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Seth Pruitt

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Stefano Giglio & Bryan T. Kelly & Seth Pruitt, 2015. "Systemic Risk and the Macroeconomy: An Empirical Evaluation," NBER Working Papers 20963, National Bureau of Economic Research, Inc.

    Mentioned in:

    1. The mythic quest for early warnings
      by Steve Cecchetti and Kim Schoenholtz in Money, Banking and Financial Markets on 2015-04-13 17:40:01

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Nir Jaimovich & Seth Pruitt & Henry E. Siu, 2013. "The Demand for Youth: Explaining Age Differences in the Volatility of Hours," American Economic Review, American Economic Association, vol. 103(7), pages 3022-3044, December.

    Mentioned in:

    1. The Demand for Youth: Explaining Age Differences in the Volatility of Hours (AER 2013) in ReplicationWiki ()
  2. James D. Hamilton & Seth Pruitt & Scott Borger, 2011. "Estimating the Market-Perceived Monetary Policy Rule," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 1-28, July.

    Mentioned in:

    1. Estimating the Market-Perceived Monetary Policy Rule (AEJ:MA 2011) in ReplicationWiki ()

Working papers

  1. 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.

    Cited by:

    1. Jan Sila & Michael Mark & Ladislav Kristoufek & Thomas A. Weber, 2025. "Crypto market betas: the limits of predictability and hedging," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-28, December.
    2. Cakici, Nusret & Zaremba, Adam, 2024. "What drives stock returns across countries? Insights from machine learning models," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    3. 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).
    4. Valentin Haddad & Tyler Muir, 2021. "Do Intermediaries Matter for Aggregate Asset Prices?," Journal of Finance, American Finance Association, vol. 76(6), pages 2719-2761, December.
    5. Alexander M. Chinco & Andreas Neuhierl & Michael Weber, 2019. "Estimating The Anomaly Base Rate," NBER Working Papers 26493, National Bureau of Economic Research, Inc.
    6. Christopher G. Lamoureux, 2026. "The Gibbs Posterior and Parametric Portfolio Choice," Papers 2603.02455, arXiv.org, revised Mar 2026.
    7. Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).
    8. Amit Goyal & Alessio Saretto, 2022. "Are Equity Option Returns Abnormal? IPCA Says No," Working Papers 2214, Federal Reserve Bank of Dallas.
    9. Leippold, Markus & Wang, Qian & Zhou, Wenyu, 2022. "Machine learning in the Chinese stock market," Journal of Financial Economics, Elsevier, vol. 145(2), pages 64-82.
    10. Fabian Krause & Jan-Peter Calliess, 2024. "End-to-End Policy Learning of a Statistical Arbitrage Autoencoder Architecture," Papers 2402.08233, arXiv.org.
    11. Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022. "Deep Partial Least Squares for Empirical Asset Pricing," Papers 2206.10014, arXiv.org.
    12. Alejandro Rodriguez Dominguez, 2026. "Causal Separation in Portfolio Choice: Screening-Off Information and Conditional Risk," Papers 2607.05320, arXiv.org, revised Aug 2026.
    13. 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.
    14. Wolfgang Drobetz & Rebekka Haller & Christian Jasperneite & Tizian Otto, 2019. "Predictability and the cross section of expected returns: evidence from the European stock market," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 508-533, December.
    15. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    16. Alex Chinco & Samuel M. Hartzmark & Abigail B. Sussman, 2022. "A New Test of Risk Factor Relevance," Journal of Finance, American Finance Association, vol. 77(4), pages 2183-2238, August.
    17. Bartram, Söhnke M. & Grinblatt, Mark, 2021. "Global market inefficiencies," Journal of Financial Economics, Elsevier, vol. 139(1), pages 234-259.
    18. Gonçalves, Andrei S. & Leonard, Gregory, 2023. "The fundamental-to-market ratio and the value premium decline," Journal of Financial Economics, Elsevier, vol. 147(2), pages 382-405.
    19. Jinghai He & Cheng Hua & Chunyang Zhou & Zeyu Zheng, 2025. "Reinforcement-Learning Portfolio Allocation with Dynamic Embedding of Market Information," Papers 2501.17992, arXiv.org.
    20. Shi, Huai-Long & Chen, Huayi, 2024. "Understanding co-movements based on heterogeneous information associations," International Review of Financial Analysis, Elsevier, vol. 94(C).
    21. Yanchu Liu & Heyang Zhou & Xiaoqiong Li & Jianfeng Liang & Haisheng Yang, 2025. "An Instrumented Principal Component Analysis Factor Model for Chinese Equity Options Returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 65(5), pages 4370-4390, December.
    22. Guillaume Coqueret & Tony Guida, 2020. "Training trees on tails with applications to portfolio choice," Annals of Operations Research, Springer, vol. 288(1), pages 181-221, May.
    23. Hanauer, Matthias X. & Kalsbach, Tobias, 2023. "Machine learning and the cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 55(C).
    24. 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).
    25. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    26. 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.
    27. 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).
    28. Harvey, Campbell R. & Liu, Yan, 2021. "Lucky factors," Journal of Financial Economics, Elsevier, vol. 141(2), pages 413-435.
    29. 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.
    30. Vu Le Tran & Guillaume Coqueret, 2023. "ESG news spillovers across the value chain," Financial Management, Financial Management Association International, vol. 52(4), pages 677-710, December.
    31. Joseph Abadi, 2026. "Demand-Based Asset Pricing in General Equilibrium," Working Papers 26-12, Federal Reserve Bank of Philadelphia.
    32. Michael Hasler & Charles Martineau, 2023. "Explaining the Failure of the Unconditional CAPM with the Conditional CAPM," Management Science, INFORMS, vol. 69(3), pages 1835-1855, March.
    33. Byun, Suk-Joon & Cho, Sangheum & Kim, Da-Hea, 2024. "Can a machine learn from behavioral biases? Evidence from stock return predictability of deep learning models," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    34. Huei-Wen Teng & Yu-Hsien Li, 2023. "Can deep neural networks outperform Fama-MacBeth regression and other supervised learning approaches in stock returns prediction with asset-pricing factors?," Digital Finance, Springer, vol. 5(1), pages 149-182, March.
    35. Jungjun Choi & Ming Yuan, 2025. "Inferential Theory for Pricing Errors with Latent Factors and Firm Characteristics," Papers 2511.03076, arXiv.org.
    36. Branco, Rafael R. & Rubesam, Alexandre & Zevallos, Mauricio, 2024. "Forecasting realized volatility: Does anything beat linear models?," Journal of Empirical Finance, Elsevier, vol. 78(C).
    37. Tobek, Ondrej & Hronec, Martin, 2021. "Does it pay to follow anomalies research? Machine learning approach with international evidence," Journal of Financial Markets, Elsevier, vol. 56(C).
    38. 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.
    39. Jorge Guijarro-Ordonez & Markus Pelger & Greg Zanotti, 2021. "Deep Learning Statistical Arbitrage," Papers 2106.04028, arXiv.org, revised Oct 2022.
    40. 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).
    41. Qin Yiyi & Jun Cai & Jie Zhu & Robert Webb, 2025. "Commodity Futures Characteristics and Asset Pricing Models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(3), pages 176-207, March.
    42. 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.).
    43. Ma, Tian & Sheng, Haoyun & Wang, Yuejie, 2024. "Noisy market, machine learning and fundamental momentum," Pacific-Basin Finance Journal, Elsevier, vol. 86(C).
    44. Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
    45. 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.
    46. 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).
    47. Karin Klieber, 2023. "Non-linear dimension reduction in factor-augmented vector autoregressions," Papers 2309.04821, arXiv.org.
    48. Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," CERGE-EI Working Papers wp677, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    49. 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.
    50. Xiaolu Wei & Hongbing Ouyang, 2023. "Forecasting Carbon Price Using Double Shrinkage Methods," IJERPH, MDPI, vol. 20(2), pages 1-20, January.
    51. Nima Afsharhajari & Jonathan Yu-Meng Li, 2026. "The Virtue of Sparsity in Complexity," Papers 2604.17166, arXiv.org.
    52. 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).
    53. Doron Avramov & Xin He, 2026. "Stochastic Discount Factors with Cross-Asset Spillovers," Papers 2602.20856, arXiv.org.
    54. Li, Zhiyong & Wang, Haixu & Yu, Mei, 2023. "Beyond rocket science: A factor model for convertible bond returns," Economics Letters, Elsevier, vol. 233(C).
    55. Wang, Feifei & Yan, Xuemin Sterling, 2021. "Downside risk and the performance of volatility-managed portfolios," Journal of Banking & Finance, Elsevier, vol. 131(C).
    56. Xuhui (Nick) Pan & Bharat Raj Parajuli & Petra Sinagl, 2025. "Firm Disclosures, Uncertain Profits, and (Indirectly) Priced Idiosyncratic Volatility," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 52(5), pages 2415-2437, November.
    57. 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).
    58. Yuan Liao & Viktor Todorov, 2024. "Changes in the span of systematic risk exposures," Quantitative Economics, Econometric Society, vol. 15(3), pages 817-847, July.
    59. 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.
    60. Niko Hauzenberger & Florian Huber & Karin Klieber, 2020. "Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques," Papers 2012.08155, arXiv.org, revised Dec 2021.
    61. Christian Fieberg & Lars Hornuf & Gerrit Liedtke & Thorsten Poddig, 2020. "Are Characteristics Covariances? A Comment on Instrumented Principal Component Analysis," CESifo Working Paper Series 8377, CESifo.
    62. Hai-Chuan Xu & Meng Wu & Wei-Xing Zhou, 2026. "Sparse principal component factors in asset pricing: evidence from the Chinese stock market," Annals of Operations Research, Springer, vol. 357(1), pages 505-529, February.
    63. Ruofan Xu & Qingliang Fan, 2025. "Single-Index Quantile Factor Model with Observed Characteristics," Papers 2506.19586, arXiv.org.
    64. Vasant Dhar & Jo~ao Sedoc, 2025. "DBOT: Artificial Intelligence for Systematic Long-Term Investing," Papers 2504.05639, arXiv.org.
    65. Fieberg, Christian & Osorio, Carlos & Poddig, Thorsten & Varmaz, Armin, 2026. "Enhancing index-tracking performance: Leveraging characteristic-based factor models for reduced estimation errors," European Journal of Operational Research, Elsevier, vol. 331(1), pages 278-291.
    66. Nechvátalová, Lenka, 2025. "Autoencoder asset pricing models and economic restrictions — international evidence," International Review of Financial Analysis, Elsevier, vol. 107(C).
