Out of Sample Predictability in Predictive Regressions with Many Predictor Candidates
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- Gonzalo, Jesús & Pitarakis, Jean-Yves, 2024. "Out-of-sample predictability in predictive regressions with many predictor candidates," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1166-1178.
- Pitarakis, Jean-Yves, 2020. "Out of sample predictability in predictive regressions with many predictor candidates," UC3M Working papers. Economics 31554, Universidad Carlos III de Madrid. Departamento de EconomÃa.
References listed on IDEAS
- Ivo Welch & Amit Goyal, 2008.
"A Comprehensive Look at The Empirical Performance of Equity Premium Prediction,"
The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
- Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
- Amit Goyal & Ivo Welch & Athanasse Zafirov, 2021. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction II," Swiss Finance Institute Research Paper Series 21-85, Swiss Finance Institute.
- Amit Goval & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," NBER Working Papers 10483, National Bureau of Economic Research, Inc.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021.
"Economic Predictions With Big Data: The Illusion of Sparsity,"
Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic predictions with big data: the illusion of sparsity," Staff Reports 847, Federal Reserve Bank of New York.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
- Jiahan Li & Ilias Tsiakas & Wei Wang, 2015.
"Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?,"
Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 293-341.
- Jiahan Li & Ilias Tsiakas & Wei Wang, 2014. "Predicting Exchange Rates Out of Sample: Can Economic Fundamentals Beat the Random Walk?," Working Paper series 05_14, Rimini Centre for Economic Analysis.
- West, Kenneth D, 1996.
"Asymptotic Inference about Predictive Ability,"
Econometrica, Econometric Society, vol. 64(5), pages 1067-1084, September.
- West, K.D., 1994. "Asymptotic Inference About Predictive Ability," Working papers 9417, Wisconsin Madison - Social Systems.
- Kenneth D. West, 1994. "Asymptotic Inference About Predictive Ability," Macroeconomics 9410002, University Library of Munich, Germany.
- Michael W. McCracken & Serena Ng, 2016.
"FRED-MD: A Monthly Database for Macroeconomic Research,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 574-589, October.
- Michael W. McCracken & Serena Ng, 2015. "FRED-MD: A Monthly Database for Macroeconomic Research," Working Papers 2015-12, Federal Reserve Bank of St. Louis.
- Magdalinos, Tassos & Phillips, Peter C.B., 2009. "Limit Theory For Cointegrated Systems With Moderately Integrated And Moderately Explosive Regressors," Econometric Theory, Cambridge University Press, vol. 25(2), pages 482-526, April.
- Berenguer-Rico, Vanessa & Nielsen, Bent, 2020. "Cumulated Sum Of Squares Statistics For Nonlinear And Nonstationary Regressions," Econometric Theory, Cambridge University Press, vol. 36(1), pages 1-47, February.
- West, Kenneth D., 2006. "Forecast Evaluation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 3, pages 99-134, Elsevier.
- Deng, Ai & Perron, Pierre, 2008.
"The Limit Distribution Of The Cusum Of Squares Test Under General Mixing Conditions,"
Econometric Theory, Cambridge University Press, vol. 24(3), pages 809-822, June.
- Ai Deng & Pierre Perron, 2006. "The Limit Distribution of the CUSUM of Squares Test Under General Mixing Conditions," Boston University - Department of Economics - Working Papers Series wp2006-004, Boston University - Department of Economics.
- 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.
- Yu‐Chin Hsu & Xiaoxia Shi, 2017. "Model‐selection tests for conditional moment restriction models," Econometrics Journal, Royal Economic Society, vol. 20(1), pages 52-85, February.
- Clark, Todd E. & West, Kenneth D., 2007.
"Approximately normal tests for equal predictive accuracy in nested models,"
Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
- Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper RWP 05-05, Federal Reserve Bank of Kansas City.
- Kenneth D. West & Todd Clark, 2006. "Approximately Normal Tests for Equal Predictive Accuracy in Nested Models," NBER Technical Working Papers 0326, National Bureau of Economic Research, Inc.
- Clark, Todd & McCracken, Michael, 2013.
"Advances in Forecast Evaluation,"
Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1107-1201,
Elsevier.
- Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers 2011-025, Federal Reserve Bank of St. Louis.
- Todd E. Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Papers (Old Series) 1120, Federal Reserve Bank of Cleveland.
- Susanne M. Schennach & Daniel Wilhelm, 2017.
"A Simple Parametric Model Selection Test,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1663-1674, October.
- Susanne M. Schennach & Daniel Wilhelm, 2014. "A simple parametric model selection test," CeMMAP working papers CWP10/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Susanne M. Schennach & Daniel Wilhelm, 2016. "A simple parametric model selection test," CeMMAP working papers CWP30/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Susanne M. Schennach & Daniel Wilhelm, 2016. "A simple parametric model selection test," CeMMAP working papers 30/16, Institute for Fiscal Studies.
- Susanne M. Schennach & Daniel Wilhelm, 2014. "A simple parametric model selection test," CeMMAP working papers 10/14, Institute for Fiscal Studies.
- Xiaoxia Shi, 2015. "A nondegenerate Vuong test," Quantitative Economics, Econometric Society, vol. 6(1), pages 85-121, March.
- Pitarakis, Jean-Yves, 2019. "Predictive Regressions," UC3M Working papers. Economics 28554, Universidad Carlos III de Madrid. Departamento de EconomÃa.
- Phillips, Peter C.B. & Magdalinos, Tassos, 2007.
"Limit theory for moderate deviations from a unit root,"
Journal of Econometrics, Elsevier, vol. 136(1), pages 115-130, January.
- Peter C.B. Phillips & Tassos Magdalinos, 2004. "Limit Theory for Moderate Deviations from a Unit Root," Cowles Foundation Discussion Papers 1471, Cowles Foundation for Research in Economics, Yale University.
- Liu, Weiling & Moench, Emanuel, 2016.
"What predicts US recessions?,"
International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
- Weiling Liu & Emanuel Moench, 2014. "What predicts U.S. recessions?," Staff Reports 691, Federal Reserve Bank of New York.
- Yu-chin Chen & Kwok Ping Tsang, 2013.
"What Does the Yield Curve Tell Us about Exchange Rate Predictability?,"
The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 185-205, March.
- Yu-chin Chen & Kwok Ping Tsang, 2009. "What Does the Yield Curve Tell Us About Exchange Rate Predictability?," Working Papers UWEC-2009-04, University of Washington, Department of Economics.
- Yu-chin Chen & Kwok Ping Tsang, 2010. "What Does the Yield Curve Tell Us about Exchange Rate Predictability?," Working Papers 292010, Hong Kong Institute for Monetary Research.
- McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
- Molodtsova, Tanya & Papell, David H., 2009. "Out-of-sample exchange rate predictability with Taylor rule fundamentals," Journal of International Economics, Elsevier, vol. 77(2), pages 167-180, April.
- Jianqing Fan & Yuan Liao & Jiawei Yao, 2015. "Power Enhancement in High‐Dimensional Cross‐Sectional Tests," Econometrica, Econometric Society, vol. 83(4), pages 1497-1541, July.
- Ian W. McKeague & Min Qian, 2015. "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1422-1433, December.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-333, March.
- Ghysels, Eric & Hill, Jonathan B. & Motegi, Kaiji, 2020. "Testing a large set of zero restrictions in regression models, with an application to mixed frequency Granger causality," Journal of Econometrics, Elsevier, vol. 218(2), pages 633-654.
- Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," The Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-428.
- Geoffrey Decrouez & Peter Hall, 2014. "Split sample methods for constructing confidence intervals for binomial and Poisson parameters," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(5), pages 949-975, November.
- Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
- Jean-Yves Pitarakis, 2020. "A Novel Approach to Predictive Accuracy Testing in Nested Environments," Papers 2008.08387, arXiv.org, revised Oct 2023.
- Pesaran, M Hashem & Timmermann, Allan, 1995. "Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-1228, September.
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
- Jianqing Fan & Jinchi Lv, 2008. "Sure independence screening for ultrahigh dimensional feature space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 849-911, November.
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Cited by:
- Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
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More about this item
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ETS-2023-03-06 (Econometric Time Series)
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