A domain-specific language model that parses central bank data has produced mixed results when it comes to predicting monetary policy stances, a Bank for International Settlements (BIS) study argues.
The working paper, published on October 1, looks at whether “central banking language models” (CB-LMs) can accurately assess sentiment from monetary policy statements.
Unlike large language models (LLMs) such as ChatGPT, CB-LMs are domain-specific. This means they are trained on data that exclusively
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@centralbanking.com
