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--- mycourse:machine_learning_and_finance [2024/09/20 23:08] – [主要参考文献] kk
+++ mycourse:machine_learning_and_finance [2025/12/01 13:39] (当前版本) – kk
@@ 行 8: / 行 8: @@
   * Wechat: {{ :mycourse:t7me_qr_code.jpg?nolink&150 |}}
 ===== 教学计划 =====
+  * ver2025
+| 序号 | 主题 | 时间 | Slides |
+| 1 | Introduction | wk1 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L01-Introduction-slides-v2025.html|L01-introduction-slides]] |
+| 2 | Shallow Learning | wk2 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L02-Shallow-slides-v2025.html|L02-shallow-slides]]；[[http://kktim.cn/teaching/mlinfin/MLinFin-L02-Shallow-slides-v2025-CN.html|L02中文机翻版]] |
+| 3 | Deep Learning | wk3 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L03-DL-slides-v2025.html|L03-DL-slides]]；[[http://kktim.cn/teaching/mlinfin/MLinFin-L03-DL-slides-v2025-CN.html|L03中文机翻版]] |
+| 4 | Reinforcement Learning | wk4 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L04-RL-slides-v2025.html|L04-RL-slides]]; [[http://kktim.cn/teaching/mlinfin/MLinFin-L04-RL-slides-v2025-CN.html|L04中文机翻版]] |
+| 5 | Big Data & ML | wk5 |  |
+| 6 | Empirical Asset Pricing & ML | wk6 |  |
+| 7 | Causal Inference & ML | wk7 |  |
+| 8 | LLMs & Agents | wk8 |  |
+  * ver2024
 | 序号 | 主题 | 时间 | Slides |
@@ 行 13: / 行 28: @@
 | 2 | Shallow Learning Algorithms | wk2-wk3 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L02-Regression-slides.html|L02-regression-slides]]\\ [[http://kktim.cn/teaching/mlinfin/MLinFin-L03-Classification-slides.html|L03-classification-slides]]\\ [[http://kktim.cn/teaching/mlinfin/MLinFin-L04-Trees-slides.html|L04-trees-and-ensemble-learning-slides]]\\ [[http://kktim.cn/teaching/mlinfin/MLinFin-L05-Unsupervised-Learning-slides.html|L05-unsupervised-learning-slides]] |
 | 3 | Deep Neural Networks | wk4 | [[http://kktim.cn/teaching/mlinfin/MLinFin-L06-Deep-Learning-slides.html|L06-deep-learning-I-slides]], [[http://kktim.cn/teaching/mlinfin/MLinFin-L06-Deep-Learning-II-slides.html|L06-Deep-Learning-II-slides]] |
-| 4 | Literature Studies | wk5-wk8 | - |
+| 4 | Literature Studies | wk5-wk8 | [[http://kktim.cn/teaching/mlinfin/MLinFin-LXX-Presentation-schedule-slides.html|Presentation Schedule]] |
 | 5 | MDP & Reinforcement Learning | by yourself | [[http://kktim.cn/teaching/mlinfin/MLinFin-L06-MDP-in-Finance-slides.html|L07a-MDP-slides]]\\  [[http://kktim.cn/teaching/mlinfin/MLinFin-L07-Advances-of-RL-in-Finance-slides.html|L07b-RL-slides]] |
 | 6 | SP1: Machine Learning & Asset Pricing & Financial Bigdata | by yourself | [[https://www.nber.org/papers/w31502|NBER Working Paper: Financial Machine Learning]] |
@@ 行 30: / 行 45: @@
   - Ashwin Rao, Tikhon Jelvis. Foundations of Reinforcement Learning with Applications in Finance[M]. Stanford University, 2022.
   - Denev A, Amen S. The Book of Alternative Data: A Guide for Investors, Traders and Risk Managers[M]. John Wiley & Sons, 2020.
+  - Gaillac C, L'Hour J. Machine Learning for Econometrics[M]. Oxford University Press, 2025.
