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Large Language Models as Financial Data Annotators: A Study on Effectiveness and Efficiency
Collecting labeled datasets in finance is challenging due to scarcity of domain experts and higher cost of employing them.
From Pixels to Predictions: Spectrogram and Vision Transformer for Better Time Series Forecasting
Time series forecasting plays a crucial role in decision-making across various domains, but it presents significant challenges.
REFinD: Relation Extraction Financial Dataset
A number of datasets for Relation Extraction (RE) have been created to aide downstream tasks such as information retrieval, semantic search, question answering and textual entailment.
Financial Time Series Forecasting using CNN and Transformer
In our experiments, we demonstrated the success of the proposed method in comparison to commonly adopted statistical and deep learning methods on forecasting intraday stock price change of S&P 500 constituents.
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