    67. Guillaume Coqueret & Tony Guida, 2020. "Training trees on tails with applications to portfolio choice," Post-Print hal-04144665, HAL.
    68. Iason Kynigakis & Ekaterini Panopoulou, 2022. "Does model complexity add value to asset allocation? Evidence from machine learning forecasting models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 603-639, April.
    69. Konstantin Gorgen & Abdolreza Nazemi & Melanie Schienle, 2022. "Robust Knockoffs for Controlling False Discoveries With an Application to Bond Recovery Rates," Papers 2206.06026, arXiv.org.
    70. 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).
    71. 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.
    72. Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
    73. Fang, Yvonne & Hu, Xiaolu & Zhong, Angel & Pan, Zheyao & Cao, Youdan, 2026. "Machine learning in corporate bonds: Evidence from China," Journal of Banking & Finance, Elsevier, vol. 184(C).
    74. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2020. "Estimation of large dimensional conditional factor models in finance," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 219-282, Elsevier.
    75. Ahmad Haboub & Aris Kartsaklas & Vasilis Sarafidis, 2025. "Residual Income Valuation and Stock Returns: Evidence from a Value-to-Price Investment Strategy," Papers 2506.00206, arXiv.org.
    76. Riccardo Rebonato & Dherminder Kainth & Lionel Melin, 2025. "The Impact of Physical Climate Risk on the Valuation of Global Equity Assets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 88(4), pages 857-894, April.
    77. Zichuan Guo & Mihai Cucuringu & Alexander Y. Shestopaloff, 2025. "Generalized Factor Neural Network Model for High-dimensional Regression," Papers 2502.11310, arXiv.org, revised Mar 2025.
    78. Elizaveta V. Anufrieva, 2019. "Influence of Macroeconomic Factors on the Return of Russian Stock Exchange Indices," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 4, pages 75-87, August.
    79. Jinbo Cai & Wenze Li & Wenjie Wang, 2025. "Electricity Market Predictability: Virtues of Machine Learning and Links to the Macroeconomy," Papers 2507.07477, arXiv.org.
    80. Wang, Jinzhe & Zhu, Yifeng, 2024. "A comparison of factor models in China," Journal of Empirical Finance, Elsevier, vol. 79(C).
    81. Liu, Yanchu & Zhou, Heyang & Yang, Haisheng, 2025. "Latent factor models for the Chinese commodity futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 93(C).
    82. 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).
    83. Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2020. "Factor Timing," NBER Working Papers 26708, National Bureau of Economic Research, Inc.
    84. Ge, S. & Li, S. & Linton, O., 2020. "A Dynamic Network of Arbitrage Characteristics," Cambridge Working Papers in Economics 2060, Faculty of Economics, University of Cambridge.
    85. Bryzgalova, Svetlana & Huang, Jiantao & Julliard, Christian, 2020. "Bayesian solutions for the factor zoo: we just ran two quadrillion models," LSE Research Online Documents on Economics 118924, London School of Economics and Political Science, LSE Library.
    86. Adel Javanmard & Jingwei Ji & Renyuan Xu, 2024. "Multi-Task Dynamic Pricing in Credit Market with Contextual Information," Papers 2410.14839, arXiv.org, revised Dec 2025.
    87. 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.
    88. Chen, Xing & Huang, Rui & Wu, Chongfeng, 2026. "Quantile auto-encode narrative asset pricing model in the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 96(C).
    89. Yuhan Cheng & Heyang Zhou & Yanchu Liu, 2025. "Large Language Models and Futures Price Factors in China," Papers 2509.23609, arXiv.org.
    90. 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.
    91. Khem Raj Bhatt & Krishna Sharma, 2026. "Algorithmic Compliance and Regulatory Loss in Digital Assets," Papers 2603.04328, arXiv.org, revised Apr 2026.
    92. Shanyan Lai, 2025. "Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models," Papers 2508.19006, arXiv.org, revised Jun 2026.
    93. Eric Andr'e & Guillaume Coqueret, 2020. "Dirichlet policies for reinforced factor portfolios," Papers 2011.05381, arXiv.org, revised Jun 2021.
    94. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    95. Constant Aka & Marie‐Hélène Gagnon & Gabriel J. Power, 2025. "Commodity Option Return Predictability," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1544-1578, October.
    96. Christian Fieberg & Daniel Metko & Thorsten Poddig & Thomas Loy, 2023. "Machine learning techniques for cross-sectional equity returns’ prediction," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(1), pages 289-323, March.
    97. 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.
    98. 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.
    99. Patton, Andrew J. & Weller, Brian M., 2020. "What you see is not what you get: The costs of trading market anomalies," Journal of Financial Economics, Elsevier, vol. 137(2), pages 515-549.
    100. Nicolae Gârleanu & Lasse Heje Pedersen, 2022. "Active and Passive Investing: Understanding Samuelson’s Dictum [A noisy rational expectations equilibrium for multi-asset securities markets]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(2), pages 389-446.
    101. Mao, Jie & Shao, Jingjing & Wang, Weiguan, 2025. "Risk premium principal components for the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 89(C).
    102. 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.
    103. Guillaume Coqueret, 2022. "Characteristics-driven returns in equilibrium," Papers 2203.07865, arXiv.org.
    104. Krisna Nugraha & Muhtosim Arief & Sri Bramantoro Abdinagoro & Pantri Heriyati, 2022. "Factors Influencing Bank Customers’ Orientations toward Islamic Banks: Indonesian Banking Perspective," Sustainability, MDPI, vol. 14(19), pages 1-18, September.
    105. Chen, Minghui & Hanauer, Matthias X. & Kalsbach, Tobias, 2025. "Model complexity and the performance of global versus regional models," Economics Letters, Elsevier, vol. 257(C).
    106. Alex Kim & Maximilian Muhn & Valeri Nikolaev, 2023. "Bloated Disclosures: Can ChatGPT Help Investors Process Information?," Papers 2306.10224, arXiv.org, revised Oct 2025.
    107. Ma, Tian & Wang, Wanwan & Jiang, Fuwei, 2025. "Machine learning the performance of hedge fund," Journal of International Money and Finance, Elsevier, vol. 155(C).
    108. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "A diagnostic criterion for approximate factor structure," Journal of Econometrics, Elsevier, vol. 212(2), pages 503-521.
    109. William Forbes & Egor Kiselev & Len Skerratt, 2025. "Potential of fast and frugal trees in factor investing on the US equity market," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 24(2), pages 437-448, December.
    110. Shunwei Zhu & Chunyang Zhou, 2026. "Systematic Risk Factors in China's Stock Market: A High‐Frequency PCA Approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 66(1), pages 602-620, March.
    111. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    112. 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).
    113. 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.
    114. Su, Liangjun & Jin, Sainan & Wang, Xia, 2025. "Sieve estimation of state-varying factor models," Journal of Econometrics, Elsevier, vol. 251(C).
    115. Bruno Spilak & Wolfgang Karl Hardle, 2022. "Risk budget portfolios with convex Non-negative Matrix Factorization," Papers 2204.02757, arXiv.org, revised Jun 2023.
    116. 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).
    117. Andersen, Torben G. & Riva, Raul & Thyrsgaard, Martin & Todorov, Viktor, 2023. "Intraday cross-sectional distributions of systematic risk," Journal of Econometrics, Elsevier, vol. 235(2), pages 1394-1418.
    118. Hai Lin & Pengfei Liu & Cheng Zhang, 2023. "The trend premium around the world: Evidence from the stock market," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 317-358, June.
    119. Steffen Günther & Christian Fieberg & Thorsten Poddig, 2020. "The Cross-Section of Cryptocurrency Risk and Return," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 89(4), pages 7-28.
    120. Atanasova, Christina & Miao, Terrel & Segarra, Ignacio & Willeboordse, Frederick, 2025. "Aggregate illiquidity and crypto option returns," Finance Research Letters, Elsevier, vol. 85(PC).
    121. Chu Zhang, 2024. "Testing Pricing Errors of Models with Latent Factors and Firm Characteristics as Covariances," Management Science, INFORMS, vol. 70(3), pages 1706-1728, March.
    122. Yan Liu & Ye Luo & Zigan Wang & Xiaowei Zhang, 2026. "Uncertainty-Adjusted Sorting for Asset Pricing with Machine Learning," Papers 2601.00593, arXiv.org.
    123. Ai He & Guofu Zhou, 2023. "Diagnostics for asset pricing models," Financial Management, Financial Management Association International, vol. 52(4), pages 617-642, December.
    124. 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.
    125. Yong Zhang & Xinxiao Wu & Yunde Jia & Che Sun, 2026. "Game-Theoretic Modeling of Heterogeneous Investor Interactions for Stock Price Forecasting," Papers 2605.23953, arXiv.org.
    126. Son, Bumho & Lee, Jaewook, 2022. "Graph-based multi-factor asset pricing model," Finance Research Letters, Elsevier, vol. 44(C).
    127. Vu Le Tran & Guillaume Coqueret, 2023. "ESG news spillovers across the value chain," Post-Print hal-04325746, HAL.
    128. 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).
    129. Chun-I Lee & Chueh-Yung Tsao, 2024. "A comprehensive reexamination of the weather effects," Empirical Economics, Springer, vol. 66(3), pages 1333-1382, March.
    130. Ko, Hyungjin & Byun, Junyoung & Lee, Jaewook, 2023. "A privacy-preserving robo-advisory system with the Black-Litterman portfolio model: A new framework and insights into investor behavior," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    131. Fernando Moraes & Rodrigo De-Losso, 2020. "Risk Factor Centrality and the Cross-Section of Expected Returns," Working Papers, Department of Economics 2020_17, University of São Paulo (FEA-USP).
    132. Chen, Zhenhua & Liu, Zhenya & Teka, Hanen & Zhang, Yifan, 2022. "Smart money in China's A-share market: Evidence from big data," Research in International Business and Finance, Elsevier, vol. 61(C).
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    1. Elin Halvorsen & Hans Holter & Serdar Ozkan & Kjetil Storesletten, 2022. "Dissecting Idiosyncratic Earnings Risk," Working Papers 2022-024, Federal Reserve Bank of St. Louis, revised 02 Mar 2023.
    2. De Nardi, Mariacristina & Fella, Giulio & Knoef, Marike & Paz-Pardo, Gonzalo & Van Ooijen, Raun, 2021. "Family and government insurance: Wage, earnings, and income risks in the Netherlands and the U.S," Journal of Public Economics, Elsevier, vol. 193(C).
    3. David Domeij & Fatih Guvenen & Rocio Madera & Christopher Busch, 2020. "Skewed Idiosyncratic Income Risk over the Business Cycle: Sources and Insurance," Working Papers 1180, Barcelona School of Economics.

