Modality-aware Transformer for Financial Time series Forecasting

arXiv:2310.01232v2 Announce Type: replace
Abstract: Time series forecasting presents a significant challenge, particularly when its accuracy relies on external data sources rather than solely on historical values. This issue is prevalent in the financial sector, where the future behavior of time series is often intricately linked to information derived from various textual reports and a multitude of economic indicators. In practice, the key challenge lies in constructing a reliable time series forecasting model capable of harnessing data from diverse sources …

abstract accuracy arxiv behavior challenge cs.lg data data sources external data financial financial sector forecasting future information issue reports sector series textual time series time series forecasting transformer type values