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Serhiy Kozak

Citations

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RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2017. "Shrinking the Cross Section," NBER Working Papers 24070, National Bureau of Economic Research, Inc.

    Mentioned in:

    1. > Econometrics > Big Data

Working papers

  1. Serhiy Kozak & Stefan Nagel, 2023. "When Do Cross-Sectional Asset Pricing Factors Span the Stochastic Discount Factor?," NBER Working Papers 31275, National Bureau of Economic Research, Inc.

    Cited by:

    1. Dimos Andronoudis & Massimo Guidolin & Manuela Pedio, 2025. "How Smart is the Real Estate Smart Beta? Evidence from Optimal Style Factor Strategies for REITs," BAFFI CAREFIN Working Papers 25241, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    2. Useong Shin, 2026. "Overshooting the Coordinate: Where Factor Corrections Land on Characteristic Axes," Papers 2607.05091, arXiv.org, revised Jul 2026.
    3. Matthias Bank & Franz Insam & Jochen Lawrenz, 2026. "Taste for characteristics or risk factor aversion? Evidence from institutional demand," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 40(1), pages 27-96, March.
    4. Bryan Kelly & Boris Kuznetsov & Semyon Malamud & Yuan Zhang, 2024. "Large and Deep Factor Models," Papers 2402.06635, arXiv.org, revised Jun 2026.

  2. Stefano Giglio & Bryan T. Kelly & Serhiy Kozak, 2023. "Equity Term Structures without Dividend Strips Data," NBER Working Papers 31119, National Bureau of Economic Research, Inc.

    Cited by:

    1. Jiang, Fuwei & Li, Kunpeng & Ning, Wei & Xue, Hao, 2026. "Scaled factor portfolio," Pacific-Basin Finance Journal, Elsevier, vol. 98(C).
    2. Martijn Boons & Anthony M. Diercks & Petra Sinagl & Andrea Tamoni, 2026. "The Response of Equity Yields to a Long-Run Shock," Finance and Economics Discussion Series 2026-044, Board of Governors of the Federal Reserve System (U.S.).
    3. Prat, Georges & Le Bris, David, 2024. "Term structure of equity risk premia in rough terrain: 150 years of the French stock market," The Quarterly Review of Economics and Finance, Elsevier, vol. 97(C).
    4. Galindo Gil, Hamilton, 2025. "The role of external habits and preference heterogeneity in the equity term structure," Journal of Economic Dynamics and Control, Elsevier, vol. 178(C).
    5. Zeng, Ming & Zhao, Guihai, 2026. "Expectation-driven term structure of equity and bond yields," Journal of Monetary Economics, Elsevier, vol. 157(C).
    6. Galindo Gil, Hamilton, 2026. "Risk aversion heterogeneity and the equity term structure," International Review of Economics & Finance, Elsevier, vol. 107(C).
    7. de Vries, Martijn A., 2026. "Time-varying risk aversion and the equity term structure," Journal of Behavioral and Experimental Finance, Elsevier, vol. 49(C).
    8. Li, Ye & Wang, Chen, 2025. "The Information Cliff," SocArXiv bf8cx_v1, Center for Open Science.
    9. Michael Hasler & Mariana Khapko & Roberto Marfè, 2026. "Value Premium and Equity Term Structures of Value and Growth Firms," Management Science, INFORMS, vol. 72(7), pages 5916-5942, July.
    10. Li, Kai & Xu, Chenjie, 2024. "Intermediary-based equity term structure," Journal of Financial Economics, Elsevier, vol. 157(C).
    11. Chibane, Messaoud & Poncet, Patrice, 2025. "Housing rare disaster events and asset prices," Economic Modelling, Elsevier, vol. 147(C).

  3. Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2020. "Factor Timing," NBER Working Papers 26708, National Bureau of Economic Research, Inc.

    Cited by:

    1. Cho, Thummim, 2020. "Turning alphas into betas: arbitrage and endogenous risk," LSE Research Online Documents on Economics 102085, London School of Economics and Political Science, LSE Library.
    2. Chernov, Mikhail & Lochstoer, Lars & Lundeby, Stig, 2018. "Conditional dynamics and the multi-horizon risk-return trade-off," CEPR Discussion Papers 13365, Centre for Economic Policy Research.
    3. de Oliveira Souza, Thiago, 2019. "Macro-finance and factor timing: Time-varying factor risk and price of risk premiums," Discussion Papers on Economics 7/2019, University of Southern Denmark, Department of Economics.
    4. Cho, Thummim, 2020. "Turning alphas into betas: Arbitrage and endogenous risk," Journal of Financial Economics, Elsevier, vol. 137(2), pages 550-570.

  4. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2017. "Shrinking the Cross Section," CEPR Discussion Papers 12463, Centre for Economic Policy Research.

    Cited by:

