Neil Shephard

Datos Biográficos

ID5729147
NOMBRENeil Shephard
NOMBRESNeil
APELLIDOShephard
FIRMASHEPHARD N
AFILIACIONESHarvard University
ORCID0000-0001-8230-9754
VERIFICADOSí
TOTAL DE OBRAS5
TOTAL DE CITAS0
TOTAL COMO AUTOR5
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN1994
AÑO MÁS RECIENTE DE PUBLICACIÓN2021
ÍNDICE H0

  • Fitting Vast Dimensional Time-Varying Covariance Models

    Cavit Pakel, Neil Shephard et al.ARTICLEJournal of Business and Economic…2021

    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.…

  • Econometric Analysis of Vast Covariance Matrices Using Composite Realized Kernels and Their Application to Portfolio Choice

    Asger Lunde, Neil Shephard et al.ARTICLEJournal of Business and Economic…2016

    We propose a composite realized kernel to estimate the ex-post covariation of asset prices. These measures can in turn be used to forecast the covariation of future asset returns. Composite realized kernels are a data-efficient method, where the covariance estimate is composed of univariate realized kernels to estimate variances and bivariate realized kernels to estimate correlations. We analyze the merits of our composite realized kernels in an …

  • Estimation of an Asymmetric Stochastic Volatility Model for Asset Returns

    Andrew Harvey, Andrew C Harvey et al.ARTICLEJournal of Business and Economic…1996

    A stochastic volatility model may be estimated by a quasi-maximum likelihood procedure by transforming to a linear state-space form. The method is extended to handle correlation between the two disturbances in the model and applied to data on stock returns

  • Stamp 5.0 Structural Time Series Analyser, Modeller and Predictor

    Guy Judge, Siem Jan Koopman et al.ARTICLEThe Economic Journal1996

    Part 1: installation procedure for STAMP. Part 2 Tutorials on structural time series modelling: getting started on simple univariate modelling tutorial on components tutorial on interventions and explanatory variables tutorial on multivariate models applications in macroeconomics and finance. Part 3 STAMP tutorials: the basic skills tutorial on graphics tutorial on data input and output tutorial on data transformation and description tutorial on …

  • [Bayesian Analysis of Stochastic Volatility Models]

    Neil Shephard, Sangjoon Kim et al.ARTICLEJournal of Business and Economic…1994