conclude with a simulation study and an empirical application in which we reanalyze a lab experiment on cooperation.}, author = {Neil Shephard and Iavor Bojinov and Ashesh Rambachan} } @article {642785, title = {Fitting Vast Dimensional Time-Varying Covariance Models}, journal = {Journal of Business and Economic Statistics}, volume = {39}, year = {2021}, month = {2019}, pages = {652-668}, abstract = {Estimation of time-varying covariances is a key input in risk management and\ asset allocation. ARCH-type multivariate models are used widely for this purpose.\ Estimation of such models is computationally costly and parameter estimates are\ meaningfully biased when applied to a moderately large number of assets. Here we\ propose a novel estimation approach that suffers from neither of these issues, even\ when the number of assets is in the hundreds. The theory of this new method is\ developed in some detail. The performance of the proposed method is investigated\ using extensive simulation studies and empirical examples.}, author = {Robert F Engle and Pakel, Cavit and Kevin K. Shephard and Neil Shephard} } @report {632986, title = {Where is the money going? Estimating government spending on different university degrees}, year = {2019}, institution = {Institute of Fiscal Studies}, address = {London}, url = {https://www.ifs.org.uk/uploads/publications/bns/BN244.pdf}, author = {Jack Britton and Laura van der Erve and Neil Shephard and Chris Belfield} } @article {546281, title = {Is improving access to university enough? Socio economic gaps in the earnings of English graduates}, journal = {Oxford Bulletin of Economics and Statistics}, volume = {81}, year = {2019}, month = {2018}, pages = {328-368}, abstract = {Much research and policy attention has been on socio economic gaps in participation at\ university, but little attention has been paid to gaps in earnings. This paper addresses this\ shortfall using tax and student loan administrative data to investigate the earnings of English\ graduates up to their mid thirties by socio economic background. We find that \ graduates from\ higher income families (from the top fth of the income distribution of those enrolled in university) have average earnings which are 20\% higher than those from lower income families.\ Once we condition on institution and subject choices, this premium roughly halves, to around 10\%. The premium grows with age and is larger for men, in particular for men at the most\ selective universities. We follow Chetty et al. (2017) and estimate English mobility scorecards\ by university and subject, highlighting the good performance of medicine, economics, law, business, engineering, technology, math, computer science and architecture courses as well as the\ prominent London-based universities.}, author = {Jack Britton and Lorraine Deardon and Neil Shephard and Anna Vignoles} } @article {546276, title = {Time series experiments and causal estimands: exact randomization tests and trading}, journal = {Journal of the American Statistical Association}, volume = {114}, year = {2019}, month = {2019}, pages = {1665-82}, abstract = {We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. \ Our approach allows the estimation of a broad class of these estimands and exact randomization based p-values for testing causal effects, without imposing stringent assumptions. \ We further derive a general central limit theorem that can be used to conduct conservative tests and build confidence intervals for causal effects. \ Finally, we provide three methods for generalizing our approach to multiple units that are receiving the same class of treatment, over time. \ We test our methodology on simulated "potential autoregressions,"which have a causal interpretation. \ Our methodology is partially inspired by data from a large number of experiments carried out by a financial company who compared the impact of two different ways of trading equity futures contracts. \ We use our methodology to make causal statements about their trading methods.