Serhiy Kozak
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.RePEc Biblio mentions
As found on the RePEc Biblio, the curated bibliography of Economics:- Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2017.
"Shrinking the Cross Section,"
NBER Working Papers
24070, National Bureau of Economic Research, Inc.
- Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
- Nagel, Stefan & Santosh, Shrihari & Kozak, Serhiy, 2017. "Shrinking the Cross Section," CEPR Discussion Papers 12463, C.E.P.R. Discussion Papers.
Mentioned in:
- > Econometrics > Big Data
Working papers
- 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:
- Bryan Kelly & Boris Kuznetsov & Semyon Malamud & Teng Andrea Xu, 2024. "Large (and Deep) Factor Models," Papers 2402.06635, arXiv.org.
- 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:
- Li, Kai & Xu, Chenjie, 2024. "Intermediary-based equity term structure," Journal of Financial Economics, Elsevier, vol. 157(C).
- Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2020.
"Factor Timing,"
NBER Working Papers
26708, National Bureau of Economic Research, Inc.
- 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.
Cited by:
- Mikhail Chernov & Lars A. Lochstoer & Stig R. H. Lundeby, 2018.
"Conditional Dynamics and the Multi-Horizon Risk-Return Trade-Off,"
NBER Working Papers
25361, National Bureau of Economic Research, Inc.
- Mikhail Chernov & Lars A Lochstoer & Stig R H Lundeby, 2022. "Conditional Dynamics and the Multihorizon Risk-Return Trade-Off," The Review of Financial Studies, Society for Financial Studies, vol. 35(3), pages 1310-1347.
- Chernov, Mikhail & Lochstoer, Lars & Lundeby, Stig, 2018. "Conditional dynamics and the multi-horizon risk-return trade-off," CEPR Discussion Papers 13365, C.E.P.R. Discussion Papers.
- 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.
- 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.
- Cho, Thummim, 2020. "Turning alphas into betas: Arbitrage and endogenous risk," Journal of Financial Economics, Elsevier, vol. 137(2), pages 550-570.
- Nagel, Stefan & Santosh, Shrihari & Kozak, Serhiy, 2017.
"Shrinking the Cross Section,"
CEPR Discussion Papers
12463, C.E.P.R. Discussion Papers.
- Kozak, Serhiy & Nagel, Stefan & Santosh, Shrihari, 2020. "Shrinking the cross-section," Journal of Financial Economics, Elsevier, vol. 135(2), pages 271-292.
- Serhiy Kozak & Stefan Nagel & Shrihari Santosh, 2017. "Shrinking the Cross Section," NBER Working Papers 24070, National Bureau of Economic Research, Inc.
Cited by:
- 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).
- Alexander M. Chinco & Andreas Neuhierl & Michael Weber, 2019.
"Estimating The Anomaly Base Rate,"
NBER Working Papers
26493, National Bureau of Economic Research, Inc.
- Chinco, Alex & Neuhierl, Andreas & Weber, Michael, 2021. "Estimating the anomaly base rate," Journal of Financial Economics, Elsevier, vol. 140(1), pages 101-126.
- Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
- Yan, Jingda & Yu, Jialin, 2023. "Cross-stock momentum and factor momentum," Journal of Financial Economics, Elsevier, vol. 150(2).
- Giglio, Stefano & Feng, Guanhao & Xiu, Dacheng, 2020.
"Taming the Factor Zoo: A Test of New Factors,"
CEPR Discussion Papers
14266, C.E.P.R. Discussion Papers.
- Guanhao Feng & Stefano Giglio & Dacheng Xiu, 2019. "Taming the Factor Zoo: A Test of New Factors," NBER Working Papers 25481, National Bureau of Economic Research, Inc.
- 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.
- Paul Schneider & Christian Wagner & Josef Zechner, 2019.
"Low Risk Anomalies?,"
Swiss Finance Institute Research Paper Series
19-50, Swiss Finance Institute.
- Paul Schneider & Christian Wagner & Josef Zechner, 2020. "Low‐Risk Anomalies?," Journal of Finance, American Finance Association, vol. 75(5), pages 2673-2718, October.
- Schneider, Paul & Wagner, Christian & Zechner, Josef, 2016. "Low risk anomalies?," CFS Working Paper Series 550, Center for Financial Studies (CFS).
- 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.
- 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.
- Pan, Zhiyuan & Zhong, Hao & Wang, Yudong & Huang, Juan, 2024. "Forecasting oil futures returns with news," Energy Economics, Elsevier, vol. 134(C).