  3. Michiel De Pooter & Robert F. Martin & Seth Pruitt, 2015. "The Liquidity Effects of Official Bond Market Intervention," International Finance Discussion Papers 1138, Board of Governors of the Federal Reserve System (U.S.).

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    1. Christoph Trebesch & Jeromin Zettelmeyer, 2014. "ECB Interventions in Distressed Sovereign Debt Markets: The Case of Greek Bonds," CESifo Working Paper Series 4731, CESifo.
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    3. Yuriy Kitsul & Oleg Sokolinskiy & Jonathan H. Wright, 2022. "Market Effects of Central Bank Credit Markets Support Programs in Europe," International Finance Discussion Papers 1357, Board of Governors of the Federal Reserve System (U.S.).
    4. Wollmershäuser, Timo & Hristov, Nikolay & Hülsewig, Oliver & Siemsen, Thomas, 2014. "Smells Like Fiscal Policy? Assessing the Potential Effectiveness of the ECB s OMT Program," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100280, Verein für Socialpolitik / German Economic Association.
    5. Marco Casiraghi & Eugenio Gaiotti & Lisa Rodano & Alessandro Secchi, 2013. "The impact of unconventional monetary policy on the Italian economy during the sovereign debt crisis," Questioni di Economia e Finanza (Occasional Papers) 203, Bank of Italy, Economic Research and International Relations Area.
    6. Amy Y. Guisinger & Michael W. Mccracken & Michael T. Owyang, 2025. "Reconsidering the Fed's Inflation Forecasting Advantage," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 57(1), pages 5-30, February.
    7. Boneva, Lena & Kastl, Jakub & Zikes, Filip, 2025. "Dealer balance sheets and bidding behavior in the Bank of England’s QE reverse auctions," Journal of Financial Economics, Elsevier, vol. 174(C).
    8. Christophe Blot & Caroline Bozou & Jérôme Creel & Paul Hubert, 2021. "Are all Central Bank Asset Purchases the Same? Different Rationales, Different Effects," Sciences Po Economics Publications (main) hal-03554141, HAL.
    9. Blix Grimaldi, Marianna & Crosta, Alberto & Zhang, Dong, 2021. "The Liquidity of the Government Bond Market – What Impact Does Quantitative Easing Have? Evidence from Sweden," Working Paper Series 402, Sveriges Riksbank (Central Bank of Sweden).
    10. Bank for International Settlements, 2019. "Large central bank balance sheets and market functioning," Markets Committee Papers 11, Bank for International Settlements.
    11. Lena Boneva & David Elliott & Iryna Kaminska & Oliver Linton & Nick McLaren & Ben Morley, 2019. "The impact of corporate QE on liquidity: evidence from the UK," Bank of England Staff Working Paper series 782, Bank of England.
    12. Pateiro-Rodríguez, Carlos & Freire-Seoane, María Jesús & López-Bermúdez, Beatriz & Pateiro-López, Carlos, 2020. "Análisis de la tendencia a la liquidez del agregado monetario M3 en la eurozona: 1997-2018," El Trimestre Económico, Fondo de Cultura Económica, vol. 87(345), pages 171-201, enero-mar.
    13. Yuriy Kitsul & Oleg V. Sokolinskiy & Jonathan H. Wright, 2026. "Market Effects of Central Bank Credit Markets Support Programs in Europe," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 58(4), pages 937-967, June.
    14. Gómez-Puig, Marta & Pieterse-Bloem, Mary & Sosvilla-Rivero, Simón, 2023. "Dynamic connectedness between credit and liquidity risks in euro area sovereign debt markets," Journal of Multinational Financial Management, Elsevier, vol. 68(C).
    15. Weigerding, Michael, 2023. "Long-term liquidity effects of large-scale asset purchase programs: Evidence from the euro covered bond market," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 244-264.
    16. Eser, Fabian & Lemke, Wolfgang & Nyholm, Ken & Radde, Sören & Vladu, Andreea Liliana, 2019. "Tracing the impact of the ECB’s asset purchase programme on the yield curve," Working Paper Series 2293, European Central Bank.
    17. Eijffinger, Sylvester C.W. & Pieterse-Bloem, Mary, 2023. "Eurozone government bond spreads: A tale of different ECB policy regimes," Journal of International Money and Finance, Elsevier, vol. 139(C).
    18. Corradin, Stefano & Grimm, Niklas & Schwaab, Bernd, 2021. "Euro area sovereign bond risk premia during the Covid-19 pandemic," Working Paper Series 2561, European Central Bank.
    19. Ortmans, Aymeric & Tripier, Fabien, 2021. "COVID-induced sovereign risk in the euro area: When did the ECB stop the spread?," European Economic Review, Elsevier, vol. 137(C).
    20. Caballero, Diego & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2019. "Risk endogeneity at the lender/investor-of-last-resort," Working Paper Series 2225, European Central Bank.
    21. Hartmann, Philipp & Smets, Frank, 2018. "The first twenty years of the European Central Bank: monetary policy," CEPR Discussion Papers 13411, Centre for Economic Policy Research.
    22. Michele Anelli & Michele Patanè & Mario Toscano & Alessio Gioia, 2021. "The Evolution of the Lead-lag Markets in the Price Discovery Process of the Sovereign Credit Risk: the Case of Italy," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(2), pages 1-7.
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    Cited by:

    1. Markmann, Holger & Zietz, Joachim, 2017. "Determining the effectiveness of the Eurosystem’s Covered Bond Purchase Programs on secondary markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 66(C), pages 314-327.