}, author = {Iavor Bojinov and Neil Shephard} } @article {360976, title = {A comparison of sample survey measures of earnings of English graduates with administrative data}, journal = {Journal of the Royal Statistical Society, Series A}, volume = {182}, year = {2019}, month = {2018}, pages = {719-754}, author = {Jack Britton and Neil Shephard and Anna Vignoles} } @article {360971, title = {Moment conditions and Bayesian nonparametrics}, journal = {Journal of the Royal Statistical Society, Series B}, volume = {81}, year = {2019}, month = {2018}, pages = {5-43}, author = {Bornn, Luke and Neil Shephard and Reza Solgi} } @article {619826, title = {A Nonparametric Bayesian Approach to Copula Estimation}, journal = {Journal of Statistical Computation and Simulation}, volume = {201}, year = {2018}, pages = {1081-1105}, abstract = {We propose a novel Dirichlet-based P{\'o}lya tree (D-P tree) prior on the copula and based on the D-P tree prior, a nonparametric Bayesian inference procedure. Through theoretical analysis and simulations, we are able to show that the flexibility of the D-P tree prior ensures its consistency in copula estimation, thus able to detect more subtle and complex copula structures than earlier nonparametric Bayesian models, such as a Gaussian copula mixture. Furthermore, the continuity of the imposed D-P tree prior leads to a more favourable smoothing effect in copula estimation over classic frequentist methods, especially with small sets of observations. We also apply our method to the copula prediction between the S\&P 500 index and the IBM stock prices during the 2007{\textendash}08 financial crisis, finding that D-P tree-based methods enjoy strong robustness and flexibility over classic methods under such irregular market behaviours.}, author = {Neil Shephard and Shaoyang Ning} } @article {360986, title = {Continuous time analysis of fleeting discrete price moves}, journal = {Journal of the American Statistical Association}, volume = {112}, year = {2017}, month = {2017}, pages = {1090-1106}, author = {Neil Shephard and Justin J Yang} } @article {360811, title = {Econometric analysis of vast covariance matrices using composite realized kernels and their application to portfolio choice}, journal = {Journal of Business and Economic Statistics}, volume = {34}, year = {2015}, pages = {504-518}, author = {Lunde, Asger and Kevin Sheppard and Neil Shephard} } @inbook {360826, title = {Likelihood Inference for Exponential-Trawl Processes}, booktitle = {The Fascination of Probability, Statistics and their Applications}, year = {2015}, pages = {251-281}, publisher = {Springer}, organization = {Springer}, url = {http://www.springer.com/us/book/9783319258249$\#$aboutBook}, author = {Neil Shephard and Justin Yang}, editor = {Mark Podolskij and Robert Stelzer and S Thorbjornsen} } @inbook {360821, title = {Martingale unobserved component models}, booktitle = {Unobserved Components and Time Series Econometrics}, year = {2015}, pages = {218-249}, publisher = {Oxford University Press}, organization = {Oxford University Press}, address = {Oxford}, author = {Neil Shephard}, editor = {Koopman, Siem Jan and Neil Shephard} } @book {106886, title = {Unobserved Components and Time Series Econometrics}, year = {2015}, pages = {370}, publisher = {Oxford University Press}, organization = {Oxford University Press}, address = {Oxford}, url = {https://global.oup.com/academic/product/unobserved-components-and-time-series-econometrics-9780199683666?cc=us\&lang=en\&}, editor = {Koopman, Siem Jan and Neil Shephard} } @article {360816, title = {Multivariate Rotated ARCH models}, journal = {Journal of Econometrics}, volume = {179}, year = {2014}, pages = {16-30}, author = {Noureldin, Diaa and Kevin Sheppard and Neil Shephard} } @article {107126, title = {Integer value trawl processes: a class of stationary infinitely divisible processes}, journal = {Scandanavian Journal of Statistics}, volume = {41}, year = {2014}, pages = {693-724}, author = {Barndorff-Nielsen, Ole E. and Lunde, Asger and Neil Shephard and Veraart, Almut} } @article {107146, title = {Integer-valued Levy processes and low latency financial econometrics}, journal = {Quantitative Finance}, volume = {12}, year = {2012}, pages = {587-605}, author = {Barndorff-Nielsen, Ole E. and Pollard, David G. and Neil Shephard} } @article {107136, title = {Multivariate high-frequency-based volatility (HEAVY) models}, journal = {Journal of Applied Econometrics}, volume = {27}, year = {2012}, pages = {907-933}, author = {Neil Shephard and Noureldin, Diaa and Sheppard, Kevin K} } @article {107166, title = {Subsampling realised kernels}, journal = {Journal of Econometrics}, volume = {160}, year = {2011}, pages = {204-219}, author = {Barndorff-Nielsen, Ole E. and Hansen, Peter R and