    1. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    2. Bandi, Federico M. & Chaudhuri, Shomesh E. & Lo, Andrew W. & Tamoni, Andrea, 2021. "Spectral factor models," Journal of Financial Economics, Elsevier, vol. 142(1), pages 214-238.
    3. Cui, Mengqi & Li, Daye, 2024. "A four-factor model based on factor momentum," Pacific-Basin Finance Journal, Elsevier, vol. 87(C).
    4. Carl Remlinger & Bri`ere Marie & Alasseur Cl'emence & Joseph Mikael, 2021. "Expert Aggregation for Financial Forecasting," Papers 2111.15365, arXiv.org, revised Jul 2023.
    5. Bryzgalova, Svetlana & Huang, Jiantao & Julliard, Christian, 2023. "Bayesian solutions for the factor zoo: we just ran two quadrillion models," LSE Research Online Documents on Economics 126151, London School of Economics and Political Science, LSE Library.
    6. Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023. "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, vol. 237(2).
    7. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2023. "Machine learning goes global: Cross-sectional return predictability in international stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 155(C).
    8. Molero-González, L. & Trinidad-Segovia, J.E. & Sánchez-Granero, M.A. & García-Medina, A., 2023. "Market Beta is not dead: An approach from Random Matrix Theory," Finance Research Letters, Elsevier, vol. 55(PA).
    9. Kozak, Serhiy & Santosh, Shrihari, 2020. "Why do discount rates vary?," Journal of Financial Economics, Elsevier, vol. 137(3), pages 740-751.
    10. Liu, Weiyi & Zhang, Huachen & Wan, Die, 2026. "Overlapping factor momentum," Finance Research Letters, Elsevier, vol. 90(C).
    11. Viet Anh Nguyen & Fan Zhang & Shanshan Wang & José Blanchet & Erick Delage & Yinyu Ye, 2025. "Robustifying Conditional Portfolio Decisions via Optimal Transport," Operations Research, INFORMS, vol. 73(5), pages 2801-2829, September.
    12. Cong, Lin William & Feng, Guanhao & He, Jingyu & He, Xin, 2025. "Growing the efficient frontier on panel trees," Journal of Financial Economics, Elsevier, vol. 167(C).
    13. Maysam Khodayari Gharanchaei & Prabhu Prasad Panda & Xilin Chen, 2024. "Quantitative Investment Diversification Strategies via Various Risk Models," Papers 2407.01550, arXiv.org.
    14. Chai, Bailin & Jiang, Fuwei & Lin, Yihao & You, Tian, 2025. "Predicting bond risk premiums with machine learning: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 93(C).
    15. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    16. Anna Brzozowska & Dagmara Bubel, 2020. "Estimation of the Imperative of Rural Area Development on Panel Data in the Process of Managing Agricultural Holdings in Poland," Agriculture, MDPI, vol. 10(7), pages 1-20, July.
    17. Zhang, Ailian & Pan, Mengmeng & Zhang, Xuan, 2025. "The pricing ability of factor model based on machine learning: Evidence from high-frequency data in China," International Review of Economics & Finance, Elsevier, vol. 101(C).
    18. Neely, Christopher J., 2022. "How persistent are unconventional monetary policy effects?," Journal of International Money and Finance, Elsevier, vol. 126(C).
    19. Constantinos Kardaras & Hyeng Keun Koo & Johannes Ruf, 2022. "Estimation of growth in fund models," Papers 2208.02573, arXiv.org.
    20. Almeida, Caio & Freire, Gustavo, 2022. "Pricing of index options in incomplete markets," Journal of Financial Economics, Elsevier, vol. 144(1), pages 174-205.
    21. Pedro M. Mirete-Ferrer & Alberto Garcia-Garcia & Juan Samuel Baixauli-Soler & Maria A. Prats, 2022. "A Review on Machine Learning for Asset Management," Risks, MDPI, vol. 10(4), pages 1-46, April.
    22. Siddhartha Chib & Lingxiao Zhao & Guofu Zhou, 2024. "Winners from Winners: A Tale of Risk Factors," Management Science, INFORMS, vol. 70(1), pages 396-414, January.
    23. Sun, Chuanping, 2024. "Factor correlation and the cross section of asset returns: A correlation-robust machine learning approach," Journal of Empirical Finance, Elsevier, vol. 77(C).
    24. Wang, Jianqiu & Wang, Zhuo & Wu, Ke, 2025. "Forecasting stock market return with anomalies: Evidence from China," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1278-1295.
    25. Malakhov, Alexey & Riley, Timothy B. & Yan, Qing, 2024. "Do hedge funds bet against beta?," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1507-1525.
    26. Paul Felix Reiter, 2023. "Measuring the Relevance of Factors on Cross-Sectional Returns with Decision Trees," Applied Economics and Finance, Redfame publishing, vol. 10(4), pages 14-25, November.
    27. Ai He & Dashan Huang & Jiaen Li & Guofu Zhou, 2023. "Shrinking Factor Dimension: A Reduced-Rank Approach," Management Science, INFORMS, vol. 69(9), pages 5501-5522, September.
    28. Croux, Christophe & Jagtiani, Julapa & Korivi, Tarunsai & Vulanovic, Milos, 2020. "Important factors determining Fintech loan default: Evidence from a lendingclub consumer platform," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 270-296.
    29. Simon Fritzsch & Felix Irresberger & Gregor Weiß, 2026. "Predicting option prices from their price history via machine learning," Review of Derivatives Research, Springer, vol. 29(1), pages 1-38, December.
    30. Manresa, Elena & Penaranda, Francisco & Sentana, Enrique, 2017. "Empirical Evaluation of Overspecified Asset Pricing Models," CEPR Discussion Papers 12085, Centre for Economic Policy Research.
    31. Cederburg, Scott & O’Doherty, Michael S. & Wang, Feifei & Yan, Xuemin (Sterling), 2020. "On the performance of volatility-managed portfolios," Journal of Financial Economics, Elsevier, vol. 138(1), pages 95-117.
    32. Cong Wang, 2024. "Stock return prediction with multiple measures using neural network models," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-34, December.
    33. Hongyu Lin & Yulin Chen & Yuanrong Wang & Antonio Briola & Tomaso Aste, 2026. "Dependence-Informed Sparse Neural Architecture for Stock Return Prediction," Papers 2608.14323, arXiv.org.
    34. Guo, Li & Sang, Bo & Tu, Jun & Wang, Yu, 2024. "Cross-cryptocurrency return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 163(C).
    35. Uddin, Ajim & Yu, Dantong, 2020. "Latent factor model for asset pricing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    36. Andrew Y. Chen, 2019. "The Limits of p-Hacking : A Thought Experiment," Finance and Economics Discussion Series 2019-016, Board of Governors of the Federal Reserve System (U.S.).
    37. Zhu, Lin & Jiang, Fuwei & Tang, Guohao & Jin, Fujing, 2024. "From macro to micro: Sparse macroeconomic risks and the cross-section of stock returns," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    38. Siddhartha Chib & Simon C. Smith, 2024. "Factor Selection and Structural Breaks," Finance and Economics Discussion Series 2024-037, Board of Governors of the Federal Reserve System (U.S.).
    39. Chen, Andrew Y. & McCoy, Jack, 2024. "Missing values handling for machine learning portfolios," Journal of Financial Economics, Elsevier, vol. 155(C).
    40. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    41. Ghosh, Anisha & Julliard, Christian & Taylor, Alex. P, 2025. "An information-theoretic asset pricing model," LSE Research Online Documents on Economics 126155, London School of Economics and Political Science, LSE Library.