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  6. Jinill Kim & Seth Pruitt, 2013. "Estimating Monetary Policy Rules When Nominal Interest Rates Are Stuck at Zero," CAMA Working Papers 2013-53, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.

    Cited by:

    1. Michael D. Bauer & Carolin E. Pflueger & Adi Sunderam, 2022. "Perceptions about Monetary Policy," CESifo Working Paper Series 10182, CESifo.
    2. Arai, Natsuki, 2023. "The FOMC’s new individual economic projections and macroeconomic theories," Journal of Banking & Finance, Elsevier, vol. 151(C).
    3. Ippei Fujiwara & Yoshiyuki Nakazono & Kozo Ueda, 2015. "Policy regime change against chronic deflation? Policy option under a long-term liquidity trap," Globalization Institute Working Papers 233, Federal Reserve Bank of Dallas.
    4. Ippei Fujiwara & Yoshiyuki Nakazono & Kozo Ueda, 2015. "Policy Regime Change Against Chronic Deflation?," Working Papers halshs-01545830, HAL.
    5. Jinill Kim & Seth Pruitt, 2017. "Estimating Monetary Policy Rules When Nominal Interest Rates Are Stuck at Zero," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(4), pages 585-602, June.
    6. Hibiki Ichiue & Yoichi Ueno, 2018. "A Survey-based Shadow Rate and Unconventional Monetary Policy Effects," IMES Discussion Paper Series 18-E-05, Institute for Monetary and Economic Studies, Bank of Japan.
    7. Yoshiyuki Nakazono, 2016. "Inflation expectations and monetary policy under disagreements," Bank of Japan Working Paper Series 16-E-1, Bank of Japan.
    8. Brent Bundick, 2015. "Estimating the Monetary Policy Rule Perceived by Forecasters," Economic Review, Federal Reserve Bank of Kansas City, issue Q IV, pages 33-49.
    9. Hirokuni Iiboshi & Mototsugu Shintani & Kozo Ueda, 2018. "Estimating a Nonlinear New Keynesian Model with the Zero Lower Bound for Japan," CAMA Working Papers 2018-37, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Shunsuke Haba & Ryuichiro Hirano & Yuichiro Ito & Sohei Kaihatsu, 2026. "Changes in Perceptions about Monetary Policy: Estimating the Policy Reaction Function Using Market Survey Data," Bank of Japan Working Paper Series 26-E-5, Bank of Japan.
    11. Donato Masciandaro, 2026. "Monetary Policy and Taylor Reaction Functions: Business Cycles, Central Bank Governance and Central Bankers’ Preferences," BAFFI CAREFIN Working Papers 26270, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

  7. James D. Hamilton & Seth Pruitt & Scott Borger, 2010. "Estimating the Market-Perceived Monetary Policy Rule," NBER Working Papers 16412, National Bureau of Economic Research, Inc.

    Cited by:

    1. Gorodnichenko, Y & Coibion, O, 2016. "How inertial is monetary policy? implications for the fed’s exit strategy," Department of Economics, Working Paper Series qt2qc6f09b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    2. Michael D. Bauer & Carolin Pflueger & Adi Sunderam, 2023. "Perceptions about Monetary Policy," Working Paper Series 2023-31, Federal Reserve Bank of San Francisco.
    3. Linda S. Goldberg & Christian Grisse, 2013. "Time Variation in Asset Price Responses to Macro Announcements," NBER Working Papers 19523, National Bureau of Economic Research, Inc.
    4. Ricardo Nunes & Ali Ozdagli & Jenny Tang, 2022. "Interest Rate Surprises: A Tale of Two Shocks," Working Papers 2213, Federal Reserve Bank of Dallas.
    5. Jinill Kim & Seth Pruitt, 2017. "Estimating Monetary Policy Rules When Nominal Interest Rates Are Stuck at Zero," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(4), pages 585-602, June.
    6. Klodiana Istrefi, 2019. "In Fed Watchers Eyes: Hawks, Doves and Monetary Policy," Working papers 725, Banque de France.
    7. Barrdear, John, 2015. "Towards a new Keynesian theory of the price level," LSE Research Online Documents on Economics 86315, London School of Economics and Political Science, LSE Library.
    8. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2016. "Estimating the Taylor Rule in the Time-Frequency Domain," CEF.UP Working Papers 1404, Universidade do Porto, Faculdade de Economia do Porto.
    9. Bedri Kamil Onur Tas & Ishak Demir, 2014. "Keep your Word: Time-varying Inflation Targets and Inflation Targeting Performance," Manchester School, University of Manchester, vol. 82(2), pages 160-182, March.
    10. Murphy, Austin & AlSalman, Zeina & Souropanis, Ioannis, 2025. "An investigation into the causes of stock market return deviations from real earnings yields," International Review of Economics & Finance, Elsevier, vol. 102(C).
    11. Lakdawala, Aeimit, 2016. "Changes in Federal Reserve preferences," Journal of Economic Dynamics and Control, Elsevier, vol. 70(C), pages 124-143.
    12. Endong Wang, 2024. "Local projections identify the same policy counterfactuals as empirical and structural models," Papers 2409.09577, arXiv.org, revised Feb 2026.
    13. Wataru Hagio & Daisuke Ikeda & Koji Takahashi & Keisuke Yoshida, 2026. "Mind the Gap When Exiting Low-for-Long," IMES Discussion Paper Series 26-E-02, Institute for Monetary and Economic Studies, Bank of Japan.
    14. Marwil J. Dávila-Fernández & Germana Giombini & Edgar J. Sánchez-Carrera, 2023. "Climateflation and monetary policy in an environmental OLG growth model," Department of Economics University of Siena 905, Department of Economics, University of Siena.
    15. Haitao Li & Tao Li & Cindy Yu, 2013. "No-Arbitrage Taylor Rules with Switching Regimes," Management Science, INFORMS, vol. 59(10), pages 2278-2294, October.
    16. Luís Francisco Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2014. "Analyzing the Taylor Rule with Wavelet Lenses," NIPE Working Papers 18/2014, NIPE - Universidade do Minho.
    17. Bertsch, Christoph & Hull, Isaiah & Lumsdaine, Robin L. & Zhang, Xin, 2025. "Central bank mandates and monetary policy stances: Through the lens of Federal Reserve speeches," Journal of Econometrics, Elsevier, vol. 249(PC).
    18. Shunsuke Haba & Ryuichiro Hirano & Yuichiro Ito & Sohei Kaihatsu, 2026. "Changes in Perceptions about Monetary Policy: Estimating the Policy Reaction Function Using Market Survey Data," Bank of Japan Working Paper Series 26-E-5, Bank of Japan.
    19. Lapp, John S. & Pearce, Douglas K., 2012. "The impact of economic news on expected changes in monetary policy," Journal of Macroeconomics, Elsevier, vol. 34(2), pages 362-379.
    20. Fernanda Nechio & Carlos Carvalho, 2012. "Do People Understand Monetary Policy?," 2012 Meeting Papers 426, Society for Economic Dynamics.
    21. Michael Ehrmann, 2014. "Targeting Inflation from Below - How Do Inflation Expectations Behave?," Staff Working Papers 14-52, Bank of Canada.
    22. Ma, Yong & Li, Shushu, 2015. "Bayesian estimation of China's monetary policy transparency: A New Keynesian approach," Economic Modelling, Elsevier, vol. 45(C), pages 236-248.
    23. Vijay A Murik, 2013. "Measuring monetary policy expectations," Australian Journal of Management, Australian School of Business, vol. 38(1), pages 49-65, April.
    24. Zhu, Dandan & Wang, Xiangdong & Zhang, Yifan, 2025. "Narrative monetary policy expectation in China," China Economic Review, Elsevier, vol. 94(PB).
    25. Christopher Healy & Chengcheng Jia, 2024. "Financial Markets’ Perceptions of the FOMC’s Data-Dependent Monetary Policy," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2024(03), pages 1-5, February.
    26. Luca Metelli & Filippo Natoli & Luca Rossi, 2020. "Monetary policy gradualism and the nonlinear effects of monetary shocks," Temi di discussione (Economic working papers) 1275, Bank of Italy, Economic Research and International Relations Area.
    27. Sandra Schmidt & Dieter Nautz, 2012. "Central Bank Communication and the Perception of Monetary Policy by Financial Market Experts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(2‐3), pages 323-340, March.
    28. John Y. Campbell & Carolin Pflueger & Luis M. Viceira, 2013. "Macroeconomic Drivers of Bond and Equity Risks," Harvard Business School Working Papers 14-031, Harvard Business School, revised Aug 2018.
    29. Donato Masciandaro, 2026. "Monetary Policy and Taylor Reaction Functions: Business Cycles, Central Bank Governance and Central Bankers’ Preferences," BAFFI CAREFIN Working Papers 26270, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.

