Análisis de procesos explosivos en el precio de los activos financieros: evidencia alrededor del mundo
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- Bai, Jushan & Ng, Serena, 2008. "Forecasting economic time series using targeted predictors," Journal of Econometrics, Elsevier, vol. 146(2), pages 304-317, October.
- Anderson, Keith & Brooks, Chris, 2014.
"Speculative bubbles and the cross-sectional variation in stock returns,"
International Review of Financial Analysis, Elsevier, vol. 35(C), pages 20-31.
- Chris Brooks & Keith Anderson, 2012. "Speculative Bubbles and the Cross-Sectional Variation in Stock Returns," ICMA Centre Discussion Papers in Finance icma-dp2013-01, Henley Business School, University of Reading, revised Nov 2013.
- Ricardo J. Caballero & Emmanuel Farhi & Pierre-Olivier Gourinchas, 2008.
"An Equilibrium Model of "Global Imbalances" and Low Interest Rates,"
American Economic Review, American Economic Association, vol. 98(1), pages 358-393, March.
- Caballero, Ricardo J & Farhi, Emmanuel & Gourinchas, Pierre-Olivier, 2006. "An Equilibrium Model of "Global Imbalances" and Low Interest Rates," Department of Economics, Working Paper Series qt7xc0g8mm, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- Caballero, Ricardo J & Farhi, Emmanuel & Gourinchas, Pierre-Olivier, 2006. "An Equilibrium Model of "Global Imbalances" and Low Interest Rates," Center for International and Development Economics Research, Working Paper Series qt7xc0g8mm, Center for International and Development Economics Research, Institute for Business and Economic Research, UC Berkeley.
- Caballero, Ricardo & Gourinchas, Pierre-Olivier & Farhi, Emmanuel, 2006. "An Equilibrium Model of 'Global Imbalances' and Low Interest Rates," CEPR Discussion Papers 5573, Centre for Economic Policy Research.
- Ricardo J. Caballero & Emmanuel Farhi & Pierre-Olivier Gourinchas, 2006. "An Equilibrium Model of Global Imbalances and Low Interest Rates," 2006 Meeting Papers 894, Society for Economic Dynamics.
- Ricardo J Caballero & Emmanuel Farhi & Pierre-Olivier Gourinchas, 2006. "An equilibrum model of "global imbalances" and low interest rates," BIS Working Papers 222, Bank for International Settlements.
- Ricardo J. Caballero & Emmanuel Farhi & Pierre-Olivier Gourinchas, 2006. "An Equilibrium Model of "Global Imbalances" and Low Interest Rates," NBER Working Papers 11996, National Bureau of Economic Research, Inc.
- Caballero, Ricardo J. & Farhi, Emmanuel & Gourinchas, Pierre-Olivier, 2008. "An Equilibrium Model of "Global Imbalances" and Low Interest Rates," Scholarly Articles 3229094, Harvard University Department of Economics.
- Jushan Bai & Serena Ng, 2002.
"Determining the Number of Factors in Approximate Factor Models,"
Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
- Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Boston College Working Papers in Economics 440, Boston College Department of Economics.
- Tom Doan, 2025. "BAING: RATS procedure to estimate factors in a factor model using Bai-Ng formulas," Statistical Software Components RTS00012, Boston College Department of Economics.
- George A. Akerlof, 2009. "How Human Psychology Drives the Economy and Why It Matters," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(5), pages 1175-1175.
- Allen, Franklin & Gale, Douglas, 2000. "Bubbles and Crises," Economic Journal, Royal Economic Society, vol. 110(460), pages 236-255, January.
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Keywords
; ; ; ; ;JEL classification:
- G01 - Financial Economics - - General - - - Financial Crises
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
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