    42. Shunyao Wang & Ming Cheng & Christina Dan Wang, 2025. "NewsNet-SDF: Stochastic Discount Factor Estimation with Pretrained Language Model News Embeddings via Adversarial Networks," Papers 2505.06864, arXiv.org.
    43. Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
    44. Chaieb, Ines & Langlois, Hugues & Scaillet, Olivier, 2021. "Factors and risk premia in individual international stock returns," Journal of Financial Economics, Elsevier, vol. 141(2), pages 669-692.
    45. Guettler, Andre & Naeem, Mahvish & Norden, Lars & Van Doornik, Bernardus, 2024. "Pre-publication revisions of bank financial statements: A novel way to monitor banks?," Journal of Financial Intermediation, Elsevier, vol. 58(C).
    46. Yousaf, Imran & Bejaoui, Azza & Ali, Shoaib & Li, Yanshuang, 2024. "Demystifying the dynamic relationship between news sentiment index and ESG stocks: Evidence from time-frequency wavelet analysis," International Review of Financial Analysis, Elsevier, vol. 96(PB).
    47. Jiang, Fuwei & Li, Kunpeng & Ning, Wei & Xue, Hao, 2026. "Scaled factor portfolio," Pacific-Basin Finance Journal, Elsevier, vol. 98(C).
    48. Luyang Chen & Markus Pelger & Jason Zhu, 2019. "Deep Learning in Asset Pricing," Papers 1904.00745, arXiv.org, revised Aug 2021.
    49. Gupta, Arpit & Van Nieuwerburgh, Stijn, 2019. "Valuing Private Equity Strip by Strip," CEPR Discussion Papers 14241, Centre for Economic Policy Research.
    50. Ruoxuan Xiong & Markus Pelger, 2019. "Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference," Papers 1910.08273, arXiv.org, revised Jan 2022.
    51. Matteo Bagnara & Benoit Vaucher, 2025. "Performance Misattributions," Journal of Asset Management, Palgrave Macmillan, vol. 26(7), pages 883-894, December.
    52. Gu, Shihao & Kelly, Bryan & Xiu, Dacheng, 2021. "Autoencoder asset pricing models," Journal of Econometrics, Elsevier, vol. 222(1), pages 429-450.
    53. Kaniel, Ron & Lin, Zihan & Pelger, Markus & Van Nieuwerburgh, Stijn, 2023. "Machine-learning the skill of mutual fund managers," Journal of Financial Economics, Elsevier, vol. 150(1), pages 94-138.
    54. Fieberg, Christian & Liedtke, Gerrit & Zaremba, Adam, 2024. "Cryptocurrency anomalies and economic constraints," International Review of Financial Analysis, Elsevier, vol. 94(C).
    55. Francisco Peñaranda & Enrique Sentana, 2024. "Portfolio management with big data," Working Papers wp2024_2411, CEMFI.
    56. Lin William Cong & Guanhao Feng & Jingyu He & Xin He, 2025. "Growing the Efficient Frontier on Panel Trees," Papers 2501.16730, arXiv.org, revised Feb 2025.
    57. Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
    58. Baba-Yara, Fahiz & Boons, Martijn & Tamoni, Andrea, 2024. "Persistent and transitory components of firm characteristics: Implications for asset pricing," Journal of Financial Economics, Elsevier, vol. 154(C).
    59. Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).
    60. Cakici, Nusret & Zaremba, Adam, 2025. "Accounting vs technical information: what matters more for stock return predictability?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 104(C).
    61. Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, The University of Osaka.
    62. Ouyang, Ruolan & Zhang, Kun & Zhang, Xuan & Zhu, Dongming, 2024. "Can factor momentum beat momentum factor? Evidence from China," Finance Research Letters, Elsevier, vol. 62(PA).
    63. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    64. Yoshimasa Uematsu & Shinya Tanaka, 2026. "Post-Screening Portfolio Selection," Papers 2604.17593, arXiv.org.
    65. Arpit Gupta & Stijn Van Nieuwerburgh, 2021. "Valuing Private Equity Investments Strip by Strip," Journal of Finance, American Finance Association, vol. 76(6), pages 3255-3307, December.
    66. Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2017. "Predicting Relative Returns," NBER Working Papers 23886, National Bureau of Economic Research, Inc.
    67. Meng, Qingbin & Qi, Ji & Wang, Solomon & Zhao, Xuankai, 2026. "Disciplining the factor zoo: Identifying pricing factors in the Chinese stock market," Economic Modelling, Elsevier, vol. 155(C).
    68. Ardia, David & Barras, Laurent & Gagliardini, Patrick & Scaillet, Olivier, 2024. "Is it alpha or beta? Decomposing hedge fund returns when models are misspecified," Journal of Financial Economics, Elsevier, vol. 154(C).
    69. Božović, Miloš, 2024. "VIX-managed portfolios," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    70. Söhnke M. Bartram & Harald Lohre & Peter F. Pope & Ananthalakshmi Ranganathan, 2021. "Navigating the factor zoo around the world: an institutional investor perspective," Journal of Business Economics, Springer, vol. 91(5), pages 655-703, July.
    71. Beckmeyer, Heiner & Wiedemann, Timo, 2022. "Recovering Missing Firm Characteristics with Attention-Based Machine Learning," VfS Annual Conference 2022 (Basel): Big Data in Economics 264135, Verein für Socialpolitik / German Economic Association.
    72. 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.
    73. Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
    74. Jin Du & Alexander Walter & Maxim Ulrich, 2026. "Cross-Market Alpha: Testing Short-Term Trading Factors in the U.S. Market via Double-Selection LASSO," Papers 2601.06499, arXiv.org, revised Sep 2026.
    75. Feng, Guanhao & He, Jingyu, 2022. "Factor investing: A Bayesian hierarchical approach," Journal of Econometrics, Elsevier, vol. 230(1), pages 183-200.
    76. Georges, Christophre & Pereira, Javier, 2021. "Market stability with machine learning agents," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).
    77. Dickerson, Alexander & Julliard, Christian & Mueller, Philippe, 2026. "The co-pricing factor zoo," LSE Research Online Documents on Economics 138476, London School of Economics and Political Science, LSE Library.
    78. Carter Davis, 2023. "The Elasticity of Quantitative Investment," Papers 2303.14533, arXiv.org, revised Sep 2024.
    79. Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2020. "Taming the Factor Zoo: A Test of New Factors," Journal of Finance, American Finance Association, vol. 75(3), pages 1327-1370, June.
    80. Bell, Sebastian & Kakhbod, Ali & Lettau, Martin & Nazemi, Abdolreza, 2026. "Glass box machine learning and corporate bond returns," Journal of Financial Economics, Elsevier, vol. 181(C).
    81. Aoxin Zhang & Yuhan Cheng & Kwanting Leung, 2026. "Benchmarking Deep Time Series Models for Equity Portfolios," Papers 2606.09420, arXiv.org.
    82. Andrew Y. Chen & Jack McCoy, 2022. "Missing Values Handling for Machine Learning Portfolios," Papers 2207.13071, arXiv.org, revised Jan 2024.
    83. Kristoffer Pons Bertelsen, 2022. "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers 2022-05, Department of Economics and Business Economics, Aarhus University.
    84. Firoozye, Nikan & Tan, Vincent & Zohren, Stefan, 2023. "Canonical portfolios: Optimal asset and signal combination," Journal of Banking & Finance, Elsevier, vol. 154(C).
    85. Bank, Matthias & Insam, Franz, 2021. "Corporate aging and changes in the pricing of stock characteristics," Finance Research Letters, Elsevier, vol. 42(C).
    86. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
    87. Wu, Hongxu & Wang, Qiao & Li, Jianping & Deng, Zhibin, 2025. "Enhancing stock return prediction in the Chinese market: A GAN-based approach," Research in International Business and Finance, Elsevier, vol. 75(C).