  8. Max Floetotto & Nir Jaimovich & Seth Pruitt, 2009. "Markup variation and endogenous fluctuations in the price of investment goods," International Finance Discussion Papers 968, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Yaniv Yedid-Levi, 2016. "Why does employment in all major sectors move together over the business cycle?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 22, pages 131-156, October.
    2. Alain Gabler, 2014. "Relative Price Fluctuations in a Two-Sector Model with Imperfect Competition," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(3), pages 474-483, July.
    3. Alejandro Justiniano & Giorgio Primiceri & Andrea Tambalotti, 2011. "Investment Shocks and the Relative Price of Investment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 101-121, January.
    4. Marc-Andre Letendre & Joel Wagner, 2015. "Agnecy Costs, Risk Shocks and International Cycles," Department of Economics Working Papers 2015-09, McMaster University.
    5. Sohei Kaihatsu & Takushi Kurozumi, 2014. "Sources of Business Fluctuations: Financial or Technology Shocks?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 17(2), pages 224-242, April.

  9. Scott C. Borger & James D. Hamilton & Seth Pruitt, 2009. "The market-perceived monetary policy rule," International Finance Discussion Papers 982, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Michael D. Bauer, 2011. "Nominal interest rates and the news," Working Paper Series 2011-20, Federal Reserve Bank of San Francisco.
    2. Sinclair, Tara M. & Gamber, Edward N. & Stekler, Herman & Reid, Elizabeth, 2012. "Jointly evaluating the Federal Reserve’s forecasts of GDP growth and inflation," International Journal of Forecasting, Elsevier, vol. 28(2), pages 309-314.
    3. James D. Hamilton & Seth Pruitt & Scott Borger, 2011. "Estimating the Market-Perceived Monetary Policy Rule," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(3), pages 1-28, July.
    4. Jeffrey R. Campbell & Charles L. Evans & Jonas D. M. Fisher & Alejandro Justiniano, 2012. "Macroeconomic effects of Federal Reserve forward guidance," Working Paper Series WP-2012-03, Federal Reserve Bank of Chicago.
    5. Di Maggio, Marco, 2010. "The Political Economy of the Yield Curve," MPRA Paper 20697, University Library of Munich, Germany.
    6. Luis Viceira & Carolin Pflueger & John Campbell, 2014. "Monetary Policy Drivers of Bond and Equity Risks," 2014 Meeting Papers 137, Society for Economic Dynamics.
    7. Barrdear, John, 2015. "Towards a new Keynesian theory of the price level," LSE Research Online Documents on Economics 86315, London School of Economics and Political Science, LSE Library.
    8. Fernanda Nechio & Carlos Carvalho, 2012. "Do People Understand Monetary Policy?," 2012 Meeting Papers 426, Society for Economic Dynamics.
    9. Nikolay Markov & Thomas Nitschka, 2013. "Estimating Taylor Rules for Switzerland: Evidence from 2000 to 2012," Working Papers 2013-08, Swiss National Bank.

  10. Nir Jaimovich & Seth Pruitt & Henry E. Siu, 2009. "The demand for youth: implications for the hours volatility puzzle," International Finance Discussion Papers 964, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Sebastian Dyrda & Greg Kaplan & José-Víctor Ríos-Rull, 2012. "Business Cycles and Household Formation: The Micro vs the Macro Labor Elasticity," NBER Working Papers 17880, National Bureau of Economic Research, Inc.
    2. Alexandre Janiak & Paulo Santos Monteiro, 2011. "Towards a quantitative theory of automatic stabilizers: the role of demographics," Documentos de Trabajo 284, Centro de Economía Aplicada, Universidad de Chile.
    3. Greg Kaplan, 2014. "Business Cycles and Household Formation," 2014 Meeting Papers 82, Society for Economic Dynamics.
    4. Lugauer, Steven & Redmond, Michael, 2012. "The age distribution and business cycle volatility: International evidence," Economics Letters, Elsevier, vol. 117(3), pages 694-696.
    5. Diana Alessandrini & Stephen Kosempel & Thanasis Stengos, 2012. "The Business Cycle Human Capital Accumulation Nexus and its Effect on Labor Supply Volatility," Working Paper series 62_12, Rimini Centre for Economic Analysis.
    6. Lugauer, Steven, 2012. "Demographic Change And The Great Moderation In An Overlapping Generations Model With Matching Frictions," Macroeconomic Dynamics, Cambridge University Press, vol. 16(5), pages 706-731, November.
    7. Ariel Burstein & Javier Cravino & Jonathan Vogel, 2011. "Importing Skill-Biased Technology," NBER Working Papers 17460, National Bureau of Economic Research, Inc.
    8. Steven Lugauer, 2012. "Estimating the Effect of the Age Distribution on Cyclical Output Volatility Across the United States," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 896-902, November.
    9. Julia Dennett & Alicia Sasser Modestino, 2013. "Uncertain futures?: youth attachment to the labor market in the United States and New England," New England Public Policy Center Research Report 13-3, Federal Reserve Bank of Boston.

  11. Seth Pruitt, 2008. "Uncertainty over models and data: the rise and fall of American inflation," International Finance Discussion Papers 962, Board of Governors of the Federal Reserve System (U.S.).

    Cited by:

    1. Makin, Anthony J. & Robson, Alex & Ratnasiri, Shyama, 2017. "Missing money found causing Australia's inflation," Economic Modelling, Elsevier, vol. 66(C), pages 156-162.
    2. Pablo Aguilar & Jesús Vázquez, 2015. "The role of term structure in an estimated DSGE model with learning," LIDAM Discussion Papers IRES 2015007, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    3. Thomas A. Lubik & Christian Matthes, 2014. "Indeterminacy and Learning: An Analysis of Monetary Policy in the Great Inflation," Working Paper 14-2, Federal Reserve Bank of Richmond.
    4. Casares, Miguel & Vázquez, Jesús, 2016. "Data Revisions In The Estimation Of Dsge Models," Macroeconomic Dynamics, Cambridge University Press, vol. 20(7), pages 1683-1716, October.
    5. Aguilar, Pablo & Vázquez, Jesús, 2021. "An Estimated Dsge Model With Learning Based On Term Structure Information," Macroeconomic Dynamics, Cambridge University Press, vol. 25(7), pages 1635-1665, October.
    6. Lafuente, Juan A. & Pérez, Rafaela & Ruiz, Jesús, 2014. "Time-varying inflation targeting after the nineties," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 400-408.
    7. Xueting Yu & Yuhan Zhu & Guangming Lv, 2020. "Analysis of the Impact of China’s GDP Data Revision on Monetary Policy from the Perspective of Uncertainty," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1251-1274, May.

Articles

  1. Bryan Kelly & Diogo Palhares & Seth Pruitt, 2023. "Modeling Corporate Bond Returns," Journal of Finance, American Finance Association, vol. 78(4), pages 1967-2008, August.