 ===== 考核方式 =====
   - 考核方式：课程项目
-    - 项目展示：40%
+    - 平时（40%）：论文展示
-    - 项目报告：60%
+    - 期末（60%）：项目展示+ 项目报告
   - 课程项目内容（**同时**）包括：
     - 文献评述
@@ 行 45: / 行 61: @@
     - 内容必须**同时**与**机器学习**和**金融研究**密切相关
     - 无任何学术不端行为
-  - **DDL：15-Dec-2024, 20:00**：项目报告+PPT
+  - **DDL：31-Dec-2025, 20:00**：项目报告+PPT
   - 提交方式：百度网盘
@@ 行 201: / 行 217: @@
  [51] Kim, Alex G. and Muhn, Maximilian and Nikolaev, Valeri V., Financial Statement Analysis with Large Language Models (May 20, 2024). Chicago Booth Research Paper Forthcoming, Fama-Miller Working Paper, Available at SSRN: https://ssrn.com/abstract=4835311 or http://dx.doi.org/10.2139/ssrn.4835311
- <del>[52] Murray S, Xia Y, Xiao H. Charting by machines[J]. Journal of Financial Economics, 2024, 153: 103791.</del>
+ [52] Potluru V K, Borrajo D, Coletta A, et al. Synthetic Data Applications in Finance[J]. arXiv preprint arXiv:2401.00081, 2024.
- [53] Potluru V K, Borrajo D, Coletta A, et al. Synthetic Data Applications in Finance[J]. arXiv preprint arXiv:2401.00081, 2024.
 **Machine Learning and Financial Risk Management**
- [54] Cohen, Samuel N. and Snow, Derek and Szpruch, Lukasz, Black-Box Model Risk in Finance (February 9, 2021). Available at SSRN: https://ssrn.com/abstract=3782412 or http://dx.doi.org/10.2139/ssrn.3782412
+ [53] Cohen, Samuel N. and Snow, Derek and Szpruch, Lukasz, Black-Box Model Risk in Finance (February 9, 2021). Available at SSRN: https://ssrn.com/abstract=3782412 or http://dx.doi.org/10.2139/ssrn.3782412
- [55] Fuster A, Goldsmith‐Pinkham P, Ramadorai T, et al. Predictably unequal? The effects of machine learning on credit markets[J]. The Journal of Finance, 2022, 77(1): 5-47.
+ [54] Fuster A, Goldsmith‐Pinkham P, Ramadorai T, et al. Predictably unequal? The effects of machine learning on credit markets[J]. The Journal of Finance, 2022, 77(1): 5-47.
- [56] Luong T M, Scheule H, Wanzare N. Impact of mortgage soft information in loan pricing on default prediction using machine learning[J]. International Review of Finance, 2023, 23(1): 158-186.
+ [55] Luong T M, Scheule H, Wanzare N. Impact of mortgage soft information in loan pricing on default prediction using machine learning[J]. International Review of Finance, 2023, 23(1): 158-186.
- [57] Koelbl M, Laschinger R, Steininger B I, et al. Revealing the risk perception of investors using machine learning[J]. The European Journal of Finance, 2024: 1-27.
+ [56] Koelbl M, Laschinger R, Steininger B I, et al. Revealing the risk perception of investors using machine learning[J]. The European Journal of Finance, 2024: 1-27.
 **Machine Learning and Corporate Finance**
- [58] Erel I, Stern L H, Tan C, et al. Selecting directors using machine learning[J]. The Review of Financial Studies, 2021, 34(7): 3226-3264.
+ [57] Erel I, Stern L H, Tan C, et al. Selecting directors using machine learning[J]. The Review of Financial Studies, 2021, 34(7): 3226-3264.
- [59] Li K, Mai F, Shen R, et al. Measuring corporate culture using machine learning[J]. The Review of Financial Studies, 2021, 34(7): 3265-3315.
+ [58] Li K, Mai F, Shen R, et al. Measuring corporate culture using machine learning[J]. The Review of Financial Studies, 2021, 34(7): 3265-3315.
- [60] Bubb R, Catan E M. The party structure of mutual funds[J]. The Review of Financial Studies, 2022, 35(6): 2839-2878.
+ [59] Bubb R, Catan E M. The party structure of mutual funds[J]. The Review of Financial Studies, 2022, 35(6): 2839-2878.