    88. Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
    89. Seegmiller, Bryan, 2026. "Intermediation frictions in equity markets," Journal of Financial Economics, Elsevier, vol. 176(C).
    90. Guanhao Feng & Jingyu He & Nicholas G. Polson, 2018. "Deep Learning for Predicting Asset Returns," Papers 1804.09314, arXiv.org, revised Apr 2018.
    91. Mekelburg, Erik & Strauss, Jack, 2024. "Pooling and winsorizing machine learning forecasts to predict stock returns with high-dimensional data," Journal of Empirical Finance, Elsevier, vol. 79(C).
    92. Caio Vigo Pereira, 2020. "Portfolio Efficiency with High-Dimensional Data as Conditioning Information," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202015, University of Kansas, Department of Economics, revised Sep 2020.
    93. Bagnara, Matteo & Goodarzi, Milad, 2023. "Clustering-based sector investing," SAFE Working Paper Series 397, Leibniz Institute for Financial Research SAFE.
    94. Hoechle, Daniel & Schmid, Markus & Zimmermann, Heinz, 2017. "Does Unobservable Heterogeneity Matter for Portfolio-Based Asset Pricing Tests?," Working Papers on Finance 1717, University of St. Gallen, School of Finance, revised Mar 2020.
    95. Müller, Sebastian & Pugachyov, Nikolay & Weigert, Florian, 2026. "Forecasting mutual fund performance: Combining return-based with portfolio holdings-based predictors," CFR Working Papers 26-01, University of Cologne, Centre for Financial Research (CFR).
    96. Wang, Feifei & Yan, Xuemin Sterling, 2021. "Downside risk and the performance of volatility-managed portfolios," Journal of Banking & Finance, Elsevier, vol. 131(C).
    97. Celso Brunetti & Marc Joëts & Valérie Mignon, 2023. "Reasons Behind Words: OPEC Narratives and the Oil Market," Working Papers 2023-19, CEPII research center.
    98. Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2020. "Factor Timing," NBER Working Papers 26708, National Bureau of Economic Research, Inc.
    99. Guo, Xu & Lin, Hai & Wu, Chunchi & Zhou, Guofu, 2022. "Predictive information in corporate bond yields," Journal of Financial Markets, Elsevier, vol. 59(PB).
    100. Mao, Jie & Shao, Jingjing & Wang, Weiguan, 2025. "Risk premium principal components for the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 89(C).
    101. Lassance, Nathan & Vanderveken, Rodolphe & Vrins, Frédéric, 2025. "Shrink with Purpose: Optimal Covariance Matrix Estimation for Portfolio Selection," LIDAM Discussion Papers LFIN 2025002, Université catholique de Louvain, Louvain Finance (LFIN).
    102. Markus Pelger, 2020. "Understanding Systematic Risk: A High‐Frequency Approach," Journal of Finance, American Finance Association, vol. 75(4), pages 2179-2220, August.
    103. Ai He & Guofu Zhou, 2023. "Diagnostics for asset pricing models," Financial Management, Financial Management Association International, vol. 52(4), pages 617-642, December.
    104. Mercik, Aleksander & Zaremba, Adam & Demir, Ender, 2026. "Crypto factor zoo (.Zip)," International Review of Financial Analysis, Elsevier, vol. 113(C).
    105. Cássio Roberto de Andrade Alves & Márcio Laurini, 2023. "Estimating the Capital Asset Pricing Model with Many Instruments: A Bayesian Shrinkage Approach," Mathematics, MDPI, vol. 11(17), pages 1-20, September.
    106. Fieberg, Christian & Liedtke, Gerrit & Zaremba, Adam & Cakici, Nusret, 2025. "A factor model for the cross-section of country equity risk premia," Journal of Banking & Finance, Elsevier, vol. 171(C).
    107. Paraschiv, Florentina & Schmid, Markus & Wahlstrøm, Ranik Raaen, 2026. "Bankruptcy prediction of privately held SMEs using feature selection methods," Journal of Empirical Finance, Elsevier, vol. 86(C).
    108. Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," Papers 2009.03394, arXiv.org, revised Feb 2026.
    109. Wolfgang Drobetz & Tizian Otto, 2021. "Empirical asset pricing via machine learning: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 22(7), pages 507-538, December.
    110. Shi, Yun & Kong, Lingjie & Yang, Lanzhi & Li, Duan & Cui, Xiangyu, 2024. "Dynamic mean-variance portfolio selection under factor models," Journal of Economic Dynamics and Control, Elsevier, vol. 167(C).
    111. Doron Avramov & Si Cheng & Lior Metzker, 2023. "Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability," Management Science, INFORMS, vol. 69(5), pages 2587-2619, May.
    112. Guilherme V. Moura & Andr'e P. Santos & Hudson S. Torrent, 2025. "Variable selection for minimum-variance portfolios," Papers 2508.14986, arXiv.org.
    113. Mehmet Caner & Agostino Capponi & Nathan Sun & Jonathan Y. Tan, 2026. "Designing Agentic AI-Based Screening for Portfolio Investment," Papers 2603.23300, arXiv.org, revised Aug 2026.
    114. Zhipeng Liao & Yan Liu & Zhenzhen Xie, 2024. "Optimal Cross-Sectional Regression," Management Science, INFORMS, vol. 70(11), pages 7911-7942, November.
    115. Ma, Tian & Liao, Cunfei & Jiang, Fuwei, 2024. "Factor momentum in the Chinese stock market," Journal of Empirical Finance, Elsevier, vol. 75(C).
    116. Nathan Lassance & Victor DeMiguel & Frédéric Vrins, 2022. "Optimal Portfolio Diversification via Independent Component Analysis," Operations Research, INFORMS, vol. 70(1), pages 55-72, January.
    117. Paul Schneider & Christian Wagner & Josef Zechner, 2020. "Low‐Risk Anomalies?," Journal of Finance, American Finance Association, vol. 75(5), pages 2673-2718, October.
    118. Lioui, Abraham & Tarelli, Andrea, 2022. "Chasing the ESG factor," Journal of Banking & Finance, Elsevier, vol. 139(C).
    119. Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
    120. Alexander Arimond & Damian Borth & Andreas Hoepner & Michael Klawunn & Stefan Weisheit, 2020. "Neural Networks and Value at Risk," Papers 2005.01686, arXiv.org, revised May 2020.
    121. Angelidis, Timotheos & Sakkas, Athanasios & Tessaromatis, Nikolaos, 2025. "Predicting commodity returns: Time series vs. cross sectional prediction models," Journal of Commodity Markets, Elsevier, vol. 38(C).
    122. Jorge Guijarro-Ordonez & Markus Pelger & Greg Zanotti, 2021. "Deep Learning Statistical Arbitrage," Papers 2106.04028, arXiv.org, revised Oct 2022.
    123. Andrew Y. Chen & Tom Zimmermann, 2018. "Publication Bias and the Cross-Section of Stock Returns," Finance and Economics Discussion Series 2018-033, Board of Governors of the Federal Reserve System (U.S.).
    124. Nechvátalová, Lenka, 2025. "Autoencoder asset pricing models and economic restrictions — international evidence," International Review of Financial Analysis, Elsevier, vol. 107(C).
    125. Chen, Shan & Li, Tao, 2025. "A unified duration-based explanation of the value, profitability, and investment anomalies," Journal of Empirical Finance, Elsevier, vol. 84(C).
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    127. Christian Schlag & Michael Semenischev & Julian Thimme, 2021. "Predictability and the Cross-Section of Expected Returns: A Challenge for Asset Pricing Models," Management Science, INFORMS, vol. 67(12), pages 7932-7950, December.
    128. Wang, Jinzhe & Zhu, Yifeng, 2024. "A comparison of factor models in China," Journal of Empirical Finance, Elsevier, vol. 79(C).
    129. Oghenovo A. Obrimah, 2025. "Is the Fama and French three factor model robust to the pricing of risk preferences?," Empirical Economics, Springer, vol. 69(4), pages 2027-2063, October.