    Cited by:

    1. Liu, Yuekun & Riley, Timothy B., 2025. "How should we measure the performance of corporate bond mutual funds? Evaluating model quality and impact on inferences," Journal of Banking & Finance, Elsevier, vol. 173(C).
    2. Yanchu Liu & Heyang Zhou & Xiaoqiong Li & Jianfeng Liang & Haisheng Yang, 2025. "An Instrumented Principal Component Analysis Factor Model for Chinese Equity Options Returns," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 65(5), pages 4370-4390, December.
    3. Alexander Dickerson & Cesare Robotti & Giulio Rossetti, 2026. "The Corporate Bond Factor Replication Crisis," Papers 2604.07880, arXiv.org.
    4. Qianwen Chen & Jaewon Choi, 2024. "Reaching for Yield and the Cross Section of Bond Returns," Management Science, INFORMS, vol. 70(8), pages 5226-5245, August.
    5. Redouane Elkamhi & Chanik Jo & Yoshio Nozawa, 2024. "A One-Factor Model of Corporate Bond Premia," Management Science, INFORMS, vol. 70(3), pages 1875-1900, March.
    6. Liu, Yanchu & Zhou, Heyang & Yang, Haisheng, 2025. "Latent factor models for the Chinese commodity futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 93(C).
    7. Haiying Wang & Ting Luo & Chonghui Jiang & Mingchen Sun, 2025. "Does carbon market add investment value in multi‐asset portfolios? Evidence from hedge, safe haven, and portfolio performance," International Review of Finance, International Review of Finance Ltd., vol. 25(3), September.
    8. 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).
    9. Liu, Zhen & Guo, Qiang & Yang, Shuangpeng, 2025. "Environmental Information Disclosure and Corporate Bond Spread," Finance Research Letters, Elsevier, vol. 86(PF).
    10. Hong, Yi & Xu, Maochun & Wen, Conghua, 2026. "On the dynamics of treasury bond yields: From term structure modelling to economic scenario generation," The British Accounting Review, Elsevier, vol. 58(2).
    11. Travis Cable & Amir Mani & Wei Qi & Georgios Sotiropoulos & Yiyuan Xiong, 2025. "On the Efficacy of Shorting Corporate Bonds as a Tail Risk Hedging Solution," Papers 2504.06289, arXiv.org.
    12. Desislava Vladimirova, 2024. "In the shadow of country risk: asset pricing model of emerging market corporate bonds," Journal of Asset Management, Palgrave Macmillan, vol. 25(5), pages 479-492, September.
    13. Kuong, John Chi-Fong & O’Donovan, James & Zhang, Jinyuan, 2024. "Monetary policy and fragility in corporate bond mutual funds," Journal of Financial Economics, Elsevier, vol. 161(C).
    14. DICKERSON, Alexander & NOZAWA, Yoshio & ROBOTTI, Cesare, 2025. "Factor Investing with Delays," Discussion Paper Series 771, Institute of Economic Research, Hitotsubashi University.
    15. Junyi Ye & Bhaskar Goswami & Jingyi Gu & Ajim Uddin & Guiling Wang, 2024. "From Factor Models to Deep Learning: Machine Learning in Reshaping Empirical Asset Pricing," Papers 2403.06779, arXiv.org.
    16. Mathieu Fournier & Kris Jacobs & Piotr Orłowski, 2024. "Modeling Conditional Factor Risk Premia Implied by Index Option Returns," Journal of Finance, American Finance Association, vol. 79(3), pages 2289-2338, June.

  2. Kelly, Bryan T. & Moskowitz, Tobias J. & Pruitt, Seth, 2021. "Understanding momentum and reversal," Journal of Financial Economics, Elsevier, vol. 140(3), pages 726-743.

    Cited by:

    1. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda & Melin, Olena, 2023. "Identification-robust beta pricing, spanning, mimicking portfolios, and the benchmark neutrality of catastrophe bonds," Journal of Econometrics, Elsevier, vol. 236(1).
    2. Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).
    3. 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).
    4. Xie, Jun & Fang, Yuying & Gao, Bin & Tan, Chunzhi, 2023. "Availability heuristic and expected returns," Finance Research Letters, Elsevier, vol. 51(C).
    5. Takano, Yuichi & Gotoh, Jun-ya, 2023. "Dynamic portfolio selection with linear control policies for coherent risk minimization," Operations Research Perspectives, Elsevier, vol. 10(C).
    6. Ross Koval & Nicholas Andrews & Xifeng Yan, 2025. "Multimodal Language Models with Modality-Specific Experts for Financial Forecasting from Interleaved Sequences of Text and Time Series," Papers 2509.19628, arXiv.org.
    7. Liu, Yanchu & Zhou, Heyang & Yang, Haisheng, 2025. "Latent factor models for the Chinese commodity futures markets," Pacific-Basin Finance Journal, Elsevier, vol. 93(C).
    8. Chen, Hong-Yi & Hsieh, Chia-Hsun & Lee, Cheng-Few, 2023. "Revisiting the momentum effect in Taiwan: The role of persistency," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
    9. Han, Yufeng & Mo, Xi Nancy & Yang, Jian, 2025. "Trend factors around the world: Performance and determinants," Journal of Banking & Finance, Elsevier, vol. 181(C).
    10. Fan, John Hua & Qiao, Xiao, 2023. "Commodity momentum: A tale of countries and sectors," Journal of Commodity Markets, Elsevier, vol. 29(C).
    11. Wu, Luyao & Wu, Jinshun, 2025. "Long memory of stock market return volatility and its impact on market efficiency," Finance Research Letters, Elsevier, vol. 86(PG).
    12. Tobias Wiest, 2023. "Momentum: what do we know 30 years after Jegadeesh and Titman’s seminal paper?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(1), pages 95-114, March.
    13. 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).
    14. Büsing, Pascal & Mohrschladt, Hannes & Siedhoff, Susanne, 2024. "Decomposing momentum: The forgotten component," Journal of Banking & Finance, Elsevier, vol. 168(C).
    15. Arbab Khalid Cheema & Wenjie Ding & Qingwei Wang, 2023. "The cross-section of January effect," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 513-530, October.
    16. Xingyue Pu & Stephen Roberts & Xiaowen Dong & Stefan Zohren, 2023. "Network Momentum across Asset Classes," Papers 2308.11294, arXiv.org.
    17. Gormsen, Niels Joachim & Jensen, Christian Skov, 2024. "Conditional risk," Journal of Financial Economics, Elsevier, vol. 162(C).
    18. Madhusmita Bhadra & Doyeon Kim, 2023. "Income elasticity of demand and stock market beta," International Finance, Wiley Blackwell, vol. 26(2), pages 225-240, August.
    19. Li, Yan & Liang, Chao & Huynh, Toan L.D. & He, Qiubei, 2022. "Price reversal and heterogeneous belief," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 104-119.
    20. Cai, Xing & Xia, Wei & Huang, Weihua & Yang, Haijun, 2024. "Dynamics of momentum in financial markets based on the information diffusion in complex social networks," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).
    21. Li, Yan & Huo, Jiale & Xu, Yongan & Liang, Chao, 2023. "Belief-based momentum indicator and stock market return predictability," Research in International Business and Finance, Elsevier, vol. 64(C).
    22. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2025. "Identification-robust and simultaneous inference in multifactor asset pricing models," Journal of Econometrics, Elsevier, vol. 248(C).
    23. Dong, Liang & Dai, Yiqing & Haque, Tariq & Kot, Hung Wan & Yamada, Takeshi, 2022. "Coskewness and reversal of momentum returns: The US and international evidence," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 241-264.
    24. Langlois, Hugues, 2023. "What matters in a characteristic?," Journal of Financial Economics, Elsevier, vol. 149(1), pages 52-72.
    25. Wang, Wenhao & Zhang, Qingyi & An, Pengda & Cai, Feifei, 2024. "Momentum and reversal strategies with low uncertainty," Finance Research Letters, Elsevier, vol. 68(C).
    26. Klaus Grobys, 2024. "Science or scientism? On the momentum illusion," Annals of Finance, Springer, vol. 20(4), pages 479-519, December.
    27. Qingyuan Han, 2025. "Understanding price momentum, market fluctuations, and crashes: insights from the extended Samuelson model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-37, December.
    28. Beckmeyer, Heiner & Wiedemann, Timo, 2025. "All Days Are Not Created Equal: Understanding Momentum by Learning to Weight Past Returns," Journal of Banking & Finance, Elsevier, vol. 181(C).
    29. Bartram, Söhnke & Djuranovik, Leslie & Garratt, Anthony, 2021. "Currency Anomalies," CEPR Discussion Papers 15653, Centre for Economic Policy Research.
    30. Matteo Bagnara, 2024. "Asset Pricing and Machine Learning: A critical review," Journal of Economic Surveys, Wiley Blackwell, vol. 38(1), pages 27-56, February.
    31. Xin, Ling, 2024. "Short-term contrarian in the carbon emission market," Energy Economics, Elsevier, vol. 139(C).
    32. Zhang, Shaojun, 2022. "Dissecting currency momentum," Journal of Financial Economics, Elsevier, vol. 144(1), pages 154-173.
    33. Ashrafee T. Hossain & Mostafa Monzur Hasan & Abdullah‐Al Masum, 2026. "Political Risk, Political Polarization, and Earnings Management," The Financial Review, Eastern Finance Association, vol. 61(1), pages 175-200, February.
    34. Wei Guo, 2025. "Can Chinese stock market volatility forecast US news sentiment?," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(5), pages 4503-4523, October.

