- AkaikeH. (1987). Factor Analysis and AIC. Psychometrika, 52, 317–332.
- BartholomewD. (1987). Latent Variable Models and Factor Analysis. Charles Griffin & Co. Ltd, London.
- BlackF. (1976). Studies of Stock Market Volatility Changes. Proceedings of the American Statistical Association, Business and Economic Statistics Section, 177–181.
- BollerslevT. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31, 307–327.
- BollerslevT. (1987). A Conditional Heteroskedastic Time Series Model for Speculative Prices and Rates of Return. Review of Economics and Statistics, 69, 542–547.
- BollerslevT., EngleR., and WooldridgeM. (1988). A Capital Asset Pricing Model with Time-varying Covariances. Journal of Political Economy, 96, 116–131.
- BozdoganH. and RamirezD.E. (1987). An expert model selection approach to determine the “best” pattern structure in factor analysis models. In Multivariate Statistical Modelling and Data Analysis (eds BozdoganH. and GuptaA.K.).
- BrockwellP.J., and DavisR.A. (1991). Time Series: Theory and Methods, Springer-Verlag, New York.
- ChongY.Y. and HendryD.F. (1986). Econometric evaluation of linear macroeconomics models. Review of Economics Studies, 53, 671–690.
- ChouR.Y. (1988). Volatility persistence and stock valuations: Some empirical evidence using GARCH. Journal of Applied Econometrics, 3, 279–294.
- ChristieA.A. (1982). The Stochastic Behavior of Common Stock Variances: Value, Leverage and Interest Rate Effects. Journal of Financial Economics, 10, 407–432.
- DarratA.F. and ZhongM. (2000). On testing the random-walk hypothesis: a model comparison approach. The Financial Review, 35, 105–124.
- DempsterA., LairdN., and RubinD.B. (1977). Maximum Likelihood from incomplete data via the EM algorithm. Journal of Royal Statistical Society Series B, 39, 1–38.
- DieboldF., and NerloveM. (1989). The Dynamics of Exchange Rate Volatility: A Multivariate Latente Factor ARCH Model. Journal of Applied Econometrics, 4, 1–21.
- DomowitzI., and HakkioC.S. (1985). Conditional variance and the risk premium in the foreign exchange market. Journal of International Economics, 19, 47–66.
- DonaldsonR.G. and KamstraM. (1997). An artificial neural network-GARCH model for international stock return volatility. Journal of Empirical Finance, 4, 17–46.
- EngleR.F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of the united kingdom inflation. Econometrica, 50, 987–1007.
- EngleR.F. and BollerslevT. (1986). Modeling the persistence of conditional variances. Econometric Reviews, 5, 1–50.
- EngleR.F. (1987). Multivariate ARCH with factor structures - Cointegration in variance. mimeo, University of California, San Diego.
- EngleR.F., LilienD. and RobinsR. (1987). Estimating time varying risk premia in the term structure: The ARCH-M model. Econometrica, 55, 391–408.
- EngleR., NgV.K., and RothschildM. (1990). Asset Pricing with a Factor-ARCH Structure: Empirical Estimates for Treasury Bills. Journal of Econometrics, 45, 213–237.
- EngleR. and NgV.K. (1990). An Examination of the Impact of Volatility Shocks on the Short-End of the Term Structure Based on a Factor-ARCH Model for Treasury Bills. mimeo, School of Business Administration, University of Michigan, Ann Arbor.
- FrenchK.R., SchwertG.W., and StambaughR.F. (1987). Expected Stock Returns and Volatility. Journal of Financial Economics, 19, 3–29.
- HarveyA., RuizE., and SentanaE. (1992). Unobserved component time series models with ARCH disturbances. Journal of Econometrics, 52, 129–157.
- JennrichR.I. (1978). Rotational Equivalence of Factor Loading Matrices with Specified Values. Psychometrika, 43, 421–426.
- KingM., SentanaE., and WadhwaniS. (1994). Volatility and Links between National Stock Markets. Econometrica, 62, 901–933.
- LehmanB.N., and ModestD.M. (1988). The empirical foundations of the arbitrage pricing theory. Journal of Financial Economics, 21, 213–254.
- LiuC., and RubinD.B. (1998). Maximum likelihood estimation of factor analysis using the ECME algorithm with complete and incomplete data. Statistica Sinica, 8, 729–747.
- LjungG., and BoxG. (1978). On a Measure of Lack of Fit in Time Series Models. Biometrika, 67, 297–303.
- LopesH.F., and WestM. (2004). Bayesian Model Assessment in Factor Analysis. Statistica Sinica, 14, 41–67.
- McCurdyT.H., and MorganI.G. (1988). Testing the martingale hypothesis in Deutschmark futures with models specifying the form of heteroskedasticity. Journal of Applied Econometrics, 3, 187–202.
- MilhojA. (1987). A conditional variance model for daily deviations of an exchange rate. Journal of Business and Economic Statistics, 5, 99–103.
- RossS.A. (1976). The Arbitrage Theory of Capital Asset Pricing. Journal of Economic Theory, 13, 341–360.
- RossS.A. (1977). Risk return and arbitrage. In Risk and Return in Finance (eds FriendI. and BickslerJ.L.), vol. 1. Cambridge: Ballinger.
- RoweisS., and GhahramaniZ. (1999). A Unifying Review of Linear Gaussian Models. Neural Computation, 11, 305–345.
- RubinD.B., and ThayerD.T. (1982). EM algorithms for ML factor analysis. Psychometrika, 47, 69–76.
- SchwarzG. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464.
- SentanaE. (1992). Factor Representing Portfolios in Large Asset Markets. Discussion Paper N°: 135, Financial Markets Group, London School of Economics.
- SentanaE. (1995). Quadratic ARCH models. Review of Economic Studies, 62, 639–661.
- SentanaE. (2000). The Likehood Function of Conditionally Heteroskedastic Factor Models. Anales d'économie et de Statistique, 58, 1–19.
- SharpeW.F. (1963). A simplified model for portafolio analysis. Management Science, 9, 277–293.
- ShumwayR.H., and StofferD.S. (1982). An approach to time series smoothing and forecasting using the EM algorithm. Journal of Time Series Analysis, 3, 253–264.
- WatsonM., and EngleR. (1983). Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models. Journal of Econometrics, 23, 385–400.
- WhiteH. (1980). A heteroskedasticity consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817–838.
Can the GQARCH Latent Factor Model Improve the Prediction Performance of Multivariate Financial Time Series?
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