    130. Dohyun Chun & Jongho Kang & Jihun Kim, 2024. "Forecasting returns with machine learning and optimizing global portfolios: evidence from the Korean and U.S. stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-30, December.
    131. Lettau, Martin & Pelger, Markus, 2018. "Factors that Fit the Time Series and Cross-Section of Stock Returns," CEPR Discussion Papers 13049, Centre for Economic Policy Research.
    132. Helena Chuliá & Sabuhi Khalili & Jorge M. Uribe, 2024. "Monitoring time-varying systemic risk in sovereign debt and currency markets with generative AI," IREA Working Papers 202402, University of Barcelona, Research Institute of Applied Economics, revised Feb 2024.
    133. Sak, Halis & Huang, Tao & Chng, Michael T., 2024. "Exploring the factor zoo with a machine-learning portfolio," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    134. Martin, Ian W.R. & Nagel, Stefan, 2022. "Market efficiency in the age of big data," Journal of Financial Economics, Elsevier, vol. 145(1), pages 154-177.
    135. Son, Bumho & Lee, Jaewook, 2022. "Graph-based multi-factor asset pricing model," Finance Research Letters, Elsevier, vol. 44(C).
    136. Anatolyev, Stanislav & Mikusheva, Anna, 2022. "Factor models with many assets: Strong factors, weak factors, and the two-pass procedure," Journal of Econometrics, Elsevier, vol. 229(1), pages 103-126.
    137. Solène Collot & Tobias Hemauer, 2021. "A literature review of new methods in empirical asset pricing: omitted-variable and errors-in-variable bias," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 35(1), pages 77-100, March.
    138. João Gabriel Moraes Souza & Daniel Tavares Castro & Yaohao Peng & Ivan Ricardo Gartner, 2024. "A Machine Learning-Based Analysis on the Causality of Financial Stress in Banking Institutions," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1857-1890, September.
    139. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
    140. Aleksey Kolokolov & Shifan Yu, 2026. "Realized Regularized Regressions," Papers 2604.23023, arXiv.org.
    141. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2025. "Volatility forecasting and volatility-timing strategies: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 75(C).
    142. Chen, Yi-Hsuan & Kräussl, Roman & Verwijmeren, Patrick, 2023. "The pricing of digital art," CFS Working Paper Series 716, Center for Financial Studies (CFS).
    143. Langlois, Hugues, 2023. "What matters in a characteristic?," Journal of Financial Economics, Elsevier, vol. 149(1), pages 52-72.
    144. Shiyang Huang & Yang Song & Hong Xiang, 2025. "Noise Trading and Asset Pricing Factors," Management Science, INFORMS, vol. 71(8), pages 6961-6978, August.
    145. Mao, Jie & Xia, Xiaobao & Zhuo, Haotian, 2025. "Taming the factor zoo in China’s equity market: A Bayesian approach," Pacific-Basin Finance Journal, Elsevier, vol. 93(C).
    146. Ni, Xuanming & Zheng, Tiantian & Zhao, Huimin & Zhu, Shushang, 2023. "High-dimensional portfolio optimization based on tree-structured factor model," Pacific-Basin Finance Journal, Elsevier, vol. 81(C).
    147. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    148. Branco, Rafael R. & Rubesam, Alexandre & Zevallos, Mauricio, 2024. "Forecasting realized volatility: Does anything beat linear models?," Journal of Empirical Finance, Elsevier, vol. 78(C).
    149. Junchi Shen, 2026. "Quantum Kernels and the Cross-Section of Stock Returns: Anatomy of a Vanishing Advantage," Papers 2607.20168, arXiv.org.
    150. Raymond Kan & Xiaolu Wang & Guofu Zhou, 2022. "Optimal Portfolio Choice with Estimation Risk: No Risk-Free Asset Case," Management Science, INFORMS, vol. 68(3), pages 2047-2068, March.
    151. Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," The Warwick Economics Research Paper Series (TWERPS) 1230, University of Warwick, Department of Economics.
    152. Nima Afsharhajari & Jonathan Yu-Meng Li, 2026. "The Virtue of Sparsity in Complexity," Papers 2604.17166, arXiv.org, revised Sep 2026.
    153. Schlag, Christian & Semenischev, Michael & Thimme, Julian, 2020. "Predictability and the cross-section of expected returns: A challenge for asset pricing models," SAFE Working Paper Series 289, Leibniz Institute for Financial Research SAFE.
    154. Duan, Xinrui & Guo, Li & Li, Frank Weikai & Tu, Jun, 2025. "Do factor models capture both sentiment and limited attention?," Journal of Economic Dynamics and Control, Elsevier, vol. 181(C).
    155. Khoa Hoang & Robert Faff, 2021. "Is the ex‐ante equity risk premium always positive? Evidence from a new conditional expectations model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(1), pages 95-124, March.
    156. Alois Weigand, 2019. "Machine learning in empirical asset pricing," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(1), pages 93-104, March.
    157. Wan, Runzhe & Li, Yingying & Lu, Wenbin & Song, Rui, 2024. "Mining the factor zoo: Estimation of latent factor models with sufficient proxies," Journal of Econometrics, Elsevier, vol. 239(2).
    158. Yuan Liao & Xinjie Ma & Andreas Neuhierl & Linda Schilling, 2025. "The Uncertainty of Machine Learning Predictions in Asset Pricing," Papers 2503.00549, arXiv.org.
    159. Changeun Kim & Younwoo Jeong & Bong-Gyu Jang, 2025. "Interpretable Deep Learning for Stock Returns: A Consensus-Bottleneck Asset Pricing Model," Papers 2512.16251, arXiv.org, revised Apr 2026.
    160. Korsaye, Sofonias Alemu & Trojani, Fabio & Vedolin, Andrea, 2020. "The Global Factor Structure of Exchange Rates," CEPR Discussion Papers 15337, Centre for Economic Policy Research.
    161. Peng, Yaohao & de Moraes Souza, João Gabriel, 2024. "Chaos, overfitting and equilibrium: To what extent can machine learning beat the financial market?," International Review of Financial Analysis, Elsevier, vol. 95(PB).
    162. Zhao, Yu & Lin, Sen & Kong, Ao, 2026. "Reconciling interpretability and accuracy: Evidence from categorical factors," International Review of Economics & Finance, Elsevier, vol. 107(C).
    163. Evangelos Liaras & Michail Nerantzidis & Antonios Alexandridis, 2024. "Machine learning in accounting and finance research: a literature review," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1431-1471, November.
    164. Chen, Ding & Guo, Biao & Zhou, Guofu, 2023. "Firm fundamentals and the cross-section of implied volatility shapes," Journal of Financial Markets, Elsevier, vol. 63(C).
    165. Liao Zhu, 2021. "The Adaptive Multi-Factor Model and the Financial Market," Papers 2107.14410, arXiv.org, revised Aug 2021.
    166. Bernd Johannes Wuebben, 2026. "Beyond De Prado and Cotton: Hierarchical and Iterative Methods for General Mean-Variance Portfolios," Papers 2604.23833, arXiv.org.
    167. Bagnara, Matteo, 2024. "The economic value of cross-predictability: A performance-based measure," SAFE Working Paper Series 424, Leibniz Institute for Financial Research SAFE.
    168. Lu, Zhongjin & Malliaris, Steven & Qin, Zhongling, 2023. "Heterogeneous liquidity providers and night-minus-day return predictability," Journal of Financial Economics, Elsevier, vol. 148(3), pages 175-200.
    169. Alexander M. Chinco & Andreas Neuhierl & Michael Weber, 2019. "Estimating The Anomaly Base Rate," NBER Working Papers 26493, National Bureau of Economic Research, Inc.