  3. Seth Pruitt & Nicholas Turner, 2020. "Earnings Risk in the Household: Evidence from Millions of US Tax Returns," American Economic Review: Insights, American Economic Association, vol. 2(2), pages 237-254, June.

    Cited by:

    1. Martin Eckhoff Andresen & Andreas Kostøl & Ross Milton & Corina Mommaerts & Luisa Wallossek, 2025. "Monthly Earnings Volatility and Household Pooling," CESifo Working Paper Series 12323, CESifo.
    2. Wouter Gelade & Maud Nautet & Céline Piton, 2026. "Labour supply of couples facing a risk of job loss," Empirical Economics, Springer, vol. 70(2), pages 1-30, February.
    3. Ana Sofia Pessoa, 2021. "Earnings Dynamics in Germany," CESifo Working Paper Series 9117, CESifo.
    4. Christopher Busch & David Domeij & Fatih Guvenen & Rocio Madera, 2022. "Skewed Idiosyncratic Income Risk over the Business Cycle: Sources and Insurance," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(2), pages 207-242, April.
    5. Dan Silverman, 2020. "Walking the Tightrope: Variable Income and Limited Liquidity Among the US Middle Class," Working Papers walking-the-tightrope-var, The Aspen Institute Economic Strategy Group.
    6. Nezih Guner & Yuliya Kulikova & Arnau Valladares-Esteban, 2025. "Does the Added Worker Effect Matter?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 56, April.
    7. Titan Alon & Matthias Doepke & Jane Olmstead-Rumsey & Michèle Tertilt, 2020. "This Time It's Different: The Role of Women's Employment in a Pandemic Recession," NBER Working Papers 27660, National Bureau of Economic Research, Inc.
    8. Fatih Guvenen & Serdar Ozkan & Rocio Madera, 2024. "Consumption Dynamics and Welfare under Non-Gaussian Earnings Risk," CESifo Working Paper Series 11135, CESifo.
    9. d'Astous, Philippe & Shore, Stephen H., 2024. "Human capital risk and portfolio choices: Evidence from university admission discontinuities," Journal of Financial Economics, Elsevier, vol. 154(C).
    10. Søren Leth‐Petersen & Johan Sæverud, 2022. "Inequality and dynamics of earnings and disposable income in Denmark 1987–2016," Quantitative Economics, Econometric Society, vol. 13(4), pages 1493-1526, November.
    11. Nuno Alves & Carlos Martins, 2025. "The anatomy of household income dynamics in Portugal," Economic Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies, Banco de Portugal, Economics and Research Department.
    12. Ji, Yuemei & Qi, Weiwen, 2025. "The motherhood penalty in employment: Evidence from UK Asian mothers during the pandemic," Journal of Asian Economics, Elsevier, vol. 100(C).
    13. Tertilt, Michèle & Doepke, Matthias & Olmstead-Rumsey, Jane, 2020. "This Time It’s Different: The Role of Women’s Employment in a Pandemic Recession," CEPR Discussion Papers 15149, Centre for Economic Policy Research.
    14. Joseph Altonji & Disa Hynsjo & Ivan Vidangos, 2023. "Individual Earnings and Family Income: Dynamics and Distribution," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 49, pages 225-250, July.
    15. Bloemen, Hans, 2021. "Labor Market Transitions of Members of Opposite-Sex Couples: Nonparticipation, Unemployed Search, and Employment," IZA Discussion Papers 14673, IZA Network @ LISER.
    16. d’Astous, Philippe & Shore, Stephen H., 2024. "Programs of study and earnings dynamics," Labour Economics, Elsevier, vol. 88(C).
    17. Andrew Taeho Kim & Matt Erickson & Yurong Zhang & ChangHwan Kim, 2022. "Who is the “She” in the Pandemic “She-Cession”? Variation in COVID-19 Labor Market Outcomes by Gender and Family Status," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 1325-1358, June.

  4. 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.
    See citations under working paper version above.
  5. De Pooter, Michiel & Martin, Robert F. & Pruitt, Seth, 2018. "The Liquidity Effects of Official Bond Market Intervention," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(1), pages 243-268, February.
    See citations under working paper version above.
  6. Jinill Kim & Seth Pruitt, 2017. "Estimating Monetary Policy Rules When Nominal Interest Rates Are Stuck at Zero," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(4), pages 585-602, June.
    See citations under working paper version above.
  7. Giglio, Stefano & Kelly, Bryan & Pruitt, Seth, 2016. "Systemic risk and the macroeconomy: An empirical evaluation," Journal of Financial Economics, Elsevier, vol. 119(3), pages 457-471.
    See citations under working paper version above.
  8. Kelly, Bryan & Pruitt, Seth, 2015. "The three-pass regression filter: A new approach to forecasting using many predictors," Journal of Econometrics, Elsevier, vol. 186(2), pages 294-316.

    Cited by:

    1. Marine Carrasco & Barbara Rossi, 2016. "In-sample inference and forecasting in misspecified factor models," Economics Working Papers 1530, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Matthew F. Dixon & Nicholas G. Polson & Kemen Goicoechea, 2022. "Deep Partial Least Squares for Empirical Asset Pricing," Papers 2206.10014, arXiv.org.
    3. Xi Dong & Yan Li & David E. Rapach & Guofu Zhou, 2022. "Anomalies and the Expected Market Return," Journal of Finance, American Finance Association, vol. 77(1), pages 639-681, February.
    4. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
    5. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    6. Duan, Huayou & Zhao, Chenchen & Wang, Lu & Liu, Guangqiang, 2024. "The relationship between renewable energy attention and volatility: A HAR model with markov time-varying transition probability," Research in International Business and Finance, Elsevier, vol. 71(C).
    7. Dai, Zhifeng & Kang, Jie & Hu, Yangli, 2021. "Efficient predictability of oil price: The role of number of IPOs and U.S. dollar index," Resources Policy, Elsevier, vol. 74(C).
    8. Hyeongwoo Kim & Kyunghwan Ko, 2019. "Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach," Auburn Economics Working Paper Series auwp2019-03, Department of Economics, Auburn University.
    9. 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).
    10. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    11. Yuan, Ying & Qu, Yong & Wang, Tianyang, 2025. "Predicting risk premiums: A constraint-based model," Journal of Empirical Finance, Elsevier, vol. 83(C).
    12. Pedro Isaac Chavez-Lopez & Tae-Hwy Lee, 2025. "Quantile-Covariance Three-Pass Regression Filter," Working Papers 202501, University of California at Riverside, Department of Economics.
    13. Antonios K. Alexandridis & Ekaterini Panopoulou & Ioannis Souropanis, 2024. "Forecasting exchange rates: An iterated combination constrained predictor approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 983-1017, July.
    14. Arabinda Basistha, 2023. "Estimation of short‐run predictive factor for US growth using state employment data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 34-50, January.
    15. Likun Lei & Yaojie Zhang & Yu Wei & Yi Zhang, 2021. "Forecasting the volatility of Chinese stock market: An international volatility index," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 1336-1350, January.
    16. Bernardo Raimundo & Jorge Miguel Bravo, 2026. "Forecasting meets Portfolio Theory: A Bibliometric Approach to Decision-Making under Uncertainty," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 13(1), pages 1-23, December.
    17. Pan, Shuiyang & Long, Suwan(Cheng) & Wang, Yiming & Xie, Ying, 2023. "Nonlinear asset pricing in Chinese stock market: A deep learning approach," International Review of Financial Analysis, Elsevier, vol. 87(C).
    18. Hyeongwoo Kim & Kyunghwan Ko, 2017. "Improving Forecast Accuracy of Financial Vulnerability: Partial Least Squares Factor Model Approach," Working Papers 2017-14, Economic Research Institute, Bank of Korea.
    19. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
    20. Barbarino, Alessandro & Bura, Efstathia, 2024. "Forecasting Near-equivalence of Linear Dimension Reduction Methods in Large Panels of Macro-variables," Econometrics and Statistics, Elsevier, vol. 31(C), pages 1-18.
    21. Zhang, Yaojie & He, Mengxi & Wen, Danyan & Wang, Yudong, 2023. "Forecasting crude oil price returns: Can nonlinearity help?," Energy, Elsevier, vol. 262(PB).
    22. Biao Guo & Hai Lin, 2020. "Volatility and jump risk in option returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1767-1792, November.
    23. Jiang, Fuwei & Liu, Hongkui & Tang, Guohao & Yu, Jiasheng, 2024. "Global mispricing matters," Journal of International Money and Finance, Elsevier, vol. 147(C).
    24. Wang, Yunqi & Zhou, Ti, 2023. "Out-of-sample equity premium prediction: The role of option-implied constraints," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 199-226.
    25. Mihnea Constantinescu, 2023. "Sparse Warcasting," Working Papers 01/2023, National Bank of Ukraine.
    26. 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.
    27. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
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    29. Wen, Danyan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2024. "Forecasting crude oil market volatility: A comprehensive look at uncertainty variables," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1022-1041.
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    167. Yuan Li & Yu Zhang, 2021. "Investor Sentiment, Idiosyncratic Risk, and Stock Price Premium: Evidence From Chinese Cross-Listed Companies," SAGE Open, , vol. 11(2), pages 21582440211, June.
    168. Erik Christian Montes Schütte, 2018. "In Search of a Job: Forecasting Employment Growth in the US using Google Trends," CREATES Research Papers 2018-25, Department of Economics and Business Economics, Aarhus University.
    169. Liang, Chao & Wang, Lu & Duong, Duy, 2024. "More attention and better volatility forecast accuracy: How does war attention affect stock volatility predictability?," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 1-19.
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  9. Nir Jaimovich & Seth Pruitt & Henry E. Siu, 2013. "The Demand for Youth: Explaining Age Differences in the Volatility of Hours," American Economic Review, American Economic Association, vol. 103(7), pages 3022-3044, December.

