Dr. Kekun Wu
序号 | 主题 | 时间 | Slides |
1 | A Brief Introduction to ML | wk1 | L01-introduction-slides |
2 | Shallow Learning Algorithms | wk2-wk5 | L02-regression-slides L03-classification-slides L04-trees-and-ensemble-learning-slides L05-unsupervised-learning-slides |
3 | Deep Neural Networks | wk6-7 | L06-deep-learning-I-slides, L06-Deep-Learning-II-slides |
4 | MDP & Reinforcement Learning | wk8 | L07a-MDP-slides L07b-RL-slides |
5 | SP1: Machine Learning & Asset Pricing & Financial Bigdata | by yourself | NBER Working Paper: Financial Machine Learning |
6 | ST2: Machine Learning and Causal Inference | by yourself | NBER SI 2015 Methods Lectures - Machine Learning for Economists 2018 AEA Continuing Education Webcasts: Machine Learning and Econometrics (Susan Athey, Guido Imbens) Machine Learning & Causal Inference: A Short Course |
[1] Athey S. The impact of machine learning on economics[J]. The economics of artificial intelligence: An agenda, 2018: 507-547.
[2] Athey S, Imbens G W. Machine learning methods that economists should know about[J]. Annual Review of Economics, 2019, 11: 685-725.
[3] Mullainathan S, Spiess J. Machine learning: an applied econometric approach[J]. Journal of Economic Perspectives, 2017, 31(2): 87-106.
[4] 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
[5] Goldstein I, Spatt C S, Ye M. Big data in finance[J]. The Review of Financial Studies, 2021, 34(7): 3213-3225.
[6] 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.
[7] 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.
[8] Amel-Zadeh, Amir and Calliess, Jan-Peter and Kaiser, Daniel and Roberts, Stephen, Machine Learning-Based Financial Statement Analysis (November 25, 2020). Available at SSRN: https://ssrn.com/abstract=3520684 or http://dx.doi.org/10.2139/ssrn.3520684
[9] Gu S, Kelly B, Xiu D. Empirical asset pricing via machine learning[J]. The Review of Financial Studies, 2020, 33(5): 2223-2273.
[10] Giglio, Stefano and Kelly, Bryan T. and Xiu, Dacheng, Factor Models, Machine Learning, and Asset Pricing (October 15, 2021). Available at SSRN: https://ssrn.com/abstract=3943284 or http://dx.doi.org/10.2139/ssrn.3943284
[11] Gu S, Kelly B, Xiu D. Autoencoder asset pricing models[J]. Journal of Econometrics, 2021, 222(1): 429-450.
[12] Kelly B T, Pruitt S, Su Y. Characteristics are covariances: A unified model of risk and return[J]. Journal of Financial Economics, 2019, 134(3): 501-524.
[13] Kozak S, Nagel S, Santosh S. Shrinking the cross-section[J]. Journal of Financial Economics, 2020, 135(2): 271-292.
[14] Tobek O, Hronec M. Does it pay to follow anomalies research? machine learning approach with international evidence[J]. Journal of Financial Markets, 2021, 56: 100588.
[15] Baba Yara, Fahiz and Boyer, Brian H. and Davis, Carter, The Factor Model Failure Puzzle (November 19, 2021). Available at SSRN: https://ssrn.com/abstract=3967588 or http://dx.doi.org/10.2139/ssrn.3967588
[16] Chen L, Pelger M, Zhu J. Deep learning in asset pricing[J]. Management Science, 2023.
[17] Bryzgalova, Svetlana and Pelger, Markus and Zhu, Jason, Forest Through the Trees: Building Cross-Sections of Stock Returns (September 25, 2020). Available at SSRN: https://ssrn.com/abstract=3493458 or http://dx.doi.org/10.2139/ssrn.3493458
[18] Giglio S, Liao Y, Xiu D. Thousands of alpha tests[J]. The Review of Financial Studies, 2021, 34(7): 3456-3496.
[19] 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.
[20] Jiang, Jingwen and Kelly, Bryan T. and Xiu, Dacheng, (Re-)Imag(in)ing Price Trends (December 1, 2020). Chicago Booth Research Paper No. 21-01, Available at SSRN: https://ssrn.com/abstract=3756587 or http://dx.doi.org/10.2139/ssrn.3756587
[21] Aït-Sahalia Y, Xiu D. Using principal component analysis to estimate a high dimensional factor model with high-frequency data[J]. Journal of Econometrics, 2017, 201(2): 384-399.
[22] Aït-Sahalia Y, Xiu D. Principal component analysis of high-frequency data[J]. Journal of the American Statistical Association, 2019, 114(525): 287-303.
[23] Kelly B T, Xiu D. Financial machine learning[R]. National Bureau of Economic Research, 2023.
[24] Lopez-Lira A, Tang Y. Can chatgpt forecast stock price movements? return predictability and large language models[J]. arXiv preprint arXiv:2304.07619, 2023.
[25] Yu S, Xue H, Ao X, et al. Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning[J]. arXiv preprint arXiv:2306.12964, 2023.
[26] Blitz D, Hanauer M X, Hoogteijling T, et al. The Term Structure of Machine Learning Alpha[J]. Available at SSRN, 2023.
[27] Hambly B, Xu R, Yang H. Recent advances in reinforcement learning in finance[J]. Mathematical Finance, 2023, 33(3): 437-503.
[28] Murray S, Xia Y, Xiao H. Charting by machines[J]. Journal of Financial Economics, 2024, 153: 103791.
[29] Potluru V K, Borrajo D, Coletta A, et al. Synthetic Data Applications in Finance[J]. arXiv preprint arXiv:2401.00081, 2024.
[30] Murray S, Xia Y, Xiao H. Charting by machines[J]. Journal of Financial Economics, 2024, 153: 103791.