Lunde, Asger and Neil Shephard} } @article {107161, title = {Nuisance parameters, composite likelihoods and a panel of GARCH models}, journal = {Statistica Sinica}, volume = {21}, year = {2011}, pages = {307-329}, author = {Pakel, Cavit and Neil Shephard and Sheppard, Kevin K} } @article {107156, title = {Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading}, journal = {Journal of Econometrics}, volume = {162}, year = {2011}, pages = {149-169}, author = {Barndorff-Nielsen, Ole E. and Hansen, Peter R and Lunde, Asger and Neil Shephard} } @article {107151, title = {Bayesian inference based only on a simulated likelihood}, journal = {Econometric Theory}, volume = {27}, year = {2011}, pages = {933-956}, author = {Flury, Thomas and Neil Shephard} } @article {106966, title = {Realised volatility}, journal = {Journal of Econometrics}, volume = {160}, year = {2011}, editor = {Meddahi, Nour and Mykland, Per and Neil Shephard} } @inbook {109681, title = {Measuring downside risk: realised semivariance}, booktitle = {Volatility and Time Series Econometrics: Essays in Honor of Robert F. Engle}, year = {2010}, pages = {117-136}, publisher = {Oxford University Press}, organization = {Oxford University Press}, edition = {(Edited by T. Bollerslev, J. Russell and M. Watson)}, author = {Barndorff-Nielsen, Ole E. and Kinnebrouk, Silvia and Neil Shephard} } @inbook {109626, title = {Measuring and modelling volatility}, booktitle = {Encyclopedia of Quantitative Finance}, year = {2010}, pages = {1898-1901}, publisher = {John Wiley and Sons, Ltd}, organization = {John Wiley and Sons, Ltd}, edition = {(edited by Rama Cont)}, address = {Chichester, UK}, author = {Barndorff-Neilsen, Ole E. and Neil Shephard} } @article {107176, title = {Deferred fees for universities}, journal = {Economic Affairs}, volume = {30}, number = {2}, year = {2010}, pages = {40-44}, author = {Neil Shephard} } @article {107171, title = {Realising the future: forecasting with high frequency based volatility (HEAVY) models}, journal = {Journal of Applied Econometrics}, volume = {25}, year = {2010}, pages = {197-231}, author = {Neil Shephard and Sheppard, Kevin K} } @website {106986, title = {Realized Library }, year = {2010}, abstract = {Our "Realized library" contains daily non-parametric measures of how volatility financial assets or indexes were in the past. Each day{\textquoteright}s volatility measure depends solely on financial data from that day. They are driven by the use of the latest innovations in econometric modelling and theory to design them, while we draw our high frequency data from the Reuters DataScope Tick History database. Realised measures are not volatility forecasts. However, some researchers use these measures as an input into forecasting models. The realized measures are computed every night and recorded on the website. }, url = {http://realized.oxford-man.ox.ac.uk/}, author = {Lunde, Asger and Neil Shephard and Sheppard, Kevin K} } @inbook {109686, title = {Stochastic Volatility: Origins and Overview}, booktitle = {Handbook of Financial Time Series}, year = {2009}, pages = {233-254}, publisher = {Springer}, organization = {Springer}, edition = {(Edited by T.G. Andersen, R.A. Davis, J.P. Kreiss and T. Mikosch)}, author = {Andersen, Torben G. and Neil Shephard} } @article {107256, title = {Realised kernels in practice: trades and quotes}, journal = {Econometrics Journal }, volume = {12}, year = {2009}, pages = {C1-C32}, author = {Barndorff-Nielsen, Ole E. and Hansen, Peter R and Lunde, Asger and Neil Shephard} } @article {107251, title = {Testing the assumptions behind importance sampling}, journal = {Journal of Econometrics}, volume = {149}, year = {2009}, pages = {2-11}, author = {Koopman, Siem Jan and Drew Creal and Neil Shephard} } @book {106951, title = {The Methodology and Practice of Econometrics: A Festschrift in Honour of David F. Hendry}, year = {2009}, publisher = {Oxford University Press}, organization = {Oxford University Press}, editor = {Castle, Jennifer L. and Neil Shephard} } @inbook {109691, title = {Stochastic volatility}, booktitle = {New Palgrave Dictionary of Economics, 2nd edition}, year = {2008}, publisher = {MacMillan}, organization = {MacMillan}, edition = {(edited by Steven Durlauf and Lawrence Blume)}, author = {Neil Shephard} } @article {107266, title = {Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise}, journal = {Econometrica}, volume = {76}, year = {2008}, pages = {1481-1536}, author = {Barndorff-Nielsen, Ole E. and Hansen, Peter R and Lunde, Asger and Neil Shephard} } @article {107261, title = {The ACR model: a multivariate dynamic mixture autoregression}, journal = {Oxford Bulletin of Economics and Statistics}, volume = {70}, year = {2008}, pages = {583-618}, author = {Bec, Frederique and Rahbek, Anders and Neil Shephard} } @book {106976, title = {Statistical Algorithms for Models in State Space Form: SsfPack 3.0}, year = {2008}, publisher = {Timberlake Consultants Press}, organization = {Timberlake Consultants Press}, author = {Koopman, Siem Jan and Neil Shephard and Doornik, Jurgen A} } @inbook {109696, title = {Variation, jumps and high frequency data in financial econometrics}, booktitle = {Advances in Economics and Econometrics. Theory and Applications, Nineth World Congress}, year = {2007}, pages = {328-372}, publisher = {Cambridge University Press}, organization = {Cambridge University Press}, edition = {(edited by Richard Blundell, Persson Torsten and Whitney K Newey)}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {107271, title = {Stochastic volatility with leverage: fast and efficient likelihood inference}, journal = {Journal of Econometrics}, volume = {140}, year = {2007}, pages = {425-449}, author = {Chib, Siddhartha and Omori, Yasuhiro and Nakajima, Jouchi and Neil Shephard} } @article {109881, title = {Realised variance and market microstructure noise}, journal = {Journal of Business and Economic Statistics}, year = {2006}, pages = {179-181}, author = {Neil Shephard and Barndorff-Nielsen, Ole E.}, editor = {Hansen and Lunde} } @inbook {109716, title = {A central limit theorem for realised power and bipower variations of continious semimartingales}, booktitle = {From Stochastic Analysis to Mathematical Finance, Festschrift for Albert Shiryaev}, year = {2006}, pages = {33-68}, publisher = {Springer}, organization = {Springer}, edition = {(edited by Kabanov, Y and R Lipster)}, author = {Barndorff-Nielsen, Ole E. and Gravensen, Jean Jacod and Mark Podolskij} } @inbook {109701, title = {Parallel computation in econometrics: a simplified approach}, booktitle = {Handbook of Parallel Computing and Statistics}, year = {2006}, pages = {449-476}, publisher = {Chapman and Hall}, organization = {Chapman and Hall}, edition = {(edited by E.J. Kontoghiorghes)}, author = {Doornik, Jurgen A and Hendry, David F. and Neil Shephard} } @article {107301, title = {Impact of jumps on returns and realised variances: econometric analysis of time-deformed L{\'e}vy processes"}, journal = {Journal of Econometrics}, volume = {131}, year = {2006}, pages = {217-252}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {107296, title = {Econometrics of testing for jumps in financial economics using bipower variation}, journal = {Journal of Financial Econometrics}, volume = {4}, year = {2006}, pages = {1-30}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {107291, title = {Limit theorems for multipower variation in the presence of jumps}, journal = {Stochastic Processes and Their Applications}, volume = {116}, year = {2006}, pages = {796-806}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard and Winkel, Matthias} } @article {107286, title = {Limit theorems for bipower variation in financial econometrics}, journal = {Econometric Theory}, volume = {22}, year = {2006}, pages = {677-719}, author = {Barndorff-Nielsen, Ole E. and Graversen, Sven Erik and Jacod, Jean and Neil Shepherd} } @article {107281, title = {Analysis of high dimensional multivariate stochastic volatility models}, journal = {Journal of Econometrics}, volume = {132}, year = {2006}, pages = {341-371}, author = {Chib, Siddhartha and Nardari, Federico and Neil Shephard} } @article {107276, title = {Inference for adaptive series models: stochastic volatility and conditionally Gaussian state space form}, journal = {Econometrics Reviews}, volume = {25}, year = {2006}, pages = {219-244}, author = {Bos, Charles and Neil Shephard} } @inbook {109736, title = {How accurate is the asymptotic approximation to the distribution of realised volatility?}, booktitle = {Identification and Inference for Econometric Models. A Festschrift for Tom Rotheberg}, year = {2005}, pages = {306-331}, publisher = {Cambridge University Press}, organization = {Cambridge University Press}, edition = {(edited by Donald W.K. Andrews and James H. Stock)}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @inbook {109731, title = {Are there discontinuities in financial prices?