From 53620d4c085d6e1b675823e2b8c12f668d819bd8 Mon Sep 17 00:00:00 2001 From: lwwang1995 Date: Wed, 25 Nov 2020 18:38:17 +0800 Subject: [PATCH] Add readme for SFM. --- examples/benchmarks/SFM/README.md | 4 ++++ 1 file changed, 4 insertions(+) create mode 100644 examples/benchmarks/SFM/README.md diff --git a/examples/benchmarks/SFM/README.md b/examples/benchmarks/SFM/README.md new file mode 100644 index 000000000..06ca50485 --- /dev/null +++ b/examples/benchmarks/SFM/README.md @@ -0,0 +1,4 @@ +# State-Frequency-Memory +- State Frequency Memory (SFM) is a novel recurrent network that uses Discrete Fourier Transform (DFT) to decompose the hidden states of memory cells and capture the multi-frequency trading patterns from past market data to make stock price predictions. +- The code used in Qlib is a pyTorch implementation of SFM (Zhang, L., Aggarwal, C., & Qi, G. J. (2017,)). +- Paper: Stock Price Prediction via Discovering Multi-Frequency Trading Patterns. https://www.cs.ucf.edu/~gqi/publications/kdd2017_stock.pdf. \ No newline at end of file