- [61] Cao S, Jiang W, Yang B, et al. How to talk when a machine is listening: Corporate disclosure in the age of AI[J]. The Review of Financial Studies, 2023, 36(9): 3603-3642.
+ [60] Cao S, Jiang W, Yang B, et al. How to talk when a machine is listening: Corporate disclosure in the age of AI[J]. The Review of Financial Studies, 2023, 36(9): 3603-3642.
- [62] Babina T, Fedyk A, He A, et al. Artificial intelligence, firm growth, and product innovation[J]. Journal of Financial Economics, 2024, 151: 103745.
+ [61] Babina T, Fedyk A, He A, et al. Artificial intelligence, firm growth, and product innovation[J]. Journal of Financial Economics, 2024, 151: 103745.
- [63] Gofman M, Jin Z. Artificial intelligence, education, and entrepreneurship[J]. The Journal of Finance, 2024, 79(1): 631-667.
+ [62] Gofman M, Jin Z. Artificial intelligence, education, and entrepreneurship[J]. The Journal of Finance, 2024, 79(1): 631-667.
- [64] Halskov K. Improving Merger Arbitrage Returns with Machine Learning[J]. Available at SSRN, 2024.
+ [63] Halskov K. Improving Merger Arbitrage Returns with Machine Learning[J]. Available at SSRN, 2024.
- [65] Hansen J H, Siggaard M V. Double machine learning: Explaining the post-earnings announcement drift[J]. Journal of Financial and Quantitative Analysis, 2024, 59(3): 1003-1030.
+ [64] Hansen J H, Siggaard M V. Double machine learning: Explaining the post-earnings announcement drift[J]. Journal of Financial and Quantitative Analysis, 2024, 59(3): 1003-1030.
 **Machine Learning and Portfolio Management**
- [66] Duarte V, Fonseca J, Goodman A S, et al. Simple Allocation Rules and Optimal Portfolio Choice Over the Lifecycle[R]. National Bureau of Economic Research, 2021.
+ [65] Duarte V, Fonseca J, Goodman A S, et al. Simple Allocation Rules and Optimal Portfolio Choice Over the Lifecycle[R]. National Bureau of Economic Research, 2021.
- [67] Pinelis M, Ruppert D. Machine learning portfolio allocation[J]. The Journal of Finance and Data Science, 2022, 8: 35-54.
+ [66] Pinelis M, Ruppert D. Machine learning portfolio allocation[J]. The Journal of Finance and Data Science, 2022, 8: 35-54.
- [68] Chen A Y, McCoy J. Missing values handling for machine learning portfolios[J]. Journal of Financial Economics, 2024, 155: 103815.
+ [67] Chen A Y, McCoy J. Missing values handling for machine learning portfolios[J]. Journal of Financial Economics, 2024, 155: 103815.
 **Other Topics**
- [69] Dai R, Donohue L, Drechsler Q, et al. Dissemination, publication, and impact of finance research: When novelty meets conventionality[J]. Review of Finance, 2023, 27(1): 79-141.
+ [68] Dai R, Donohue L, Drechsler Q, et al. Dissemination, publication, and impact of finance research: When novelty meets conventionality[J]. Review of Finance, 2023, 27(1): 79-141.
- [70] Hambly B, Xu R, Yang H. Recent advances in reinforcement learning in finance[J]. Mathematical Finance, 2023, 33(3): 437-503.
+ [69] Hambly B, Xu R, Yang H. Recent advances in reinforcement learning in finance[J]. Mathematical Finance, 2023, 33(3): 437-503.
- [71] Sautner Z, Van Lent L, Vilkov G, et al. Firm‐level climate change exposure[J]. The Journal of Finance, 2023, 78(3): 1449-1498.
+ [70] Sautner Z, Van Lent L, Vilkov G, et al. Firm‐level climate change exposure[J]. The Journal of Finance, 2023, 78(3): 1449-1498.
- [72] Rossi A G, Utkus S. The diversification and welfare effects of robo-advising[J]. Journal of Financial Economics, 2024, 157: 103869.
+ [71] Rossi A G, Utkus S. The diversification and welfare effects of robo-advising[J]. Journal of Financial Economics, 2024, 157: 103869.