    Cited by:

    1. Mankart, Jochen & Oikonomou, Rigas, 2015. "Household search and the aggregate labor market," Discussion Papers 26/2015, Deutsche Bundesbank.
    2. Guisinger, Amy Y., 2020. "Gender differences in the volatility of work hours and labor demand," Journal of Macroeconomics, Elsevier, vol. 66(C).
    3. Doepke, Matthias & Tertilt, Michèle, 2016. "Families in Macroeconomics," IZA Discussion Papers 9802, IZA Network @ LISER.
    4. Martin Iseringhausen & Hauke Vierke, 2018. "What Drives Output Volatility? The Role of Demographics and Government Size Revisited," European Economy - Discussion Papers 075, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    5. Bardóczy, Bence & Savoia, Ettore & Vel´asquez-Giraldo, Mateo, 2026. "HANK Comes of Age: Monetary Policy with Heterogeneous Overlapping Generations," Working Paper Series 461, Sveriges Riksbank (Central Bank of Sweden).
    6. Jean-Olivier Hairault & François Langot & Thepthida Sopraseuth, 2014. "Why is Old Workers' Labor Market more Volatile? Unemployment Fluctuations over the Life-Cycle," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00972291, HAL.
    7. Remi Jedwab & Daniel Pereira & Mark Roberts, 2019. "Cities of Workers, Children or Seniors? Age Structure and Economic Growth in a Global Cross-Section of Cities," Working Papers 2019-13, The George Washington University, Institute for International Economic Policy.
    8. Kathrin Ellieroth, 2019. "Spousal Insurance, Precautionary Labor Supply, and the Business Cycle - A Quantitative Analysis," 2019 Meeting Papers 1134, Society for Economic Dynamics.
    9. Michael Olabisi, 2020. "Input–Output Linkages and Sectoral Volatility," Economica, London School of Economics and Political Science, vol. 87(347), pages 713-746, July.
    10. Rohrbacher, Stefan & Heer, Burkhard & Scharrer, Christian, 2014. "Aging, the Great Moderation and Business-Cycle Volatility in a Life-Cycle Model," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100564, Verein für Socialpolitik / German Economic Association.
    11. Gerdie Everaert & Hauke Vierke, 2015. "Demographics And Business Cycle Volatility A Spurious Relationship?," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 15/914, Ghent University, Faculty of Economics and Business Administration.
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    13. Laure Simon, 2023. "Fiscal Stimulus and Skill Accumulation over the Life Cycle," Staff Working Papers 23-9, Bank of Canada.
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    16. Maya Eden & Paul Gaggl, 2018. "On the Welfare Implications of Automation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 15-43, July.
    17. Vincenzo Atella & Lorenzo Carbonari & Paola Samà, 2017. "Hours Worked in Selected OECD Countries: an Empirical Assessment," CEIS Research Paper 412, Tor Vergata University, CEIS, revised 21 Jul 2017.
    18. Kathrin Ellieroth, 2017. "Cyclicality of Hours Worked by Married Women and Spousal Insurance," CAEPR Working Papers 2017-009, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    19. Henrique S. Basso & Omar Rachedi, 2021. "The Young, the Old, and the Government: Demographics and Fiscal Multipliers," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 110-141, October.
    20. Giuseppe Fiori & Domenico Ferraro, 2016. "Aging of the Baby Boomers: Demographics and Propagation of Tax Shocks," 2016 Meeting Papers 359, Society for Economic Dynamics.
    21. Sohei Kaihatsu & Maiko Koga & Tomoya Sakata & Naoko Hara, 2018. "Interaction between Business Cycles and Economic Growth," Bank of Japan Working Paper Series 18-E-12, Bank of Japan.
    22. Bence Bardóczy, 2024. "HANK Comes of Age: Monetary Policy with Heterogeneous Overlapping Generations," Finance and Economics Discussion Series 2024-052r1, Board of Governors of the Federal Reserve System (U.S.), revised 19 Dec 2025.
    23. Sigurdsson,Jósef & Jósef Sigurdsson, 2025. "Transitory Earnings Opportunities and Educational Scarring of Men," CESifo Working Paper Series 11807, CESifo.
    24. Marcos Gómez & Francisco Parro, 2019. "Unintended Displacement Effects of Youth Training Programs in a Directed Search Model," Journal of Labor Research, Springer, vol. 40(2), pages 230-247, June.
    25. Giacomo Mangiante, 2022. "Demographic Trends and the Transmission of Monetary Policy," Cahiers de Recherches Economiques du Département d'économie 22.04, Université de Lausanne, Faculté des HEC, Département d’économie.

  10. 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.

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    1. Carolin Pflueger & Emil Siriwardane & Adi Sunderam, 2018. "A Measure of Risk Appetite for the Macroeconomy," NBER Working Papers 24529, National Bureau of Economic Research, Inc.
    2. Lyle, Matthew R. & Wang, Charles C.Y., 2015. "The cross section of expected holding period returns and their dynamics: A present value approach," Journal of Financial Economics, Elsevier, vol. 116(3), pages 505-525.
    3. Seegmiller, Bryan, 2026. "Intermediation frictions in equity markets," Journal of Financial Economics, Elsevier, vol. 176(C).
    4. Liya Chu & Xue-Zhong He & Kai Li & Jun Tu, 2022. "Investor Sentiment and Paradigm Shifts in Equity Return Forecasting," Management Science, INFORMS, vol. 68(6), pages 4301-4325, June.
    5. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    6. Faria, Gonçalo & Verona, Fabio, 2017. "Forecasting the equity risk premium with frequency-decomposed predictors," Bank of Finland Research Discussion Papers 1/2017, Bank of Finland.
    7. Jiahan Li & Ilias Tsiakas, 2016. "Equity Premium Prediction: The Role of Economic and Statistical Constraints," Working Paper series 16-25, Rimini Centre for Economic Analysis.
    8. Lutzenberger, Fabian T., 2014. "The predictability of aggregate returns on commodity futures," Review of Financial Economics, Elsevier, vol. 23(3), pages 120-130.
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    10. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    11. Gonçalves, Andrei S. & Leonard, Gregory, 2023. "The fundamental-to-market ratio and the value premium decline," Journal of Financial Economics, Elsevier, vol. 147(2), pages 382-405.
    12. Yuan, Ying & Qu, Yong & Wang, Tianyang, 2025. "Predicting risk premiums: A constraint-based model," Journal of Empirical Finance, Elsevier, vol. 83(C).
    13. Cieslak, Anna & Pang, Hao, 2020. "Common shocks in stocks and bonds," CEPR Discussion Papers 14708, Centre for Economic Policy Research.
    14. Pedro Isaac Chavez-Lopez & Tae-Hwy Lee, 2025. "Quantile-Covariance Three-Pass Regression Filter," Working Papers 202501, University of California at Riverside, Department of Economics.
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    27. 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.
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