}, booktitle = {Celebrating Statistics: Papers in Honour of Sir David Cox on his 80th Birthday}, year = {2005}, pages = {213-231}, publisher = {Oxford University Press}, organization = {Oxford University Press}, edition = {(edited by Anthony Davison, Yadolah Dodge and Nanny Wermuth)}, author = {Neil Shephard} } @inbook {109721, title = {Introduction}, booktitle = {Stochastic Volatility}, year = {2005}, pages = {1-33}, publisher = {Oxford University Press}, organization = {Oxford University Press}, editor = {Neil Shephard} } @inbook {109706, title = {Multipower variation and stochastic volatility}, booktitle = {Stochastic Finance }, year = {2005}, pages = {73-82}, publisher = {Springer}, organization = {Springer}, edition = {(edited by A.N. Shiryaev, M.R. Grossinho, P.E. Oliveira, M.L. Esquivel)}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {107316, title = {Power variation and time change}, journal = {Teoriya Veroyatnostei i ee Primeneniya}, volume = {50}, year = {2005}, note = {Reprinted in Theory of Probability and Its Applications, 2005, 50, 1-15.}, pages = {115-130}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @book {106956, title = {Stochastic Volatility: Selected Readings}, year = {2005}, pages = {536}, publisher = {Oxford University Press}, organization = {Oxford University Press}, author = {Neil Shephard} } @inbook {109746, title = {Measuring and forecasting financial variability using realised variance with and without a model}, booktitle = {State Space and Unobserved Component Models: Theory and Applications. Proceedings of a Conference in Honour of James Durbin}, year = {2004}, pages = {205-235}, publisher = {Cambridge University Press}, organization = {Cambridge University Press}, edition = {(edited by Andrew C. Harvey, Siem Jan Koopman and Neil Shephard)}, author = {Barndorff-Nielsen, Ole E. and Nielsen, Bent and Ysusi, Carla and Neil Shephard} } @article {108756, title = {Power and bipower variation with stochastic volatility and jumps}, journal = {(with discussion) Journal of Financial Econometrics}, volume = {2}, year = {2004}, note = {Reprinted in "Financial Risk Measurement and Management" (editor Frank X. Diebold), in Edward Elgar Publishers, 2012.}, pages = {1-48}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {107456, title = {Power variation and stochastic volatility: a review and some new results}, journal = {Journal of Applied Probability}, volume = {41A}, year = {2004}, note = {This volume was in honour of Christopher C. Hyde}, pages = {133-143}, author = {Barndorff-Nielsen, Ole E. and Graversen, Sven Erik and Neil Shephard} } @article {107341, title = {Econometric analysis of realised covariation: high frequency based covariance, regression and correlation in financial economics}, journal = {Econometrica}, volume = {72}, year = {2004}, pages = {885-9225}, author = {Barndorff-Neilsen, Ole E. and Graversen, Sven Erik and Neil Shephard} } @article {107331, title = {Likelihood-based estimation of latent generalised ARCH structures}, journal = {Econometrica}, volume = {72}, year = {2004}, pages = {885-925}, author = {Fiorentini, G and Sentana, Enrique and Neil Shephard} } @book {106961, title = {State Space and Unobserved Component Models: Theory and Applications}, year = {2004}, publisher = {Cambridge Press}, organization = {Cambridge Press}, author = {Harvey, Andrew C. and Koopman, Siem Jan and Neil Shephard} } @article {108776, title = {Realised power variation and stochastic volatility variance}, journal = {Bernoulli}, volume = {9}, year = {2003}, pages = {243-265}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {108771, title = {Integrated OU processes and non-Gaussian OU-based stochastic volatility models}, journal = {Scandinavian Journal of Statistics}, volume = {30}, year = {2003}, pages = {277-295}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {108766, title = {Dynamics of trade-by-trade price movements: decomposition and models}, journal = {Journal of Financial Econometrics}, volume = {1}, year = {2003}, pages = {2-25}, author = {Rydberg, Trina H. and Neil Shephard} } @article {108761, title = {Likelihood analysis of a first oder autoregrassive model with exponential innovations}, journal = {Journal of Time Series Analysis}, volume = {24}, year = {2003}, pages = {337-344}, author = {Nielsen, Bent and Neil Shephard} } @article {109891, title = {Comment on: Numeral techniques for maximum likelihood estimation of continuous-time diffusion processes, by Garland Durham and Ron Gallant}, journal = {Journal of Business and Economic Statistics}, year = {2002}, pages = {325-327}, author = {Neil Shephard} } @article {108821, title = {Markov Chain Monte Carlo methods for stochastic volatility models}, journal = {Journal of Econometrics}, volume = {108}, year = {2002}, pages = {281-316}, author = {Chib, Siddhartha and Nardari, Federico and Neil Shephard} } @article {108811, title = {Econometric analysis of realised volatility and its use in estimating stochastic volatility models}, journal = {Journal of the Royal Statistical Society, Series B}, volume = {63}, year = {2002}, note = {Reprinted in "Stochastic Volatility: Selected Readings," (editor Neil Shephard), Oxford University Press, 480-514, 2005. Reprinted in "Financial Risk Measurement and Management" (editor Francis X. Diebold), Edward Elgar.}, pages = {253-280}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {108806, title = {Some recent developments in stochastic volatility modelling}, journal = {Quantitative Finance}, volume = {2}, year = {2002}, pages = {11-23}, author = {Barndorff-Nielsen, Ole E. and Nicolato, Elisa and Neil Shephard} } @article {108791, title = {Computationally-intensive econometrics using a distributed matrix-programming}, journal = {Philosophical Transactions of the Royal Society of London, Series A}, volume = {30}, year = {2002}, pages = {1245-1266}, author = {Doornik, Jurgen A and Hendry, David F. and Neil Shephard} } @article {108781, title = {Estimating quardratic variation using realised variance}, journal = {Journal of Applied Econometrics}, volume = {17}, year = {2002}, pages = {457-477}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @inbook {109831, title = {Modelling by Levy processes for financial econometrics}, booktitle = {Theory and Application }, year = {2001}, pages = {283-318}, publisher = {Birkhauser}, organization = {Birkhauser}, edition = {(edited by Ole E. Barndordd-Neilsen, Thomas Mikosch and Sid Resnick)}, address = {New York}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @inbook {109826, title = {Auxiliary variable particle filters}, booktitle = {Sequential Monte Carlo Methods in Practice}, year = {2001}, pages = {273-293}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, edition = {(edited by A. Doucet, J.F.G de Freitas and N.J. Gordon)}, address = {New York}, author = {Pitt, Michael J and Neil Shephard} } @article {108841, title = {Non-Gaussian Ornstein-Uhlenbeck-based models and some of their uses in financial economics}, journal = {(with discussion) Journal of the Royal Statistical Society, Series B}, volume = {63}, year = {2001}, pages = {167-241}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {108836, title = {Likelihood inference for discretely observed non-linear diffusions}, journal = {Econometrica}, volume = {69}, year = {2001}, pages = {959-993}, author = {Elerian, Ola and Chib, Siddhartha and Neil Shephard} } @article {108826, title = {Normal modified stable processes}, journal = {Theory of Probability and Mathematical Statistics}, year = {2001}, pages = {1-19}, author = {Barndorff-Nielsen, Ole E. and Neil Shephard} } @article {109896, title = {Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives}, journal = {Journal of the Royal Statistical Society}, volume = {Series B}, number = {62}, year = {2000}, pages = {30-32}, author = {Neil Shephard}, editor = {Durbin and Koopman} } @inbook {109841, title = {A modelling framework for the prices and times made on the New York stock exchange}, booktitle = {Non-Statopnary and Non-Linear Signal Extraction}, year = {2000}, publisher = {Issac Newton Institute Series, Cambridge University Press}, organization = {Issac Newton Institute Series, Cambridge University Press}, edition = {(edited by W.J. Fitzgerald, R.L. Smith, A.T. Walden and P.C. Young)}, address = {Cambridge}, author = {Rydberg, Trina H. and Neil Shephard} } @inbook {109906, title = {State space modelling and simulation filter methods}, booktitle = { Proceedings of 52nd session of International Statistica Institute}, volume = {Book 1}, year = {1999}, pages = {187-190}, address = {Helsinki, Finland}, author = {Neil Shephard} } @inbook {109856, title = {Time varying covariances: a factor stochastic volatility approach}, booktitle = {Bayesian Statistics 6, Proceedings of the Sixth Valencia International Meeting}, year = {1999}, pages = {547-570}, publisher = {Oxford University Press}, organization = {Oxford University Press}, edition = {(edited by J.M. Bernardo, J.O. Berger, A.P. Dawid and A.F.M Smith)}, address = {Oxford}, author = {Pitt, Michael K. and Neil Shephard} } @article {108866, title = {Analytic convergence rates and parameterisation issues for the Gibbs sampler applied to state space models}, journal = {Journal of Time Series Analysis}, volume = {20}, year = {1999}, pages = {63-85}, author = {Pitt, Michael J and Neil Shephard} } @article {108856, title = {Filtering via simulation: auxiliary particle filter}, journal = {Journal of the American Statistical Association}, volume = {94}, year = {1999}, pages = {590-599}, author = {Pitt, Michael J and Neil Shephard} } @article {108851, title = {Statistical Algorithms for Models in State Space Form using SsfPack 2.2}, journal = {Econometrics Journal}, volume = {2}, year = {1999}, pages = {107-160}, author = {Koopman, Siem Jan and Doornik, Jurgen A and Neil Shephard} } @article {108881, title = {Stochastic volatility: likelihood inference and comparison with ARCH models}, journal = {Review of Economic Studies}, volume = {63}, year = {1998}, note = {Reprinted in "Recent Developments in Time Series", (editors Stephen Leybourne and Paul Newbold), in "The International Library of Critical Writings in Econometrics, Volume 2" Edward Elgar Publishers, 2003, 196-228. Reprinted in "Stochastic Volatility: Selected Readings," (editor N. Shephard), 2005, 283-322, Oxford University Press.}, pages = {361-393}, author = {Sangjoon, Kim and Neil Shephard and Chib, Siddhartha} } @article {108871, title = {Likelihood inference for limted dependent processes}, journal = {Econometrics Journal}, volume = {1}, year = {1998}, pages = {C174-C202}, author = {Manrique, Aurora and Neil Shephard} } @article {109931, title = {Antithetic MCMC for non-Gaussian measurements with applications to stochastic volatility}, journal = {Journal of the American Statistical Association}, number = {Proceedings of the Bayesian Statistics Section}, year = {1997}, pages = {81-86}, author = {Pitt, Michael K. and Neil Shephard} } @article {108886, title = {Likelihood analysis of non-Gaussian measurement time series}, journal = {Biometrika}, volume = {84}, year = {1997}, note = {Reprinted in "Readings in Unobserved Component Models," A.C. Harvey and T. Proietti, 2005, 368-385, Oxford University Press.}, pages = {653-667}, author = {Pitt, Michael K. and Neil Shephard} } @article {106971, title = {Cointegration and dynamics in Economics}, journal = {Journal of Econometrics}, volume = {80}, year = {1997}, editor = {Hendry, David F. and Neil Shephard} } @inbook {109866, title = {Statistical aspects of ARCH and stochastic volatility}, booktitle = {Time Series Models in Econometrics, Finance and Other Fields}, year = {1996}, note = {Reprinted in the Survey of Applied and Industrial Mathematics, issue on Financial and insurance mathematics, 3, 764-826, Scientific Publisher TVP, Moscow, 1996 (in Russian).}, pages = {1-67}, publisher = {Chapman \& Hall}, organization = {Chapman \& Hall}, edition = {(edited by D.R. Cox, David V. Hinkley and Ole E. Barndorff-Neilsen)}, address = {London}, author = {Neil Shephard} } @article {109101, title = {Deletion diagnostics and transformations for time series}, journal = {Journal of Forecasting}, volume = {15}, year = {1996}, pages = {1-17}, author = {Atkinson, Anthony C. and Neil Shephard} } @article {109096, title = {Estimation of an asymmetric model of asset prices}, journal = {Journal of Business and Economic Statistics}, volume = {14}, year = {1996}, pages = {429-434}, author = {Harvey, Andrew C. and Neil Shephard} } @article {109086, title = {Detecting shocks: outliers and breaks in time series}, journal = {Journal of Econometrics}, volume = {80}, year = {1996}, pages = {387-422}, author = {Atkinson, Anthony C. and Koopman, Siem Jan and Neil Shephard} } @article {109116, title = {The simulation smoother for time series models}, journal = {Biometrika}, volume = {82}, year = {1995}, note = {Reprinted in "Readings in Unobserved Component Models," A.C. Harvey and T. Proietti, 2005, 354-367, Oxford University Press.