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Verified signature## NoLBERT: A Time-Stamped Pre-Trained LLM NoLBERT (No Lookahead(back) bias bidirectional encoder representation from transformers) is a foundational transformer-based language model specifically trained to avoid both lookahead and lookback bias. Lookahead bias is a fundamental challenge when researchers and practitioners use inferences from language models for forecasting. For example, when we ask a language model to infer the short-term return of a stock given a set of news articles, a concern is that the model may have been trained on data that include future information beyond the point in time when the news articles were released. As a result, the nature of the task changes from drawing return-related inference from text to retrieving the date of the news articles and the realized returns of the particular stock shortly after that date. Consequently, this approach becomes invalid in practice when using such models to predict stock returns beyond the training data's coverage pe…6664cb6 -
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