    170. Alexander M. Chinco & Adam D. Clark-Joseph & Mao Ye, 2017. "Sparse Signals in the Cross-Section of Returns," NBER Working Papers 23933, National Bureau of Economic Research, Inc.
    171. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2022. "On modeling IPO failure risk," Economic Modelling, Elsevier, vol. 109(C).
    172. Jiang, Fuwei & Liu, Hongkui & Tang, Guohao & Yu, Jiasheng, 2024. "Global mispricing matters," Journal of International Money and Finance, Elsevier, vol. 147(C).
    173. Cakici, Nusret & Fieberg, Christian & Metko, Daniel & Zaremba, Adam, 2025. "Factor momentum versus price momentum: Insights from international markets," Journal of Banking & Finance, Elsevier, vol. 170(C).
    174. Bo Yu & Dayong Zhang & Qiang Ji, 2025. "Forecasting portfolio variance: a new decomposition approach," Annals of Operations Research, Springer, vol. 348(1), pages 543-578, May.
    175. Hyuksoo Kim & Saejoon Kim, 2024. "Estimating Asset Pricing Models in the Presence of Cross-Sectionally Correlated Pricing Errors," Mathematics, MDPI, vol. 12(21), pages 1-21, November.
    176. Miguel C. Herculano, 2026. "Bayesian Parametric Portfolio Policies," Papers 2602.21173, arXiv.org.
    177. Kwon, Tae Yeon, 2025. "Feature importance in linear models with ensemble machine learning: A study of the Fama and French five-factor model," Finance Research Letters, Elsevier, vol. 71(C).
    178. Bo Li & Sabri Boubaker & Zhenya Liu & Waël Louhichi & Yao Yao, 2023. "Exploring the Nonlinear Idiosyncratic Volatility Puzzle: Evidence from China," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 527-559, August.
    179. Huang, Jiantao & Shi, Ran, 2026. "Model uncertainty in the cross-section of stock returns," Journal of Econometrics, Elsevier, vol. 256(PB).
    180. Fuwei Jiang & Wei Ning & Hao Xue, 2023. "Factor Timing with Investor Sentiment," Annals of Economics and Finance, Society for AEF, vol. 24(2), pages 401-437, November.
    181. Alexander M. Chinco & Samuel M. Hartzmark & Abigail B. Sussman, 2020. "Necessary Evidence For A Risk Factor’s Relevance," NBER Working Papers 27227, National Bureau of Economic Research, Inc.
    182. Joseph E. Engelberg & Richard B. Evans & Greg Leonard & Adam V. Reed & Matthew C. Ringgenberg, 2025. "The Loan Fee Anomaly: A Short Seller’s Best Ideas," Management Science, INFORMS, vol. 71(7), pages 5529-5551, July.
    183. Lettau, Martin & Pelger, Markus, 2018. "Estimating Latent Asset-Pricing Factors," CEPR Discussion Papers 12926, Centre for Economic Policy Research.
    184. Yuxiao Jiao & Guofu Zhou & Wu Zhu & Yingzi Zhu, 2025. "Interpretable Factors of Firm Characteristics," Papers 2508.02253, arXiv.org.
    185. Hao Jiang & Naveen Khanna & Qian Yang & Jiayu Zhou, 2024. "The Cyber Risk Premium," Management Science, INFORMS, vol. 70(12), pages 8791-8817, December.
    186. van Binsbergen, Jules H. & Boons, Martijn & Opp, Christian C. & Tamoni, Andrea, 2023. "Dynamic asset (mis)pricing: Build-up versus resolution anomalies," Journal of Financial Economics, Elsevier, vol. 147(2), pages 406-431.
    187. Birru, Justin & Gokkaya, Sinan & Liu, Xi & Markov, Stanimir, 2024. "Quants and market anomalies," Journal of Accounting and Economics, Elsevier, vol. 78(1).
    188. Wang, Ming-Long & Shi, Huai-Long & Wan, Yu-Lei & Wang, Jing-Jin, 2026. "Luck “duels” among factors in China," The Quarterly Review of Economics and Finance, Elsevier, vol. 106(C).
    189. Li, Delong & Lu, Lei & Qi, Zhen & Zhou, Guofu, 2026. "International corporate bond returns: Uncovering predictability using machine learning," Journal of Financial Markets, Elsevier, vol. 79(C).
    190. 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.
    191. Jing Hao & Feng He & Feng Ma & Shibo Zhang & Xiaotao Zhang, 2025. "Machine learning vs deep learning in stock market investment: an international evidence," Annals of Operations Research, Springer, vol. 348(1), pages 93-115, May.
    192. Molero González, Laura & Cerqueti, Roy & Mattera, Raffaele & Sánchez Granero, Miguel Ángel & Trinidad Segovia, Juan Evangelista, 2025. "Analyzing clustered factors in the cryptocurrency market with Random Matrix Theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 665(C).
    193. Yoontae Hwang, 2026. "Portfolio Preference Elicitation in Institutional Crossing Markets," Papers 2605.21409, arXiv.org.
    194. Alex R. Horenstein, 2021. "The Unintended Impact of Academic Research on Asset Returns: The Capital Asset Pricing Model Alpha," Management Science, INFORMS, vol. 67(6), pages 3655-3673, June.
    195. Grammig, Joachim & Hanenberg, Constantin & Schlag, Christian & Sönksen, Jantje, 2020. "Diverging roads: Theory-based vs. machine learning-implied stock risk premia," University of Tübingen Working Papers in Business and Economics 130, University of Tuebingen, Faculty of Economics and Social Sciences, School of Business and Economics.
    196. Venky Nagar & Jordan Schoenfeld, 2024. "Measuring weather exposure with annual reports," Review of Accounting Studies, Springer, vol. 29(1), pages 1-32, March.
    197. Jin, Xuejun & Chen, Yifan & Liu, Xiaobin & Zeng, Tao, 2026. "Factors in the cross-section of Chinese corporate bonds: Evidence from reduced-rank analysis," Journal of Empirical Finance, Elsevier, vol. 85(C).
    198. Huang, Dashan & Li, Jiangyuan & Wang, Liyao, 2021. "Are disagreements agreeable? Evidence from information aggregation," Journal of Financial Economics, Elsevier, vol. 141(1), pages 83-101.
    199. Wang, Chuyu & Zhang, Guanglong, 2025. "In the shadows of opacity: Firm information quality and latent factor model performance," International Review of Financial Analysis, Elsevier, vol. 100(C).
    200. Li, Bin & Rossi, Alberto G. & Yan, Xuemin (Sterling) & Zheng, Lingling, 2025. "Machine learning from a “Universe” of signals: The role of feature engineering," Journal of Financial Economics, Elsevier, vol. 172(C).
    201. Liu, Tingting & Lu, Zhongjin (Gene) & Shu, Tao & Wei, Fengrong, 2022. "Unique bidder-target relatedness and synergies creation in mergers and acquisitions," Journal of Corporate Finance, Elsevier, vol. 73(C).
    202. Hongyi Liu, 2025. "Deep Learning for Conditional Asset Pricing Models," Papers 2509.04812, arXiv.org.
    203. Lavko, Matus & Klein, Tony & Walther, Thomas, 2023. "Reinforcement Learning and Portfolio Allocation: Challenging Traditional Allocation Methods," QBS Working Paper Series 2023/01, Queen's University Belfast, Queen's Business School.
    204. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.
    205. Jian'an Zhang, 2025. "FR-LUX: Friction-Aware, Regime-Conditioned Policy Optimization for Implementable Portfolio Management," Papers 2510.02986, arXiv.org.
    206. Bianchi, Francesco & Ludvigson, Sydney & MA, Sai, 2020. "Belief Distortions and Macroeconomic Fluctuations," CEPR Discussion Papers 15003, Centre for Economic Policy Research.
    207. Zheng Tracy Ke & Bryan T. Kelly & Dacheng Xiu, 2019. "Predicting Returns With Text Data," NBER Working Papers 26186, National Bureau of Economic Research, Inc.
    208. Fousseni Chabi-Yo & Markus Huggenberger & Florian Weigert, 2019. "Multivariate Crash Risk," Working Papers on Finance 1901, University of St. Gallen, School of Finance.
    209. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.

