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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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