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Selecting Directors Using Machine Learning
[The role of boards of directors in corporate governance: A conceptual framework and survey]

Citations

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Cited by:

  1. Michalski, Lachlan & Low, Rand Kwong Yew, 2024. "Determinants of corporate credit ratings: Does ESG matter?," International Review of Financial Analysis, Elsevier, vol. 94(C).
  2. Liyang Tang, 2020. "Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment," Papers 2005.08735, arXiv.org.
  3. Bo Cowgill, 2019. "Bias and Productivity in Humans and Machines," Upjohn Working Papers 19-309, W.E. Upjohn Institute for Employment Research.
  4. Gao, Wei & Ju, Ming & Yang, Tongyang, 2023. "Severe weather and peer-to-peer farmers’ loan default predictions: Evidence from machine learning analysis," Finance Research Letters, Elsevier, vol. 58(PA).
  5. Mathieu Aubry & Roman Kräussl & Gustavo Manso & Christophe Spaenjers, 2023. "Biased Auctioneers," Journal of Finance, American Finance Association, vol. 78(2), pages 795-833, April.
  6. 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.
  7. Shumiao Ouyang & Hayong Yun & Xingjian Zheng, 2024. "How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs," Papers 2406.01168, arXiv.org, revised Aug 2024.
  8. Li, Ang & Liu, Mark & Sheather, Simon, 2023. "Predicting stock splits using ensemble machine learning and SMOTE oversampling," Pacific-Basin Finance Journal, Elsevier, vol. 78(C).
  9. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2020. "Why are some Chinese firms failing in the US capital markets? A machine learning approach," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
  10. McGinnity, Frances & Quinn, Emma & McCullough, Evie & Enright, Shannen, 2021. "Measures to combat racial discrimination and promote diversity in the labour market: A review of evidence," Research Series, Economic and Social Research Institute (ESRI), number SUSTAT110.
  11. Ilya Ivaninskiy & Irina Ivashkovskaya, 2022. "Are blockchain-based digital transformation and ecosystem-based business models mutually reinforcing? The principal-agent conflict perspective," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(4), pages 643-670, December.
  12. Santiago Mejia, 2023. "The Normative and Cultural Dimension of Work: Technological Unemployment as a Cultural Threat to a Meaningful Life," Journal of Business Ethics, Springer, vol. 185(4), pages 847-864, July.
  13. Christensen, Peter & Francisco, Paul & Myers, Erica & Shao, Hansen & Souza, Mateus, 2024. "Energy efficiency can deliver for climate policy: Evidence from machine learning-based targeting," Journal of Public Economics, Elsevier, vol. 234(C).
  14. Hanauer, Matthias X. & Kalsbach, Tobias, 2023. "Machine learning and the cross-section of emerging market stock returns," Emerging Markets Review, Elsevier, vol. 55(C).
  15. Giannetti, Mariassunta & Wang, Tracy Yue, 2020. "Public Attention to Gender Equality and the Demand for Female Directors," CEPR Discussion Papers 14503, C.E.P.R. Discussion Papers.
  16. Gormley, Todd A. & Gupta, Vishal K. & Matsa, David A. & Mortal, Sandra C. & Yang, Lukai, 2023. "The Big Three and board gender diversity: The effectiveness of shareholder voice," Journal of Financial Economics, Elsevier, vol. 149(2), pages 323-348.
  17. Hanauer, Matthias X. & Kononova, Marina & Rapp, Marc Steffen, 2022. "Boosting agnostic fundamental analysis: Using machine learning to identify mispricing in European stock markets," Finance Research Letters, Elsevier, vol. 48(C).
  18. Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2022. "On modeling IPO failure risk," Economic Modelling, Elsevier, vol. 109(C).
  19. Falco J. Bargagli-Stoffi & Jan Niederreiter & Massimo Riccaboni, 2020. "Supervised learning for the prediction of firm dynamics," Papers 2009.06413, arXiv.org.
  20. Matthew Harding & Gabriel F. R. Vasconcelos, 2022. "Managers versus Machines: Do Algorithms Replicate Human Intuition in Credit Ratings?," Papers 2202.04218, arXiv.org.
  21. Luca Coraggio & Marco Pagano & Annalisa Scognamiglio & Joacim Tåg, 2022. "JAQ of All Trades: Job Mismatch, Firm Productivity and Managerial Quality," EIEF Working Papers Series 2205, Einaudi Institute for Economics and Finance (EIEF), revised Mar 2022.
  22. Vasiliy Andreevich Laptev & Daria Rinatovna Feyzrakhmanova, 2021. "Digitalization of Institutions of Corporate Law: Current Trends and Future Prospects," Laws, MDPI, vol. 10(4), pages 1-19, December.
  23. Paul Geertsema & Helen Lu, 2023. "Relative Valuation with Machine Learning," Journal of Accounting Research, Wiley Blackwell, vol. 61(1), pages 329-376, March.
  24. Gao, Feng & Chi, Hong & Shao, Xueyan, 2021. "Forecasting residential electricity consumption using a hybrid machine learning model with online search data," Applied Energy, Elsevier, vol. 300(C).
  25. Amini, Shahram & Elmore, Ryan & Öztekin, Özde & Strauss, Jack, 2021. "Can machines learn capital structure dynamics?," Journal of Corporate Finance, Elsevier, vol. 70(C).
  26. Liu, Tingting & Lu, Zhongjin (Gene) & Shu, Tao & Wei, Fengrong, 2022. "Unique bidder-target relatedness and synergies creation in mergers and acquisitions," Journal of Corporate Finance, Elsevier, vol. 73(C).
  27. Steven Balsam & So Yean Kwack, 2022. "The impact of connections between the CEO and top executives on appointment, turnover and firm value," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(5-6), pages 882-933, May.
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