- Carl Remlinger & Bri`ere Marie & Alasseur Cl'emence & Joseph Mikael, 2021. "Expert Aggregation for Financial Forecasting," Papers 2111.15365, arXiv.org, revised Jul 2023.
- Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2022. "On modeling IPO failure risk," Economic Modelling, Elsevier, vol. 109(C).
- 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.
- 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).
- 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.
- 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).
- 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).
- Kozak, Serhiy & Santosh, Shrihari, 2020. "Why do discount rates vary?," Journal of Financial Economics, Elsevier, vol. 137(3), pages 740-751.
- Yoshimasa Uematsu & Takashi Yamagata, 2020. "Inference in Weak Factor Models," ISER Discussion Paper 1080, Institute of Social and Economic Research, Osaka University.
- Jorge Guijarro-Ordonez & Markus Pelger & Greg Zanotti, 2021. "Deep Learning Statistical Arbitrage," Papers 2106.04028, arXiv.org, revised Oct 2022.
- 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).
- Oleg Rytchkov & Xun Zhong, 2020. "Information Aggregation and P-Hacking," Management Science, INFORMS, vol. 66(4), pages 1605-1626, April.
- 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.
- Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2017. "Predicting Relative Returns," NBER Working Papers 23886, National Bureau of Economic Research, Inc.
- 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.).
- Andrew Y Chen & Tom Zimmermann & Jeffrey Pontiff, 2020. "Publication Bias and the Cross-Section of Stock Returns," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(2), pages 249-289.
- 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).
- David Ardia & Laurent Barras & Patrick Gagliardini & Olivier Scaillet, 2020. "Is it Alpha or Beta? Decomposing Hedge Fund Returns When Models are Misspecified," Swiss Finance Institute Research Paper Series 20-82, Swiss Finance Institute, revised May 2023.
- Maysam Khodayari Gharanchaei & Prabhu Prasad Panda & Xilin Chen, 2024. "Quantitative Investment Diversification Strategies via Various Risk Models," Papers 2407.01550, arXiv.org.
- 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.
- Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021.
"Can machine learning help to select portfolios of mutual funds?,"
Economics Working Papers
1772, Department of Economics and Business, Universitat Pompeu Fabra.
- Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can Machine Learning Help to Select Portfolios of Mutual Funds?," Working Papers 1245, Barcelona School of Economics.
- 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.
- Martin Lettau & Markus Pelger, 2018.
"Estimating Latent Asset-Pricing Factors,"
NBER Working Papers
24618, National Bureau of Economic Research, Inc.
- Lettau, Martin & Pelger, Markus, 2020. "Estimating latent asset-pricing factors," Journal of Econometrics, Elsevier, vol. 218(1), pages 1-31.
- Lettau, Martin & Pelger, Markus, 2018. "Estimating Latent Asset-Pricing Factors," CEPR Discussion Papers 12926, C.E.P.R. Discussion Papers.
- Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018.
"Empirical Asset Pricing via Machine Learning,"
Swiss Finance Institute Research Paper Series
18-71, Swiss Finance Institute.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
- 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.
- B. Li & S. Boubaker & Z. Liu & W. Louhichi & Y. Yao, 2023. "Exploring the Nonlinear Idiosyncratic Volatility Puzzle: Evidence from China," Post-Print hal-04435519, HAL.
- 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.
- Lettau, Martin & Pelger, Markus, 2018.
"Factors that Fit the Time Series and Cross-Section of Stock Returns,"
CEPR Discussion Papers
13049, C.E.P.R. Discussion Papers.
- Martin Lettau & Markus Pelger, 2018. "Factors that Fit the Time Series and Cross-Section of Stock Returns," NBER Working Papers 24858, National Bureau of Economic Research, Inc.
- Martin Lettau & Markus Pelger & Stijn Van Nieuwerburgh, 2020. "Factors That Fit the Time Series and Cross-Section of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2274-2325.
- 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.
- Božović, Miloš, 2024. "VIX-managed portfolios," International Review of Financial Analysis, Elsevier, vol. 95(PA).
- 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.
- Thomas Conlon & John Cotter & Iason Kynigakis, 2021.
"Machine Learning and Factor-Based Portfolio Optimization,"
Papers
2107.13866, arXiv.org.
- Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Working Papers 202111, Geary Institute, University College Dublin.
- 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.
- Stanislav Anatolyev & Anna Mikusheva, 2018.
"Factor models with many assets: strong factors, weak factors, and the two-pass procedure,"
Papers
1807.04094, arXiv.org, revised Apr 2019.
- 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.
- Ian Martin & Stefan Nagel, 2019.
"Market Efficiency in the Age of Big Data,"
CESifo Working Paper Series
8015, CESifo.