  5. Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2017. "Predicting Relative Returns," NBER Working Papers 23886, National Bureau of Economic Research, Inc.

    Cited by:

    1. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    2. Mikhail Chernov & Drew D. Creal & Peter Hördahl, 2020. "Sovereign Credit and Exchange Rate Risks: Evidence from Asia-Pacific Local Currency Bonds," NBER Working Papers 27500, National Bureau of Economic Research, Inc.
    3. Lars A. Lochstoer & Paul C. Tetlock, 2020. "What Drives Anomaly Returns?," Journal of Finance, American Finance Association, vol. 75(3), pages 1417-1455, June.

Articles

  1. Stefano Giglio & Bryan Kelly & Serhiy Kozak, 2024. "Equity Term Structures without Dividend Strips Data," Journal of Finance, American Finance Association, vol. 79(6), pages 4143-4196, December.
    See citations under working paper version above.
  2. Kozak, Serhiy, 2022. "Dynamics of bond and stock returns," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 188-209.

    Cited by:

    1. Ermolov, Andrey, 2022. "Time-varying risk of nominal bonds: How important are macroeconomic shocks?," Journal of Financial Economics, Elsevier, vol. 145(1), pages 1-28.
    2. Pflueger, Carolin, 2025. "Back to the 1980s or not? The drivers of inflation and real risks in Treasury bonds," Journal of Financial Economics, Elsevier, vol. 167(C).
    3. Gregory R Duffee, 2023. "Macroeconomic News and Stock–Bond Comovement," Review of Finance, European Finance Association, vol. 27(5), pages 1859-1882.
    4. Sungjun Cho & Liu Liu, 2023. "Correcting estimation bias in regime switching dynamic term structure models," Review of Quantitative Finance and Accounting, Springer, vol. 61(3), pages 1093-1127, October.
    5. Wang, Yanning & Wang, Xichen, 2024. "The role of central bank communication in the long-term stock-bond correlations: Evidence from China," Finance Research Letters, Elsevier, vol. 67(PB).
    6. Zeng, Ming & Zhao, Guihai, 2026. "Expectation-driven term structure of equity and bond yields," Journal of Monetary Economics, Elsevier, vol. 157(C).
    7. Husain, Afzol & Karim, Sitara & Sensoy, Ahmet, 2024. "Financial fusion: Bridging Islamic and Green investments in the European stock market," International Review of Financial Analysis, Elsevier, vol. 94(C).
    8. Coulombe, Raphaelle G. & McNeil, James, 2025. "The term structure of interest rates in a noisy information model," Journal of International Money and Finance, Elsevier, vol. 159(C).
    9. Sungjune Pyun, 2025. "Stock-Bond Return Dynamics and the Expected Country Stock Returns," Management Science, INFORMS, vol. 71(12), pages 10603-10623, December.
    10. Ma, Lidong & Xiong, Youlin & Shen, Jun, 2026. "Global supply chain pressure and long-term stock–bond correlations in China," Finance Research Letters, Elsevier, vol. 103(C).

  3. Kozak, Serhiy & Santosh, Shrihari, 2020. "Why do discount rates vary?," Journal of Financial Economics, Elsevier, vol. 137(3), pages 740-751.

