ingest時出現ValueError: Failed to find any assets with country_code 'TW' that traded between 2023-05-05 00:00:00+00:00 and 2023-05-05 00:00:00+00:00. This probably means that your asset db is old or that it has incorrect country/exchange metadata.

[tej87681088]

原因

在run_pipeline的start及end期間內bundle至少要一家公司存在。可能是公司未上市，或bundle中沒該段時間的資料。

例如：

• bundle內只有一家公司2330，且start_date=20190102 end_date=20230731。利用!zipline bundle-info語法可得知下圖資訊：

• 若我執行run_pipeline()或run_algorithm()的end_date設定為'2023-08-30'，則會拋出以下錯誤：

• 原因是在20230801~20230830沒有任一家公司存活。

解法

• 調整run_pipeline()或run_algorithm()的start_date或end_date
• 重新ingest並設定正確的環境變數

  • os.environ['mdate']

  • os.environ['ticker']

• 或是利用$ zipline update語法更新bundle。

檢查程式

1. 檢查bundle資訊

 !zipline bundle-info

2. 檢查單檔個股start_date, end_date

from zipline.data import bundles
bundle_name='tquant'
symbol='1101'
bundle = bundles.load(bundle_name)

asset_=bundle.asset_finder.lookup_symbol(symbol, as_of_date=None)
asset_.start_date,asset_.end_date

3. 檢查所有個股lifetimes

# 參數
start = '2022-12-16'
end = '2023-08-30'
bundle_name='tquant'
#-----------------------------------------------------------------------

import os
import tejapi

# set tej_key and base
tej_key = <api key>
api_base = <api_base>

os.environ['TEJAPI_KEY'] = tej_key
os.environ['TEJAPI_BASE']= api_base

tejapi.ApiConfig.api_key = tej_key  
tejapi.ApiConfig.api_base = api_base

from zipline.data import bundles
from zipline.data.data_portal import DataPortal
from zipline.pipeline.domain import TW_EQUITIES
import pandas as pd


bundle = bundles.load(bundle_name)
sessions = TW_EQUITIES.all_sessions()
start_idx, end_idx = sessions.slice_locs(start, end)
extra_rows = 0
# Number of extra rows to compute before `start_date`.
# Extra rows are needed by terms like moving averages that require a
# trailing window of data.
            
lifetimes = bundle.asset_finder.lifetimes(
            dates = sessions[start_idx - extra_rows : end_idx],
            include_start_date=False,
            country_codes=('TW',),
        )
count_lifetimes = lifetimes.T.sum()
count_lifetimes_zero = count_lifetimes[count_lifetimes==0]

count_lifetimes_zero.index.min(), count_lifetimes_zero.index.max()