}, pages = {339-350}, author = {de Jong, Piet and Neil Shephard} } @book {106981, title = {STAMP: Structural Time Series Analyser, Modeller and Predictor}, year = {1995}, publisher = {Timberlake Consultants Press}, organization = {Timberlake Consultants Press}, edition = {5}, author = {Koopman, Siem Jan and Harvey, Andrew C. and Doornik, Jurgen A and Neil Shephard} } @article {109936, title = {Bayesian analysis of stochastic volatility models}, journal = {Journal of Business and Economic Statistics}, number = {11}, year = {1994}, pages = {406-410}, author = {Sangjoon, Kim and Neil Shephard} } @inbook {109871, title = {Outliers and switches in time series}, booktitle = {Asymptotic Statistics}, year = {1994}, pages = {35-48}, publisher = {Physica-Verlag}, organization = {Physica-Verlag}, edition = {(edited by P. Mandl and M. Huskova)}, address = {Heidelberg}, author = {Atkinson, Anthony C. and Koopman, Siem Jan and Neil Shephard} } @article {109586, title = {A local scale model: state space alternatives to integrated GARCH processes}, journal = {Journal of Econometrics}, volume = {60}, year = {1994}, pages = {181-202}, author = {Neil Shephard} } @article {109581, title = {Partial non-Gaussian time series models}, journal = {Biometrika}, volume = {81}, year = {1994}, pages = {115-131}, author = {Neil Shephard} } @article {109131, title = {Multivariate stochastic variance models}, journal = {Review of Economic Studies}, volume = {61}, year = {1994}, note = {Reprinted in "ARCH: Selected Readings," (editor Robert F. Engle), 1995, 256-276, Oxford University Press. Reprinted in "Recent Developments in Time Series," (editors Stephen Leybourne and Paul Newbold), Edward Elgar Publishers, 2003, 135-152. Reprinted in "Stochastic Volatility: Selected Readings," (editor Neil Shephard), Oxford University Press, 156-176, 2005.}, pages = {247-264}, author = {Harvey, Andrew C. and Ruiz, Esther and Neil Shephard} } @inbook {109876, title = {Structural time series models}, booktitle = {Handbook of Statistics}, volume = {Vol. 11:Econometrics}, year = {1993}, pages = {261-302}, publisher = {North Holland}, organization = {North Holland}, edition = {(edited by G.S. Maddala, C.R. Rao and H.D. Vinod)}, address = {Amsterdam}, author = {Harvey, Andrew C. and Neil Shephard} } @article {109601, title = {Distribution of the ML estimator of a MA(1) and a local level model}, journal = {Econometric Theory}, volume = {9}, year = {1993}, pages = {377-401}, author = {Neil Shephard} } @article {109596, title = {Maximum likelihood estimation of regression models with stochastic trend components }, journal = {Journal of the American Statistical Association}, volume = {84}, year = {1993}, pages = {590-595}, author = {Neil Shephard} } @article {109591, title = {Fitting nonlinear time series models with applications to stochastic variance models}, journal = {Journal of Applied Econometrics}, volume = {8}, year = {1993}, note = {Reprinted in "Econometric Inference using Simulation Techniques" (editors B.W. Brown, Alain Monfort and Herman K. Van Dijk), Chichester: John Wiley \& Sons, 1995, 151-168.}, pages = {S135-152} } @article {109941, title = {Tabulation of Farebrother{\textquoteright}s test for linear restrictions in linear regression models under heteroscedasticity}, journal = {Econometric Theory}, volume = {8}, year = {1992}, pages = {583-584}, author = {Neil Shephard} } @article {109606, title = {The exact score for time series models in state space form}, journal = {Biometrika}, volume = {79}, year = {1992}, pages = {823-826}, author = {Koopman, Siem Jan and Neil Shephard} } @article {109616, title = {From characteristic function to distribution function: a simple framework for the theory}, journal = {Econometric Theory}, volume = {7}, year = {1991}, pages = {519-529}, author = {Neil Shephard} } @article {109611, title = {Numerical integration rules for multivariate inversions}, journal = {Journal of Statistical Computation and Simulation}, volume = {39}, year = {1991}, pages = {37-46}, author = {Neil Shephard} } @article {109946, title = {The singular-value decomposition of the first-order difference matrix}, journal = {Econometric Theory}, number = {6}, year = {1990}, pages = {119-120}, author = {Neil Shephard} } @article {109621, title = {On the probability of estimating a deterministic component in the local level model}, journal = {Journal of Time Series Analysis}, volume = {11}, year = {1990}, pages = {339-347}, author = {Harvey, Andrew C.} }