A Generalized Factor Model with Local Factors
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DOI: 10.21799/frbp.wp.2019.23
Note: Superseded by Working Paper 21-15
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- Simon Freyaldenhoven, 2017. "A Generalized Factor Model with Local Factors," 2017 Papers pfr361, Job Market Papers.
References listed on IDEAS
- Shukla, Ravi & Trzcinka, Charles, 1990. "Sequential Tests of the Arbitrage Pricing Theory: A Comparison of Principal Components and Maximum Likelihood Factors," Journal of Finance, American Finance Association, vol. 45(5), pages 1541-1564, December.
- Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2011.
"Sectoral versus Aggregate Shocks: A Structural Factor Analysis of Industrial Production,"
Journal of Political Economy, University of Chicago Press, vol. 119(1), pages 1-38.
- Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2008. "Sectoral vs. Aggregate Shocks: A Structural Factor Analysis of Industrial Production," NBER Working Papers 14389, National Bureau of Economic Research, Inc.
- Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2008. "Sectoral vs. aggregate shocks : a structural factor analysis of industrial production," Working Paper 08-07, Federal Reserve Bank of Richmond.
- Pierre-Daniel Sarte & Mark Watson & Andrew Foerster, 2008. "Aggregate Shocks and the Variability of Industrial Production," 2008 Meeting Papers 224, Society for Economic Dynamics.
- Trzcinka, Charles A, 1986. "On the Number of Factors in the Arbitrage Pricing Model," Journal of Finance, American Finance Association, vol. 41(2), pages 347-368, June.
- Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
- Huberman, Gur & Kandel, Shmuel & Stambaugh, Robert F, 1987. "Mimicking Portfolios and Exact Arbitrage Pricing," Journal of Finance, American Finance Association, vol. 42(1), pages 1-9, March.
- Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2006.
"VARs, common factors and the empirical validation of equilibrium business cycle models,"
Journal of Econometrics, Elsevier, vol. 132(1), pages 257-279, May.
- Reichlin, Lucrezia & Sala, Luca & Giannone, Domenico, 2002. "VARs, Common Factors and the Empirical Validation of Equilibrium Business Cycle Models," CEPR Discussion Papers 3701, C.E.P.R. Discussion Papers.
- Domenica Giannone & Lucrezia Reichlin & Luca Sala, 2004. "VARs, Common Factors and the Empirical Validation of Equilibrium Business Cycle Models," Working Papers 258, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Domenico Giannone & Lucrezia Reichlin & Luca Sala, 2006. "VARs, common factors and the empirical validation of equilibrium business cycle models," ULB Institutional Repository 2013/10127, ULB -- Universite Libre de Bruxelles.
- Seung C. Ahn & Alex R. Horenstein, 2013. "Eigenvalue Ratio Test for the Number of Factors," Econometrica, Econometric Society, vol. 81(3), pages 1203-1227, May.
- Alexei Onatski, 2009. "Testing Hypotheses About the Number of Factors in Large Factor Models," Econometrica, Econometric Society, vol. 77(5), pages 1447-1479, September.
- Stock, James H. & Watson, Mark W., 2006. "Forecasting with Many Predictors," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 10, pages 515-554, Elsevier.
- Stephen A. Ross, 2013.
"The Arbitrage Theory of Capital Asset Pricing,"
World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30,
World Scientific Publishing Co. Pte. Ltd..
- Ross, Stephen A., 1976. "The arbitrage theory of capital asset pricing," Journal of Economic Theory, Elsevier, vol. 13(3), pages 341-360, December.
- Stephen A. Ross, "undated". "The Arbitrage Theory of Capital Asset Pricing," Rodney L. White Center for Financial Research Working Papers 02-73, Wharton School Rodney L. White Center for Financial Research.
- Stephen A. Ross, "undated". "The Arbitrage Theory of Capital Asset Pricing," Rodney L. White Center for Financial Research Working Papers 2-73, Wharton School Rodney L. White Center for Financial Research.
- Xavier Gabaix, 2011.
"The Granular Origins of Aggregate Fluctuations,"
Econometrica, Econometric Society, vol. 79(3), pages 733-772, May.
