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qlib/examples/benchmarks/SFM
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dependabot[bot] aeb5e40c77 Bump numpy from 1.17.4 to 1.21.0 in /examples/benchmarks/SFM (#829) 
Bumps [numpy](https://github.com/numpy/numpy) from 1.17.4 to 1.21.0.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/HOWTO_RELEASE.rst.txt)
- [Commits](https://github.com/numpy/numpy/compare/v1.17.4...v1.21.0)

---
updated-dependencies:
- dependency-name: numpy
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>

Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2022-01-18 22:14:50 +08:00
..
README.md
Add author names
2020-12-11 17:19:12 +08:00
requirements.txt
Bump numpy from 1.17.4 to 1.21.0 in /examples/benchmarks/SFM (#829)
2022-01-18 22:14:50 +08:00
workflow_config_sfm_Alpha360.yaml
simplify signal parameter
2021-10-15 14:48:31 +00:00

README.md

State-Frequency-Memory

  • State Frequency Memory (SFM) is a novel recurrent network that uses Discrete Fourier Transform to decompose the hidden states of memory cells and capture the multi-frequency trading patterns from past market data to make stock price predictions.
  • Paper: Stock Price Prediction via Discovering Multi-Frequency Trading Patterns. http://www.eecs.ucf.edu/~gqi/publications/kdd2017_stock.pdf.