| firmai/machine-learning-asset-management |
1,159 |
|
0 |
0 |
over 4 years ago |
0 |
|
2 |
|
Jupyter Notebook |
| Machine Learning in Asset Management (by @firmai) |
| OpenSourceAP/CrossSection |
516 |
|
0 |
0 |
over 2 years ago |
0 |
|
11 |
gpl-2.0 |
Stata |
| Code to accompany our paper Chen and Zimmermann (2020), "Open source cross-sectional asset pricing" |
| gudbrandtandberg/CPSC540Project |
93 |
|
0 |
0 |
almost 9 years ago |
0 |
|
1 |
|
Matlab |
| Project on financial forecasting using ML. Made by Anson Wong, Juan Garcia & Gudbrand Tandberg |
| tcloaa/Deep-Portfolio-Theory |
89 |
|
0 |
0 |
over 5 years ago |
0 |
|
3 |
|
Jupyter Notebook |
| Autoencoder framework for portfolio selection (paper published by J. B. Heaton, N. G. Polson, J. H. Witte.) |
| Feng-CityUHK/EquityCharacteristics |
63 |
|
0 |
0 |
over 2 years ago |
0 |
|
7 |
|
Python |
| Calculate U.S. equity (portfolio) characteristics |
| TatevKaren/TatevKaren-data-science-portfolio |
46 |
|
0 |
0 |
over 2 years ago |
0 |
|
1 |
|
Jupyter Notebook |
| Data Science Portfolio of Tatev Karen Aslanyan including Case Studies and Research Projects that I have completed that solve business problems or introduce new products. Case Study papers, codes, and additional resources are all included. |
| lingquant/msppy |
30 |
|
0 |
0 |
almost 5 years ago |
0 |
|
3 |
bsd-3-clause |
Python |
| ArdiaD/RiskPortfolios |
30 |
|
0 |
4 |
almost 5 years ago |
6 |
May 16, 2021 |
5 |
gpl-2.0 |
R |
| Functions for the construction of risk-based portfolios |
| hellojinwoo/CA_GMVP |
18 |
|
0 |
0 |
almost 4 years ago |
0 |
|
0 |
|
Python |
| Codes for the paper 'Clustering Approaches for Global Minimum Variance Portfolio' |
| DLColumbia/DL_forFinance |
17 |
|
0 |
0 |
almost 8 years ago |
0 |
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0 |
|
Jupyter Notebook |
| This git repository is based on the work of J.Heaton, N.Polson and J.Witte and their articleDeep Learning for Finance: Deep Portfolios. This paper let us explore the use of deeplearning models for problems in financial prediction and classification. Our goal isto show how applying deep learning methods to these problems can produce betteroutcomes than standard methods in finance or in Machine Learning |