    Cited by:

    1. Stefano Giglio & Bryan Kelly & Serhiy Kozak, 2024. "Equity Term Structures without Dividend Strips Data," Journal of Finance, American Finance Association, vol. 79(6), pages 4143-4196, December.
    2. Nian, Victor & Mignacca, Benito & Locatelli, Giorgio, 2022. "Policies toward net-zero: Benchmarking the economic competitiveness of nuclear against wind and solar energy," Applied Energy, Elsevier, vol. 320(C).
    3. Ajab Khan, 2024. "Nexus Between Discount Rate and Industrial Performance," Global Business Review, International Management Institute, vol. 25(6), pages 1590-1602, December.
    4. Jiang, Fuwei & Li, Kunpeng & Ning, Wei & Xue, Hao, 2026. "Scaled factor portfolio," Pacific-Basin Finance Journal, Elsevier, vol. 98(C).
    5. Pflueger, Carolin, 2025. "Back to the 1980s or not? The drivers of inflation and real risks in Treasury bonds," Journal of Financial Economics, Elsevier, vol. 167(C).
    6. Roberto Gómez‐Cram, 2022. "Late to Recessions: Stocks and the Business Cycle," Journal of Finance, American Finance Association, vol. 77(2), pages 923-966, April.
    7. Fousseni Chabi-Yo & Andrei S. Gonçalves & Johnathan A. Loudis, 2025. "An Intertemporal Risk Factor Model," Management Science, INFORMS, vol. 71(8), pages 6518-6544, August.
    8. Indrajit Mitra & Taeuk Seo & Yu Xu, 2021. "High Discounts and Low Fundamental Surplus: An Equivalence Result for Unemployment Fluctuations," FRB Atlanta Working Paper 2021-22, Federal Reserve Bank of Atlanta.
    9. Li, Ye & Wang, Chen, 2025. "The Information Cliff," SocArXiv bf8cx_v1, Center for Open Science.
    10. Fuwei Jiang & Wei Ning & Hao Xue, 2023. "Factor Timing with Investor Sentiment," Annals of Economics and Finance, Society for AEF, vol. 24(2), pages 401-437, November.
    11. Kozak, Serhiy, 2022. "Dynamics of bond and stock returns," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 188-209.
    12. Qiang Chen & Xinyi Song, 2026. "Crash Risk Matters: An Option‐Implied Approach to the Expected Market Return," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 46(3), pages 511-528, March.
    13. Kroencke, Tim A., 2022. "Recessions and the stock market," Journal of Monetary Economics, Elsevier, vol. 131(C), pages 61-77.

  4. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
    See citations under working paper version above.
  5. Valentin Haddad & Serhiy Kozak & Shrihari Santosh & Stijn Van Nieuwerburgh, 2020. "Factor Timing," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 1980-2018.
    See citations under working paper version above.
  6. Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2018. "Interpreting Factor Models," Journal of Finance, American Finance Association, vol. 73(3), pages 1183-1223, June.

    Cited by:

    1. Christopher G. Lamoureux, 2026. "The Gibbs Posterior and Parametric Portfolio Choice," Papers 2603.02455, arXiv.org, revised Mar 2026.
    2. Azi Ben‐Rephael & Bruce I. Carlin & Zhi Da & Ryan D. Israelsen, 2021. "Information Consumption and Asset Pricing," Journal of Finance, American Finance Association, vol. 76(1), pages 357-394, February.
    3. Liu, Weiyi & Zhang, Huachen & Wan, Die, 2026. "Overlapping factor momentum," Finance Research Letters, Elsevier, vol. 90(C).
    4. Cong, Lin William & Feng, Guanhao & He, Jingyu & He, Xin, 2025. "Growing the efficient frontier on panel trees," Journal of Financial Economics, Elsevier, vol. 167(C).
    5. Maysam Khodayari Gharanchaei & Prabhu Prasad Panda & Xilin Chen, 2024. "Quantitative Investment Diversification Strategies via Various Risk Models," Papers 2407.01550, arXiv.org.
    6. Nathan Lassance & Alberto Martín-Utrera & Majeed Simaan, 2024. "The Risk of Expected Utility Under Parameter Uncertainty," Management Science, INFORMS, vol. 70(11), pages 7644-7663, November.
    7. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
    8. Gregory Nazaire & Maria Pacurar & Oumar Sy, 2020. "Betas versus characteristics: A practical perspective," European Financial Management, European Financial Management Association, vol. 26(5), pages 1385-1413, November.
    9. Heping Xiong & Chao Tang & Jianhui Cao & Haitao Zhang, 2025. "A New Four-factor Model for the Chinese Stock Market," Annals of Economics and Finance, Society for AEF, vol. 26(2), pages 853-890, November.
    10. Shaun Bond & Hui Guo & Changyu Yang, 2025. "Systematic Mispricing: Evidence from Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 71(3), pages 420-452, October.
    11. Choi, Jiyoon, 2026. "Factor timing in currency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 110(C).
    12. Pedro M. Mirete-Ferrer & Alberto Garcia-Garcia & Juan Samuel Baixauli-Soler & Maria A. Prats, 2022. "A Review on Machine Learning for Asset Management," Risks, MDPI, vol. 10(4), pages 1-46, April.
    13. Jia, Yuecheng & Liu, Yuzheng & Wu, Yangru & Yan, Shu, 2024. "Information spillover and cross-predictability of currency returns: An analysis via Machine Learning," Journal of Banking & Finance, Elsevier, vol. 169(C).
    14. Yu Wang & Haicheng Shu, 2019. "Evaluating the Performance of Factor Pricing Models for Different Stock Market Trends: Evidence from China," Working Papers 2019-10-10, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    15. José Luis Montiel Olea & Pietro Ortoleva & Mallesh Pai & Andrea Prat, 2021. "Competing Models," Working Papers 2021-89, Princeton University. Economics Department..
    16. Kang, Hankil & Ryu, Doojin, 2019. "Information in mispricing factors for future investment opportunities," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 657-668.
    17. Yiyan Qian & Ying Jiang & Xiaoquan Liu, 2025. "Factor Momentum in Commodity Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(11), pages 1934-1969, November.
    18. Cho, Thummim, 2020. "Turning alphas into betas: arbitrage and endogenous risk," LSE Research Online Documents on Economics 102085, London School of Economics and Political Science, LSE Library.
    19. Maik Dierkes & Sebastian Schroen, 2023. "Betting against sentiment? Seemingly unrelated anomalies and the low‐risk effect," Review of Financial Economics, John Wiley & Sons, vol. 41(2), pages 152-176, April.
    20. Jules H van Binsbergen & Xiao Han & Alejandro Lopez-Lira, 2023. "Man versus Machine Learning: The Term Structure of Earnings Expectations and Conditional Biases," The Review of Financial Studies, Society for Financial Studies, vol. 36(6), pages 2361-2396.
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