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Dynamic Stock Selection Strategies: A Structured Factor Model Framework *

Carlos M. Carvalho, Hedibert F. Lopes, and Omar Aguilar

in Bayesian Statistics 9

Published in print:
2011
Published Online:
January 2012
ISBN:
9780199694587
eISBN:
9780191731921
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199694587.003.0002
Subject:
Mathematics, Probability / Statistics

We propose a novel framework for estimating the time‐varying covariation among stocks. Our work is inspired by asset pricing theory and associated developments in Financial Index Models. We work with ... More


Factor‐augmented Error Correction Models *

Anindya Banerjee and Massimiliano Marcellino

in The Methodology and Practice of Econometrics: A Festschrift in Honour of David F. Hendry

Published in print:
2009
Published Online:
September 2009
ISBN:
9780199237197
eISBN:
9780191717314
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199237197.003.0009
Subject:
Economics and Finance, Econometrics

This chapter brings together several important strands of the econometrics literature: error-correction, cointegration, and dynamic factor models. It introduces the Factor-augmented Error Correction ... More


Forecasting in Dynamic Factor Models Subject to Structural Instability *

James H. Stock and Mark W. Watson

in The Methodology and Practice of Econometrics: A Festschrift in Honour of David F. Hendry

Published in print:
2009
Published Online:
September 2009
ISBN:
9780199237197
eISBN:
9780191717314
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199237197.003.0007
Subject:
Economics and Finance, Econometrics

This chapter assesses forecasts constructed using dynamic factor models for their reliability in the face of structural breaks. Dynamic factor models have had notable empirical forecasting successes, ... More


Particle Learning for Sequential Bayesian Computation *

Hedibert F. Lopes, Michael S. Johannes, Carlos M. Carvalho, and Nicholas G. Polson

in Bayesian Statistics 9

Published in print:
2011
Published Online:
January 2012
ISBN:
9780199694587
eISBN:
9780191731921
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199694587.003.0011
Subject:
Mathematics, Probability / Statistics

Particle learning provides a simulation‐based approach to sequential Bayesian computation. To sample from a posterior distribution of interest we use an essential state vector together with a ... More


Hierarchical modelling in time series: the factor analytic approach

Gamerman Dani and Salazar Esther

in Bayesian Theory and Applications

Published in print:
2013
Published Online:
May 2013
ISBN:
9780199695607
eISBN:
9780191744167
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199695607.003.0009
Subject:
Mathematics, Probability / Statistics

This chapter addresses the issue of combining information from a possibly large time series with a factor analytic approach. Each combination of a time series and a factor gives rise to a weight or ... More


More is not always better: Kalman filtering in dynamic factor models

Pilar Poncela and Esther Ruiz

in Unobserved Components and Time Series Econometrics

Published in print:
2015
Published Online:
January 2016
ISBN:
9780199683666
eISBN:
9780191763298
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199683666.003.0011
Subject:
Economics and Finance, Econometrics

For dynamic factor models the relationship between the mean square error of the Kalman filter estimator of the underlying factors and the number of variables in the model is established. It is shown ... More


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