The economic value of cross-predictability: A performance-based measure
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- Bryan T. Kelly & Semyon Malamud & Kangying Zhou, 2022. "The Virtue of Complexity in Return Prediction," NBER Working Papers 30217, National Bureau of Economic Research, Inc.
- Kelly, Bryan T. & Pruitt, Seth & Su, Yinan, 2019.
"Characteristics are covariances: A unified model of risk and return,"
Journal of Financial Economics, Elsevier, vol. 134(3), pages 501-524.
- Bryan Kelly & Seth Pruitt & Yinan Su, 2018. "Characteristics Are Covariances: A Unified Model of Risk and Return," NBER Working Papers 24540, National Bureau of Economic Research, Inc.
- Stefano Giglio & Bryan Kelly & Dacheng Xiu, 2022. "Factor Models, Machine Learning, and Asset Pricing," Annual Review of Financial Economics, Annual Reviews, vol. 14(1), pages 337-368, November.
- Michael Gofman & Gill Segal & Youchang Wu & Stijn Van Nieuwerburgh, 2020. "Production Networks and Stock Returns: The Role of Vertical Creative Destruction," The Review of Financial Studies, Society for Financial Studies, vol. 33(12), pages 5856-5905.
- Lee, Charles M.C. & Sun, Stephen Teng & Wang, Rongfei & Zhang, Ran, 2019.
"Technological links and predictable returns,"
Journal of Financial Economics, Elsevier, vol. 132(3), pages 76-96.
- Lee, Charles M. C. Lee & Sun, Stephen Teng & Wang, Rongfei & Zhang, Ran, 2017. "Technological Links and Predictable Returns," Research Papers repec:ecl:stabus:3605, Stanford University, Graduate School of Business.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Andrew KarolyiEditor, 2020.
"Dissecting Characteristics Nonparametrically,"
Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Andrew KarolyiEditor, 2020. "Dissecting Characteristics Nonparametrically," Review of Finance, European Finance Association, vol. 33(5), pages 2326-2377.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," NBER Working Papers 23227, National Bureau of Economic Research, Inc.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 6391, CESifo.
- Lo, Andrew W & MacKinlay, A Craig, 1990.
"When Are Contrarian Profits Due to Stock Market Overreaction?,"
The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
- Lo, Andrew W. (Andrew Wen-Chuan) & MacKinlay, Archie Craig, 1955-., 1989. "When are contrarian profits due to stock market overreaction?," Working papers 3008-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Andrew W. Lo & A. Craig MacKinlay, 1989. "When are Contrarian Profits Due to Stock Market Overreaction?," NBER Working Papers 2977, National Bureau of Economic Research, Inc.
- Christopher A Parsons & Riccardo Sabbatucci & Sheridan Titman, 2020. "Geographic Lead-Lag Effects," The Review of Financial Studies, Society for Financial Studies, vol. 33(10), pages 4721-4770.
- Bryan Kelly & Seth Pruitt, 2013. "Market Expectations in the Cross-Section of Present Values," Journal of Finance, American Finance Association, vol. 68(5), pages 1721-1756, October.
- Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020.
"Shrinking the cross-section,"
Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
- Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2017. "Shrinking the Cross Section," NBER Working Papers 24070, National Bureau of Economic Research, Inc.
- Nagel, Stefan & Santosh, Shrihari & Kozak, Serhiy, 2017. "Shrinking the Cross Section," CEPR Discussion Papers 12463, C.E.P.R. Discussion Papers.
- Schlag, Christian & Zeng, Kailin, 2019. "Horizontal industry relationships and return predictability," SAFE Working Paper Series 256, Leibniz Institute for Financial Research SAFE.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020.
"Empirical Asset Pricing via Machine Learning,"
The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
- Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
- Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
- Kewei Hou & Chen Xue & Lu Zhang, 2020. "Replicating Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2019-2133.
- Lauren Cohen & Andrea Frazzini, 2008. "Economic Links and Predictable Returns," Journal of Finance, American Finance Association, vol. 63(4), pages 1977-2011, August.
- Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006.
"The CrossâSection of Volatility and Expected Returns,"
Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
- Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2004. "The Cross-Section of Volatility and Expected Returns," NBER Working Papers 10852, National Bureau of Economic Research, Inc.
- David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
- Huang, Shiyang & Lee, Charles M.C. & Song, Yang & Xiang, Hong, 2022. "A frog in every pan: Information discreteness and the lead-lag returns puzzle," Journal of Financial Economics, Elsevier, vol. 145(2), pages 83-102.
- John Y. Campbell & Samuel B. Thompson, 2008.
"Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?,"
The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
- Campbell, John & Thompson, Samuel P., 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Scholarly Articles 2622619, Harvard University Department of Economics.
- Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
- Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
- Kewei Hou, 2007. "Industry Information Diffusion and the Lead-lag Effect in Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 20(4), pages 1113-1138.
- Andrew Detzel & Jack Strauss, 2018. "Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios [Illiquidity and stock returns: cross-section and time-series effects]," Review of Finance, European Finance Association, vol. 22(5), pages 1949-1973.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
- Martin Lettau & Markus Pelger & Stijn Van Nieuwerburgh, 2020.
"Factors That Fit the Time Series and Cross-Section of Stock Returns,"
The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2274-2325.
- Lettau, Martin & Pelger, Markus, 2018. "Factors that Fit the Time Series and Cross-Section of Stock Returns," CEPR Discussion Papers 13049, C.E.P.R. Discussion Papers.
- Martin Lettau & Markus Pelger, 2018. "Factors that Fit the Time Series and Cross-Section of Stock Returns," NBER Working Papers 24858, National Bureau of Economic Research, Inc.
- Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
- Martin Lettau & Markus Pelger, 2020. "Factors That Fit the Time Series and Cross-Section of Stock Returns," Review of Finance, European Finance Association, vol. 33(5), pages 2274-2325.
- Ali, Usman & Hirshleifer, David, 2020.
"Shared analyst coverage: Unifying momentum spillover effects,"
Journal of Financial Economics, Elsevier, vol. 136(3), pages 649-675.
- Usman Ali & David Hirshleifer, 2018. "Shared Analyst Coverage: Unifying Momentum Spillover Effects," NBER Working Papers 25201, National Bureau of Economic Research, Inc.
- Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
- Badrinath, S G & Kale, Jayant R & Noe, Thomas H, 1995. "Of Shepherds, Sheep, and the Cross-autocorrelations in Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 8(2), pages 401-430.
- Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2018. "Interpreting Factor Models," Journal of Finance, American Finance Association, vol. 73(3), pages 1183-1223, June.
- Brennan, Michael J & Jegadeesh, Narasimhan & Swaminathan, Bhaskaran, 1993. "Investment Analysis and the Adjustment of Stock Prices to Common Information," The Review of Financial Studies, Society for Financial Studies, vol. 6(4), pages 799-824.
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More about this item
Keywords
Empirical Asset Pricing; Portfolio Choice; Expected Returns; Cross-Predictability;All these keywords.
JEL classification:
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
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