From df36839a7f680d71b900ea64efce09c2055dd31d Mon Sep 17 00:00:00 2001 From: you-n-g Date: Sat, 30 Oct 2021 21:36:15 +0800 Subject: [PATCH] Update README.md --- examples/benchmarks/README.md | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/examples/benchmarks/README.md b/examples/benchmarks/README.md index b1b1be82a..dfc4f492e 100644 --- a/examples/benchmarks/README.md +++ b/examples/benchmarks/README.md @@ -1,4 +1,9 @@ # Benchmarks Performance +This page lists a batch of methods designed for alpha seeking. Each method tries to give scores/predictions for all stocks each day(e.g. forecasting the future excess return of stocks). The scores/predictions of the models will be used as the mined alpha. Investing in stocks with higher scores is expected to yield more profit. + +The alpha is evaluated in two ways. +1. The correlation between the alpha and future return. +1. Constructing portfolio based on the alpha and evaluating the final total return. Here are the results of each benchmark model running on Qlib's `Alpha360` and `Alpha158` dataset with China's A shared-stock & CSI300 data respectively. The values of each metric are the mean and std calculated based on 20 runs with different random seeds.