├── LICENSE ├── README.md └── .gitignore /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 Kieran Wood 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies: X-Trend Architecture 2 | ## About 3 | This is a placeholder for the code that accompanies our paper [Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies](https://arxiv.org/abs/2310.10500). We intend to release the code in the coming weeks. This work builds upon our previous papers [Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture](https://arxiv.org/abs/2112.08534) ([code](https://github.com/kieranjwood/trading-momentum-transformer)) and [Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection](https://arxiv.org/abs/2105.13727) ([code](https://github.com/kieranjwood/slow-momentum-fast-reversion)). All papers and updates can be found on [my website](https://kieranjwood.github.io/). 4 | 5 | > Forecasting models for systematic trading strategies do not adapt quickly when financial market conditions rapidly change, as was seen in the advent of the COVID-19 pandemic in 2020, causing many forecasting models to take loss-making positions. To deal with such situations, the authors propose a novel time-series trend-following forecaster that can quickly adapt to new market conditions, referred to as regimes. The authors leverage recent developments from the deep learning community and use few-shot learning. They propose the Cross Attentive Time-Series Trend Network -- X-Trend -- which takes positions attending over a context set of financial time-series regimes. X-Trend transfers trends from similar patterns in the context set to make forecasts, then subsequently take positions for a new distinct target regime. By quickly adapting to new financial regimes, X-Trend increases Sharpe ratio by 18.9% over a neural forecaster and 10-fold over a conventional Time-series Momentum strategy during the turbulent market period from 2018 to 2023. Our strategy recovers twice as quickly from the COVID-19 drawdown compared to the neural-forecaster. X-Trend can also take zero-shot positions on novel unseen financial assets obtaining a 5-fold Sharpe ratio increase versus a neural time-series trend forecaster over the same period. Furthermore, the cross-attention mechanism allows us to interpret the relationship between forecasts and patterns in the context set. 6 | 7 | 8 | ## References 9 | Please cite our papers with: 10 | ```bib 11 | @article{wood2023fewshot, 12 | title={Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies}, 13 | author={Wood, Kieran and Kessler, Samuel and Roberts, Stephen J and Zohren, Stefan}, 14 | journal={arXiv preprint arXiv:2310.10500}, 15 | year={2023} 16 | } 17 | 18 | @article{wood2021trading, 19 | title={Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture}, 20 | author={Wood, Kieran and Giegerich, Sven and Roberts, Stephen and Zohren, Stefan}, 21 | journal={arXiv preprint arXiv:2112.08534}, 22 | year={2021} 23 | } 24 | 25 | @article {wood22slowmomfastrev, 26 | author = {Wood, Kieran and Roberts, Stephen and Zohren, Stefan}, 27 | title = {Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection}, 28 | volume = {4}, 29 | number = {1}, 30 | pages = {111--129}, 31 | year = {2022}, 32 | doi = {10.3905/jfds.2021.1.081}, 33 | publisher = {Institutional Investor Journals Umbrella}, 34 | issn = {2640-3943}, 35 | URL = {https://jfds.pm-research.com/content/4/1/111}, 36 | eprint = {https://jfds.pm-research.com/content/4/1/111.full.pdf}, 37 | journal = {The Journal of Financial Data Science} 38 | } 39 | ``` 40 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; 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