From 6a9ccd5ddbf95060a2847bd27bcdae762a46a19d Mon Sep 17 00:00:00 2001 From: TPTBusiness Date: Mon, 23 Mar 2026 15:42:52 +0100 Subject: [PATCH] fix: end-timestamp 23:45, weg, SZ-beispiele weg --- patches/qlib_experiment_prompts.yaml | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/patches/qlib_experiment_prompts.yaml b/patches/qlib_experiment_prompts.yaml index 4ba2c198..87b09e59 100644 --- a/patches/qlib_experiment_prompts.yaml +++ b/patches/qlib_experiment_prompts.yaml @@ -87,7 +87,7 @@ qlib_factor_strategy: |- qlib_factor_output_format: |- Your output should be a pandas dataframe similar to the following example information: - MultiIndex: 99904 entries, (Timestamp('2022-03-14 16:30:00'), 'EURUSD') to (Timestamp('2026-03-20 00:00:00'), 'EURUSD') + MultiIndex: 99904 entries, (Timestamp('2022-03-14 16:30:00'), 'EURUSD') to (Timestamp('2026-03-20 23:45:00'), 'EURUSD') Data columns (total 1 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- @@ -98,13 +98,6 @@ qlib_factor_output_format: |- One possible format of `result.h5` may be like following: datetime instrument 2022-03-14 EURUSD -0.000234 - SZ000166 0.005780 - SZ000686 0.004228 - SZ000712 0.001298 - SZ000728 0.005330 - ... - 2021-12-31 SZ000750 0.000000 - SZ000776 0.002459 qlib_factor_simulator: |- The factors will be sent into Qlib to train a model to predict the next several 15min bars return based on the factor values of the previous bars.