- 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.
- Martin, Ian & Nagel, Stefan, 2019. "Market Efficiency in the Age of Big Data," CEPR Discussion Papers 14235, C.E.P.R. Discussion Papers.
- Martin, Ian W.R. & Nagel, Stefan, 2022. "Market efficiency in the age of big data," LSE Research Online Documents on Economics 112960, London School of Economics and Political Science, LSE Library.
- Ian Martin & Stefan Nagel, 2019. "Market Efficiency in the Age of Big Data," NBER Working Papers 26586, National Bureau of Economic Research, Inc.
- 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.
- 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.
- 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.
- 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.
- Christopher J. Neely, 2014.
"How Persistent Are Unconventional Monetary Policy Effects?,"
Working Papers
2014-004, Federal Reserve Bank of St. Louis, revised 15 Apr 2022.
- Neely, Christopher J., 2022. "How persistent are unconventional monetary policy effects?," Journal of International Money and Finance, Elsevier, vol. 126(C).
- Son, Bumho & Lee, Jaewook, 2022. "Graph-based multi-factor asset pricing model," Finance Research Letters, Elsevier, vol. 44(C).
- 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.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2018. "Economic Predictions with Big Data: The Illusion of Sparsity," Liberty Street Economics 20180521, Federal Reserve Bank of New York.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio E., 2021. "Economic predictions with big data: the illusion of sparsity," Working Paper Series 2542, European Central Bank.
- Giannone, Domenico & Lenza, Michele & Primiceri, Giorgio, 2017. "Economic Predictions with Big Data: The Illusion Of Sparsity," CEPR Discussion Papers 12256, C.E.P.R. Discussion Papers.
- Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2021. "Economic Predictions With Big Data: The Illusion of Sparsity," Econometrica, Econometric Society, vol. 89(5), pages 2409-2437, September.
- Smith, Simon C., 2022. "Time-variation, multiple testing, and the factor zoo," International Review of Financial Analysis, Elsevier, vol. 84(C).
- Constantinos Kardaras & Hyeng Keun Koo & Johannes Ruf, 2022. "Estimation of growth in fund models," Papers 2208.02573, arXiv.org.
- 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.
- 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.
- Almeida, Caio & Freire, Gustavo, 2022. "Pricing of index options in incomplete markets," Journal of Financial Economics, Elsevier, vol. 144(1), pages 174-205.
- Manresa, Elena & Peñaranda, Francisco & Sentana, Enrique, 2023.
"Empirical evaluation of overspecified asset pricing models,"
Journal of Financial Economics, Elsevier, vol. 147(2), pages 338-351.
- Sentana, Enrique & Manresa, Elena & Penaranda, Francisco, 2017. "Empirical Evaluation of Overspecified Asset Pricing Models," CEPR Discussion Papers 12085, C.E.P.R. Discussion Papers.
- Elena Manresa & Francisco Peñaranda & Enrique Sentana, 2017. "Empirical Evaluation of Overspecified Asset Pricing Models," Working Papers wp2017_1711, CEMFI.
- 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.
- Feng, Guanhao & He, Jingyu, 2022. "Factor investing: A Bayesian hierarchical approach," Journal of Econometrics, Elsevier, vol. 230(1), pages 183-200.
- Georges, Christophre & Pereira, Javier, 2021. "Market stability with machine learning agents," Journal of Economic Dynamics and Control, Elsevier, vol. 122(C).
- 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).
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2020.
"Dissecting Characteristics Nonparametrically,"
The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 6391, CESifo.
- Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2017. "Dissecting Characteristics Nonparametrically," NBER Working Papers 23227, National Bureau of Economic Research, Inc.
- Chen, Yi-Hsuan & Kräussl, Roman & Verwijmeren, Patrick, 2023. "The pricing of digital art," CFS Working Paper Series 716, Center for Financial Studies (CFS).
- Luyang Chen & Markus Pelger & Jason Zhu, 2024.
"Deep Learning in Asset Pricing,"
Management Science, INFORMS, vol. 70(2), pages 714-750, February.
- Luyang Chen & Markus Pelger & Jason Zhu, 2019. "Deep Learning in Asset Pricing," Papers 1904.00745, arXiv.org, revised Aug 2021.
- 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.
- Carter Davis, 2023. "The Elasticity of Quantitative Investment," Papers 2303.14533, arXiv.org, revised Sep 2024.
- 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.
- Andre Guettler & Mahvish Naeem & Lars Norden & Bernardus Van Doornik, 2024.