- Xavier Gabaix, 2005. "The Granular Origins of Aggregate Fluctuations," 2005 Meeting Papers 470, Society for Economic Dynamics.
- Xavier Gabaix, 2009. "The Granular Origins of Aggregate Fluctuations," NBER Working Papers 15286, National Bureau of Economic Research, Inc.
- Kapetanios, George, 2010.
"A Testing Procedure for Determining the Number of Factors in Approximate Factor Models With Large Datasets,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 28(3), pages 397-409.
- George Kapetanios, 2005. "A Testing Procedure for Determining the Number of Factors in Approximate Factor Models with Large Datasets," Working Papers 551, Queen Mary University of London, School of Economics and Finance.
- Choi, In, 2012.
"Efficient Estimation Of Factor Models,"
Econometric Theory, Cambridge University Press, vol. 28(2), pages 274-308, April.
- In Choi, 2007. "Efficient Estimation of Factor Models," Working Papers 0701, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy), revised Dec 2010.
- Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011.
"Weak and strong cross‐section dependence and estimation of large panels,"
Econometrics Journal, Royal Economic Society, vol. 14(1), pages 45-90, February.
- Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2011. "Weak and strong cross‐section dependence and estimation of large panels," Econometrics Journal, Royal Economic Society, vol. 14, pages 45-90, February.
- Chudik, Alexander & Pesaran, Hashem & Tosetti, Elisa, 2009. "Weak and strong cross section dependence and estimation of large panels," Working Paper Series 1100, European Central Bank.
- Chudik, A. & Pesaran, M.H. & Tosetti, E., 2009. "Weak and Strong Cross Section Dependence and Estimation of Large Panels," Cambridge Working Papers in Economics 0924, Faculty of Economics, University of Cambridge.
- Alexander Chudik & M. Hashem Pesaran & Elisa Tosetti, 2009. "Weak and Strong Cross Section Dependence and Estimation of Large Panels," CESifo Working Paper Series 2689, CESifo.
- Donald W. K. Andrews & Xu Cheng, 2012.
"Estimation and Inference With Weak, Semi‐Strong, and Strong Identification,"
Econometrica, Econometric Society, vol. 80(5), pages 2153-2211, September.
- Donald W.K. Andrews & Xu Cheng, 2010. "Estimation and Inference with Weak, Semi-strong, and Strong Identification," Cowles Foundation Discussion Papers 1773, Cowles Foundation for Research in Economics, Yale University.
- Donald W.K. Andrews & Xu Cheng, 2010. "Estimation and Inference with Weak, Semi-strong, and Strong Identification," Cowles Foundation Discussion Papers 1773R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2011.
- Antoine, Bertille & Renault, Eric, 2012.
"Efficient minimum distance estimation with multiple rates of convergence,"
Journal of Econometrics, Elsevier, vol. 170(2), pages 350-367.
- Bertille Antoine & Eric Renault, 2012. "Efficient Minimum Distance Estimation with Multiple Rates of Convergence," Discussion Papers dp12-03, Department of Economics, Simon Fraser University.
- Green, Richard C & Hollifield, Burton, 1992.
"When Will Mean-Variance Efficient Portfolios Be Well Diversified?,"
Journal of Finance, American Finance Association, vol. 47(5), pages 1785-1809, December.
- Green, R.C. & Hollifield, B., 1990. "When Will Mean-Variance Efficient Portfolios Be Well Diversified?," GSIA Working Papers 1990-12, Carnegie Mellon University, Tepper School of Business.
- Chamberlain, Gary & Rothschild, Michael, 1983.
"Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets,"
Econometrica, Econometric Society, vol. 51(5), pages 1281-1304, September.
- Gary Chamberlain & Michael Rothschild, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," NBER Working Papers 0996, National Bureau of Economic Research, Inc.
- Chamberlain, Gary & Rothschild, Michael, 1982. "Arbitrage, Factor Structure, and Mean-Variance Analysis on Large Asset Markets," Scholarly Articles 3230355, Harvard University Department of Economics.
- De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008.
"Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?,"
Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
- Reichlin, Lucrezia & Giannone, Domenico & De Mol, Christine, 2006. "Forecasting Using a Large Number of Predictors: Is Bayesian Regression a Valid Alternative to Principal Components?," CEPR Discussion Papers 5829, C.E.P.R. Discussion Papers.
- De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank.
- Giannone, Domenico & Reichlin, Lucrezia & De Mol, Christine, 2006. "Forecasting using a large number of predictors: Is Bayesian regression a valid alternative to principal components?," Working Paper Series 700, European Central Bank.
- Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000.
"The Generalized Dynamic-Factor Model: Identification And Estimation,"
The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
- Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
- Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
- Alexei Onatski, 2010. "Determining the Number of Factors from Empirical Distribution of Eigenvalues," The Review of Economics and Statistics, MIT Press, vol. 92(4), pages 1004-1016, November.
- Chamberlain, Gary, 1983. "Funds, Factors, and Diversification in Arbitrage Pricing Models," Econometrica, Econometric Society, vol. 51(5), pages 1305-1323, September.
- Dias Francisco & Pinheiro Maximiano & Rua António, 2013. "Determining the number of global and country-specific factors in the euro area," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(5), pages 573-617, December.
- Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
- Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
- Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2010. "Improved penalization for determining the number of factors in approximate factor models," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1806-1813, December.
- Carvalho, Carlos M. & Chang, Jeffrey & Lucas, Joseph E. & Nevins, Joseph R. & Wang, Quanli & West, Mike, 2008. "High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1438-1456.
- George Kapetanios, 2004. "A New Method for Determining the Number of Factors in Factor Models with Large Datasets," Working Papers 525, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios, 2004.
"A New Method for Determining the Number of Factors in Factor Models with Large Datasets,"
Working Papers
525, Queen Mary University of London, School of Economics and Finance.
- George Kapetanios, 2004. "A New Method for Determining the Number of Factors in Factor Models with Large Datasets," Working Papers 525, Queen Mary University of London, School of Economics and Finance.
- Connor, Gregory & Korajczyk, Robert A, 1993. "A Test for the Number of Factors in an Approximate Factor Model," Journal of Finance, American Finance Association, vol. 48(4), pages 1263-1291, September.
- Boivin, Jean & Ng, Serena, 2006.
"Are more data always better for factor analysis?,"
Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
- Jean Boivin & Serena Ng, 2003. "Are More Data Always Better for Factor Analysis?," NBER Working Papers 9829, National Bureau of Economic Research, Inc.
- Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 91(1), pages 39-69, February.
- Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
- Tibor F. Liska, 2007. "The Liska model," Society and Economy, Akadémiai Kiadó, Hungary, vol. 29(3), pages 363-381, December.
- Michael Horvath, 1998. "Cyclicality and Sectoral Linkages: Aggregate Fluctuations from Independent Sectoral Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(4), pages 781-808, October.
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Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 587-613, August.
- Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2020. "Measurement of Factor Strength: Theory and Practice," Monash Econometrics and Business Statistics Working Papers 7/20, Monash University, Department of Econometrics and Business Statistics.
- Natalia Bailey & George Kapetanios & M. Hashem Pesaran, 2020. "Measurement of Factor Strenght: Theory and Practice," CESifo Working Paper Series 8146, CESifo.
- Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053r, Institute of Social and Economic Research, Osaka University, revised Mar 2020.
- Yoshimasa Uematsu & Takashi Yamagata, 2019.
"Estimation of Weak Factor Models,"
DSSR Discussion Papers
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- Yoshimasa Uematsu & Takashi Yamagata, 2019. "Estimation of Weak Factor Models," ISER Discussion Paper 1053, Institute of Social and Economic Research, Osaka University.
- Simon Freyaldenhoven, 2020. "Identification Through Sparsity in Factor Models," Working Papers 20-25, Federal Reserve Bank of Philadelphia.
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More about this item
Keywords
high-dimensional data; factor models; weak factors; local factors; sparsity;All these keywords.
JEL classification:
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ETS-2019-05-06 (Econometric Time Series)
- NEP-ORE-2019-05-06 (Operations Research)
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