"Pre-Publication Revisions of Bank Financial Statements: a novel way to monitor banks?,"
Working Papers Series
590, Central Bank of Brazil, Research Department.
- 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).
- Langlois, Hugues, 2023. "What matters in a characteristic?," Journal of Financial Economics, Elsevier, vol. 149(1), pages 52-72.
- 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.
- Christophe Croux & Julapa Jagtiani & Tarunsai Korivi & Milos Vulanovic, 2020. "Important Factors Determining Fintech Loan Default: Evidence from the LendingClub Consumer Platform," Working Papers 20-15, Federal Reserve Bank of Philadelphia.
- Andrew Y. Chen & Jack McCoy, 2022. "Missing Values Handling for Machine Learning Portfolios," Papers 2207.13071, arXiv.org, revised Jan 2024.
- 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.
- 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.
- Valentin Haddad & Serhiy Kozak & Shrihari Santosh, 2020. "Factor Timing," NBER Working Papers 26708, National Bureau of Economic Research, Inc.
- Firoozye, Nikan & Tan, Vincent & Zohren, Stefan, 2023.
"Canonical portfolios: Optimal asset and signal combination,"
Journal of Banking & Finance, Elsevier, vol. 154(C).
- Nikan Firoozye & Vincent Tan & Stefan Zohren, 2022. "Canonical Portfolios: Optimal Asset and Signal Combination," Papers 2202.10817, arXiv.org, revised Jul 2023.
- Bank, Matthias & Insam, Franz, 2021. "Corporate aging and changes in the pricing of stock characteristics," Finance Research Letters, Elsevier, vol. 42(C).
- 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.
- 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).
- Guo, Li & Sang, Bo & Tu, Jun & Wang, Yu, 2024. "Cross-cryptocurrency return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 163(C).
- Alexandre Belloni & Mingli Chen & Oscar Hernan Madrid Padilla & Zixuan & Wang, 2019.
"High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing,"
Papers
1912.02151, arXiv.org, revised Aug 2022.
- 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.
- Uddin, Ajim & Yu, Dantong, 2020. "Latent factor model for asset pricing," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
- Birru, Justin & Gokkaya, Sinan & Liu, Xi & Markov, Stanimir, 2024. "Quants and market anomalies," Journal of Accounting and Economics, Elsevier, vol. 78(1).
- 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).
- Arpit Gupta & Stijn Van Nieuwerburgh, 2019.
"Valuing Private Equity Strip by Strip,"
NBER Working Papers
26514, National Bureau of Economic Research, Inc.
- Van Nieuwerburgh, Stijn & Gupta, Arpit, 2019. "Valuing Private Equity Strip by Strip," CEPR Discussion Papers 14241, C.E.P.R. Discussion Papers.
- Guanhao Feng & Jingyu He & Nicholas G. Polson, 2018. "Deep Learning for Predicting Asset Returns," Papers 1804.09314, arXiv.org, revised Apr 2018.
- Celso Brunetti & Marc Joëts & Valérie Mignon, 2024.
"Reasons Behind Words: OPEC Narratives and the Oil Market,"
Finance and Economics Discussion Series
2024-003, Board of Governors of the Federal Reserve System (U.S.).
- Valérie Mignon & Celso Brunetti & Marc Joëts, 2023. "Reasons Behind Words: OPEC Narratives and the Oil Market," EconomiX Working Papers 2023-24, University of Paris Nanterre, EconomiX.
- Celso Brunetti & Marc Joëts & Valérie Mignon, 2023. "Reasons Behind Words: OPEC Narratives and the Oil Market," Working Papers 2023-19, CEPII research center.
- Celso Brunetti & Marc Joëts & Valérie Mignon, 2023. "Reasons Behind Words: OPEC Narratives and the Oil Market," Working Papers hal-04196053, HAL.
- 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.).
- Rubesam, Alexandre, 2022.
"Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market,"
Emerging Markets Review, Elsevier, vol. 51(PB).
- Alexandre Rubesam, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Post-Print hal-03707365, HAL.
- Kelly, Bryan T. & Pruitt, Seth & Su, Yinan, 2019.
"Characteristics are covariances: A unified model of risk and return,"
Journal of Financial Economics, Elsevier, vol. 134(3), pages 501-524.
- Bryan Kelly & Seth Pruitt & Yinan Su, 2018. "Characteristics Are Covariances: A Unified Model of Risk and Return," NBER Working Papers 24540, National Bureau of Economic Research, Inc.
- 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.
- Vigo Pereira, Caio, 2021. "Portfolio efficiency with high-dimensional data as conditioning information," International Review of Financial Analysis, Elsevier, vol. 77(C).
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